International Journal of Automation and Control (34 papers in press)
Assessment of Reading Material using Sensor Data
by Aniruddha Sinha, Sanjoy Kumar Saha, Anupam Basu
Abstract: Reading is characterized by a sequence of complex processing in the brain. The experienced cognitive load and engagement level play a major role in the assimilation of content. In this paper, for the evaluation of a textual content, we use Electroencephalogram (EEG) for brain signals and eyetracker for the eyegaze data. Experiment is done with two types (easy and difficult) of textual contents which are benchmarked using standard parameters of natural language processing. Features on Cognitive load and Engagement Index extracted from alpha and beta frequency bands of EEG are found to be discriminative from left-temporal and right-prefrontal lobes respectively. Statistical features, derived from the shift in eyegaze fixations from the current line to the adjacent lines, are found to be discriminative. A difficulty score is computed using a novel mapping function derived from the mixture of two partial sigmoid. This enables more objective comparison of two contents and helps in finding differences in individual reading skills.
Keywords: textual content; eye-gaze; EEG; cognitive load; sigmoid.
Improved robust stability and stabilization conditions for discrete-time linear systems with time-varying delay
by Venkatesh Modala, Sourav Patra, Goshaidas Ray
Abstract: This paper presents robust stability and stabilization problems ofrnlinear discrete-time systems with interval time-varying state delay. By invoking a new Lyapunov-Krasovskii functional, a less conservative delay-dependent robust stability criterion is derived in terms of linear matrix inequalities (LMIs) using the summation inequality in combination with the extended reciprocally convex inequality. Then, a delay-dependent stabilization problem of discrete-time systems is explored by designing a state feedback controller. The superiority of the proposed result over existing ones is demonstrated through numerical examples.
Keywords: Time-delay systems; Robust stability; Stabilization; Lyapunov-Krasovskii functional; Summation inequality; Extended reciprocally convex inequality; Linear matrix inequality.
Residual based Fault Detection Isolation and Recovery of Greenhouse
by Rahul Singhal, Rajesh Kumar, Satyanarayana Neeli
Abstract: This paper is concerned with fault detection, isolation and recovery (FDIR) of the greenhouse whose temperature is regulated by the model predictive controller (MPC). The residual generation approach is adopted for fault detection and isolation. The new considerations in the proposed FDIR approach are the residual generation for actuator faults, regulation failure detection as the indication of inappropriate regulation by the controller, below threshold actuator fault detection strategy, and recovery operation updating model used by MPC once the FDIR isolates the actuator fault. The proposed control strategy FDIR with MPC was compared with fixed model information MPC for simulated scenarios of the actuator fault. It has been shown that FDIR successfully detects, isolates and updates model information with low computation burden for non-delayed control evaluation.
Keywords: Fault detection; fault isolation; fault recovery; greenhouse environment control; model predictive control.
A Multi-Objective Criterion and Stability Analysis for Neural Adaptive Control of Nonlinear MIMO Systems: An experimental validation
by Asma Atig, Fabrice Druaux, Dimitri Lefebvre, Ridha Ben Abdennour
Abstract: This paper presents a multi-objective indirect neural adaptive control design for nonlinear square multi-variable systems with unknown dynamics. The control scheme is made of an adaptive instantaneous Neural Emulator, a Neural Controller based on fully connected Real-Time Recurrent Learning RTRL networks and an online parameter updating law. A multi-objective criterion that takes into account the minimization of the control energy is considered. The contribution of this paper is to develop a new controller parameter optimization based on the Lyapunov stability analysis while ensuring control issues with environmental and economical objectives. Performance of the proposed approach in terms of regulation, tracking and minimization of the control energy is evaluated by numerical simulations of a disturbed nonlinear multi-variable system. The obtained control scheme is then applied in real time to a disturbed MIMO thermal process.
Keywords: Multi-objective approach; Adaptive control; Stability analysis; Recurrent Neural Networks; Nonlinear systems; MIMO processes.
Design and Optimization of a Fuzzy-PI Controlled Modified Inverter based PMSM Drive Employed in Light Weight Electric Vehicle
by Chiranjit Sain, Atanu Banerjee, Pabitra Kumar Biswas, Ahmad Taher Azar
Abstract: In this paper a PWM (Pulse Width Modulation) controlled permanent magnet synchronous motor (PMSM) is designed and illustrated using fuzzy logic control. The traditional PI controller is modified as a fuzzy-PI controller for faster dynamic response. The fuzzy logic operated speed controller ensures an almost zero steady-state speed error in this proposed approach. In addition, a stochastic optimization tool such as the updated particle swarm optimization (PSO) technique is used to optimize the performance of the proposed fuzzy logic controller. Further, the armature current response is sinusoidal in a sinusoidal PWM control strategy. The pulse width modulated buck-converter fed voltage source inverter (VSI) acts as a current source inverter (CSI) and is remarkably efficient in minimizing the voltage and current ripples compared to the traditional VSI. The economical as well as robust design procedure for the buck converter fed VSI is also proposed. With the configuration of the inverter, an improved over-current protection method is developed for the permanent magnet motor in a real-time light electric vehicle. Later, the control strategy of the developed prototype is tested and verified using a low-cost microcontroller. Furthermore, to improve the robustness of the drive, sensorless speed estimation procedure is also adopted in the real-time set-up. Finally, simulations and test results reveal the efficacy of this proposed approach over the existing control topologies.
Keywords: Electric vehicle; Fuzzy control; Optimization; PWM; PMSM.
A virtual GPS design using information of indoor localization system for robotics navigation
by Mohammad Hayajneh, Antonio Galiano
Abstract: For external robot platforms under development, people must perform repeated experiments to adjust the gains, log data and check performance. Therefore, carrying out such experiments outdoor, especially those requiring position information using Global Positioning System (GPS), could be inconvenient for researchers in this stage. Furthermore, Testing robots such as drones would increase the risk on people lives because of abnormal behaviors from non-proved approach. Therefore, the completion of experiments in the laboratory will be safer and faster, but it is known that the GPS receivers used in robots do not operate efficiently inside buildings. For this reason, this work has adopted a novel design of virtual GPS that calculate its data through an indoor motion tracking system. Basically, the approach of this work converts the position information provided by the motion tracking system in local frame into the corresponding global positions in geodetic coordinates. To maintain the actual connection between GPS and the robot, the location data set is formatted in specific binary structure using UBX messages and is provided through a serial connection to the GPS port in the robot side. To validate the adopted approach, real-time executions were performed on a powerful Linux computer that handles the computational cost of complex algorithms, provides serial communication with a quadcopter, and establishes the wireless communication with a ground station.
Keywords: virtual-GPS; Quadcopter; Optitrack; UBX; Pixhawk; Raspberry pi; Navigation.
Stable Optimal Self-tuning Interval Type-2 Fuzzy Controller for Servo Position Control System.
by Ritu Rani De (Maity), Rajani K. Mudi, Chanchal Dey
Abstract: An optimal self-tuning interval Type-2 fuzzy controller for servo position control systems is reported here. To achieve precise positioning of the actuator, input scaling factors of an interval Type-2 fuzzy proportional-integral controller are updated online depending on the latest operating conditions in terms of closed loop tracking error and change of error. To ensure desired performance, input scaling factors are obtained by adaptive cuckoo search based optimization algorithm. Efficacy of the proposed scheme is substantiated through performance comparison with recently reported peak observer based and online self-tuning based interval Type-2 fuzzy PID, interval Type-2 fuzzy PI, and also Type-1 fuzzy PI controllers through simulation study along with real-time validation on a DC servo position control system. Lyapunov function based stability analysis for the proposed controller is also provided.
Keywords: Type-2 fuzzy control; self-tuning mechanism; optimal fuzzy control; servo position control; real-time experimentation.
Closed-loop thickness control and sensor placement in extrusion blow molding
by Mostafa Darabi, Raffi Toukhtarian, Hossein Vahid Alizadeh, Benoit Boulet
Abstract: Extrusion Blow Molding (EBM) is a polymer forming technique
used in manufacturing processes which produce hollow plastic parts
such as fuel tanks for the automotive industry. Mathematical models
built using the Finite Element Method (FEM) and simulation-based
optimization of the extrusion process are studied extensively in the literature to improve the quality of the final parts as well as to minimize
material usage. Such optimization techniques are open-loop tasks that
obtain the optimal die gap setpoints for the next cycles of the EBM
process. When new feed material is introduced or an unexpected machine drift occurs, a trial and error method is used to retune the die
gap setpoints, which is time consuming and costly. Therefore, in this
work, the feasibility of using a closed-loop control approach in the
EBM process is studied to compensate for machine drift and disturbances in real time. An automatic control system for regulating the
extrusion process in EBM is proposed. The controller aims to increase
the consistency of the manufacturing process and minimize machine
drift. The thickness of the extrudate is measured in real time and any
unexpected drift is compensated for by changing the die gap instantly.
The model of the closed-loop system used in this work was developed
in previous work and has a transport Partial Differential Equation/
Non-linear Ordinary Differential Equation cascade structure model.
The controller has a Smith predictor configuration to compensate for
the input-dependent delay generated by the polymer transport partial
differential equation. In addition, H1 control theory is used to design
an optimal controller in order to maintain the desired extrudate thickness in the presence of disturbances or machine drift. A simulation
of the H1 controller system shows better thickness accuracy under
upset condition compared to the open loop system. This new control technique may reduce the useless of scrapped parts and improve
Keywords: H infinity controller; Optimal control; Smith predictor; Parameter identification; Polymer extrusion; Sensor placement; Variable die gap; Input-dependent delay; Hammerstein block.
Robust Attitude Stabilization Reactive Control of Quadruped Robot under Load Disturbance
by Xiaolu Zhu, Jinxiao Wan, Wei Xu, Chuan Zhou
Abstract: In order to solve the walking stability problem of quadruped robot under load disturbance, a robust attitude stabilization reactive control strategy based on ZMP (zero-moment point) stability criterion is proposed. This control strategy is composed of two layers, including an adaptive gait planner based on ZMP criterion at the upper planning layer and a robust joint angle tracking controller at the bottom layer. The adaptive gait planner calculates the desired ZMP position in real time by the robot body dynamics, which can adaptively plan the foot-end trajectory of the quadruped robot to ensure the attitude stability of the robot under load disturbance. The robust joint angle tracking controller is a sliding-mode tracking controller with disturbance observer, which calculates the disturbance and compensates for it through the complete dynamics of the quadruped robot with disturbance term. The robust joint angle tracking controller can enable quadruped robot to maintain robust joint angle tracking under the load disturbance. Finally, the effectiveness of the proposed reactive control strategy is verified by co-simulation of ADAMS and MATLAB.
Keywords: quadruped robot; load disturbance; zero-moment point (ZMP); disturbance observer; sliding-mode control; reactive control.
Load following approach for a VVER Nuclear Power Plant using Generic Model Control
by Khaled Rady, Mahmoud El Metwally, Ahmed Abouelsoud, Mahmoud Farrag, Said Kotb
Abstract: Possible application of generic nonlinear model control (GMC) for Dabaa pressurized water reactor (PWR) type nuclear power plant is studied for the load following operations. A self-adapting controller based on a generic minimal variance strategy is utilized. The controller design is modelled as a linear second-order model with unspecified time-varying parameters. Configuration parameters are modified online using an extended least square approach with a recursive prediction sequence; the controller is implemented on an optimized model from the literature. The cooling temperature is kept as close as possible to the desired value in the load following operating mode. The position of the control rod is selected as the control variable. The proposed controller was benchmarked against the conventional rod speed program controller (CRSP). The outcomes are promising and indicate the opportunity to implement the GMC approach for an actual nuclear power plant.
Keywords: Generic nonlinear model control ; nuclear power plant ; Robust Controller.
A Decoupler Assisted Optimized Controller Design for Greenhouse System
by SHRIJI GANDHI, Ravi Gandhi, Santosh Kakad, Manish Thakker
Abstract: This paper presents the application of the feedback feed-forward linearization integrated with the optimized PID controller for the greenhouse system (GHS). The GHS is a group of MIMO systems with highly coupled, disturbed, and nonlinear dynamics. Using the proposed approach, initially, the nonlinear MIMO system is separated into two independent SISO systems (i.e., temperature loop and humidity loop). After the decoupling, the separated loops are regulated by the Genetic Algorithm based optimized PID controllers. The extensive simulation study is carried out for the stabilizing and the tracking control operations for both the loops of the GHS in the presence of various initial conditions, various load disturbances (e.g. Canopy temperature, external temperature, external humidity, and solar radiation). Finally, the performance robustness of the proposed control structure is compared with the linear quadratic regulator(LQR) controller, conventional PID controller, and the Ziegler-Nichols tuned PID controller under diversified scenarios.
Keywords: Feedback feed-forward linearization; Greenhouse system; PID controller; Genetic Algorithm.
Novel Design of PID Controllers for Minimum and Non-Minimum Phase Time Delay Processes for Enhanced Performance
by Chandra Mohan Goud Ediga, Chidambaram M, Seshagiri Rao A
Abstract: A new technique is proposed for the design of PID controllers for minimum and non-minimum phase (NMP) stable first-order and second-order processes. The idea is to make the open-loop transfer function model equal to an integrating model with which the closed loop consists of first order dynamics. The resulting controller settings are functions of the tuning factor ? and process model parameters. The tuning parameter is selected based on the stability and robustness margins. Different case studies for simulation and experimental implementation are considered and the closed loop responses are examined. The proposed technique gives enhanced closed-loop performance for both set point and regulatory problems compared to the current techniques in both perfect and perturbed model conditions. Performance metrics such as integral error, control variation, stability margins, and sensitivity peak are compared and noted that the enhanced responses are achieved with the proposed simple method which has straight forward simple analytical relations for design of the controller.
Keywords: FOPTD process; SOPTD process; PID control; Total variation; Maximum sensitivity.
Adaptive differential evolution with linear population reduction for parameter estimation of solar cell models
by Zhen Yan, Wenyin Gong, Shuijia Li
Abstract: Parameter estimation of solar cell models is an important part of photovoltaic power generation system. However, it is still a challenging problem. In this study, an adaptive differential evolution with linear population reduction, called LRJADE, is developed to accurately estimate solar cell models parameters. In LRJADE, the linear population reduction strategy is employed to accelerate convergence speed. Additionally, the crossover rate repairing is also used. The performance of proposed LRJADE is verified by 13 benchmark functions and two solar cell model parameter estimation problems. Simulated results show that LRJADE not only obtains promising results in benchmark functions, but also achieves the very accurate solutions to solar cell model parameter estimation problems.
Keywords: Parameter estimation; solar cell models; differential evolution; adaptation.
Swarm Activity-Based Dynamic PSO for Distribution Decision
by Yu Su, Lingjuan Hou
Abstract: The distribution decision is a complicated constrained optimization problem that plays a key role in the production planning and inventory scheduling at the current era of intelligent big data, since few studies have developed new models integrating intelligent supply chain management. Aim at the limitation of traditional methods which are difficult to obtain feasible solutions in large-scale search space with limited time, a new swarm activity-based intelligent optimization algorithm, called PSO-SAW, is reconstructed in this paper by improving particle swarm optimization (PSO). The methodology is validated through several benchmarks and experimental applications to some distribution decision problems adopted from the literatures. Empirical results have implied the feasibility, effectiveness and robustness of the proposed method. Moreover, the experimental results of the algorithm have also verified the promising performances and applicability to distribution decision problems by comparing with other considered stochastic algorithms.
Keywords: particle swarm; swarm activity; dynamic inertia weight; distribution decision; supply chain optimization.
Intelligent Optimal Hybrid Motion/Force Control of Constrained Robot Manipulator
by Komal Rani, Naveen Kumar
Abstract: This paper presents a neural network based optimal control approach
for hybrid motion/force control problem of robot manipulators in the presence
of structured and unstructured uncertainties. The quadratic optimization with
sliding mode control and neural network is utilized to propose an optimal hybrid
motion/force control of robotic manipulators. Firstly, the dynamics of robot
manipulator is reduced into state-space form describing the constrained and
unconstrained motion separately. Then the optimal hybrid motion/force control
scheme is derived utilizing the optimization of Hamilton Jacobi Bellman (HJB)
equation and sliding mode control approach. The structured and unstructured
uncertainties of the system are compensated using radial basis function neural
network and adaptive compensator. The radial basis function neural network
approximates the unknown dynamics and adaptive compensator is used to
estimate the bounds on neural network approximation error and the unstructured
uncertainties of the system. The neural networks are trained in online manner
using weight update algorithms derived with Lyapunov approach to guarantee the
tracking stability and error convergence with prescribed quadratic performance
index. Finally, the proposed control approach are verified through simulation
results with two link constrained manipulator in a comparative manner.
Keywords: Optimal hybrid Motion/force control; Sliding mode control; Neuralrnnetwork; Constrained and unconstrained motion; Hamilton Jacobi Bellman (HJB)rnoptimization; performance index.
Development of modified LQG controller for mitigation of seismic vibrations using swarm intelligence
by Gaurav Kumar, Roshan Kumar, Ashok Kumar, Brij Mohan Singh
Abstract: A method is presented to design and tune the modified Linear Quadratic
Gaussian (LQG) controller to obtain increased efficiency during the earthquake.
It utilizes swarm intelligence to tune the parameters of LQG based on quasi
resonance between the natural frequencies of the structure in the first two modes
and the predominant frequencies of the seismic signal. The modified controller
thus developed minimizes the energy of structure by altering its parameters
online. For testing of this modified controller, a benchmark prototype structure
is numerically tested under different seismic signatures recorded in near/far fault sites in the different soil conditions. A parametric study comparing the efficiencies of modified LQG, and other contemporary controllers is presented. It is observed for the El-Centro earthquake that the modified controller achieved reductions of 22%, 33%, and 27% in relative displacement, inter-story drift, and absolute acceleration respectively as compared to the conventional LQG controller. Similar results are observed for Gebze and Chi-Chi earthquakes. The modified controller is also evaluated in a situation where power vanishes at the peak of the seismic excitation.
Based on the results and discussion, the performance of the proposed controller
is observed superior among all controllers considered in this study.
Keywords: Semi-active Control; Magneto-Rheological Damper; Seismic Vibrations; Optimal Control; Particle Swarm Optimization; LQG.
Numerical integration-like algorithm for time-optimal trajectory optimization of multi-axis motion system based on iterative learning
by Tie Zhang, Cailei Liao, Yanbiao Zou, Zhongqiang Kang, Caicheng Wu
Abstract: In order to realize the high-velocity and high-precision motion of multi-axis motion system, a numerical integration-like time-optimal trajectory optimization algorithm combined with iterative learning is proposed. Based on the established dynamic model of the multi-axis motion system, the mathematical model with time optimization as the objective function is derived under kinematics and dynamics constraints. The planned trajectory is discretized and the uniform acceleration equation (SUVAT) between any two adjacent discrete points is assumed so that pseudo-velocity planning of the phase plane is carried out by SUVAT equation instead of numerical integration method, after which the optimal solution satisfying the constraints can be obtained. In order to improve the dynamic model and reduce the errors between the calculated and the actual measured torques, a PD-type iterative learning method with forgetting factor is used to continuously update the dynamic model.
Keywords: high-velocity; high-precision; multi-axis motion system; time-optimal control; dynamic model; phase plane; numerical integration; iterative learning; forgetting factor.
Control of Three-Links Robot Arm Based on Fuzzy Neural Petri Nets
by Salam Abdul Hady1, Abduladhem Ali, Waleed Breesam, Ameer Saleh, Yasir Al-Yasir, Raed Abd-Alhameed
Abstract: A fuzzy neural Petri Nets (FNPN) controller is utilized for controlling three links robot arm which considers a nonlinear dynamic system. The incorporation of the classical FNN with a Petri net (PN) has been suggested to produce a new representing system called FNPN structure to alleviate the computation burden. The motion equation of three links robot arm is derived from Lagranges equation. This equation has been incorporated with the motion equations of DC Servo motors which motivate the robot. For nonlinearity dynamic problem, this paper presents a direct adaptive control technique to control three links robot arm utilizing FNPN controller. The computer simulation depicts that the present FNPN controller accomplished better performance with fast response and minimum error.
Keywords: Fuzzy neural Petri Net; Forward Adaptive Control; Robot Arm Control.
Globally linearizing control of linear time-fractional diffusion-advection-reaction systems
by Ahmed MAIDI, Jean-Pierre Corriou
Abstract: The globally linearising control (GLC) structure is adopted to solve both the step tracking and disturbance rejection problems for distributed parameter system described by a time-fractional partial differential equation. The actuation is assumed to be distributed in the spatial domain while the controlled output is defined as a spatial weighted average of the state. First, following a similar reasoning to geometric control and based on the late lumping approach, an infinite dimensional state feedback that yields a fractional finite dimensional system in closed loop is developed. Then, the input of this resulting closed-loop system is defined by means of a robust controller to cope with step disturbances. Assuming that the output shaping function is non-vanishing, on the spatial domain, it is demonstrated that the GLC strategy is stable. Two applications examples are presented to show, through simulation runs, the stabilisation, step tracking and disturbance rejection capabilities of the GLC scheme.
Keywords: distributed parameter system; time-fractional partial differential equation; distributed control; input-output linearisation; globally linearising control; GLC; diffusion-advection-reaction system.
Cruise Control of Autonomous Battery Electric Vehicle using Super Twisting Sliding Mode based Active Disturbance Rejection Control
by Suhail Ahmad Suhail, Mohammad Abid Bazaz, Shoeb Hussain
Abstract: This paper proposes a novel control scheme for the design of cruise control for an autonomous battery electric vehicle (BEV), based on active disturbance rejection control (ADRC) and super twisting sliding mode control (STSMC) featuring accuracy, and rapid convergence. The central concept is to combine the advantages of STSMC to track the reference trajectory accurately with the ability of ADRC to reject the parameter uncertainties and external disturbances. The combination of ADRC and STSMC relaxes the dependency of the controller on the accuracy of the plant model. Compared to the sliding mode control (SMC), adaptive SMC, and fast terminal SMC, the proposed control scheme is independent of the plant model. Simulations are carried out to assess the effectiveness of the proposed control scheme. The simulation results show that the proposed control strategy can significantly reduce the chattering phenomenon, owing to the estimation capability of extended state observer (ESO). The simulation results also show that the proposed strategy is much better in terms of tracking performance than ADRC and proportional integral derivative (PID). The proposed method improves the robustness against modelling errors and disturbances and performs smooth tracking of the reference.
Keywords: active disturbance rejection control; ADRC; electric vehicle; sliding mode control; SMC; cruise control; extended state observer; ESO.
H_infinity Stabilization of Uncertain Discrete Time-Delayed System with Actuator Saturation by using Wirtinger Inequality
by Komal Agrawal, Richa Negi, VIPIN CHANDRA PAL, Vishwajeet Patel
Abstract: This paper contemplates the H? control of discrete-time delayed systems together with actuator saturation, parametric uncertainties and disturbances. H?-based state feedback controller is conceived to stabilise the closed loop system. Lyapunov Krasovskii functional (LKF), discrete Wirtinger-based summation inequality and convex hull approach are combined to obtain novel regional stability conditions. The estimated attraction domain is maximised using an optimisation method along with linear matrix inequality (LMI). A omparative study is shown between the obtained and existing findings. The results are found to be less conservative than the prior ones. Finally, instances signify efficacy of presented approaches.
Keywords: time-delay; discrete system; actuator saturation; linear matrix inequality; LMI; H? control; Wirtinger inequality.
A novel optimised method for speckle reduction in medical ultrasound images
by V.B. Shereena, G. Raju
Abstract: The advancement of medical imaging techniques evolving from X-ray to PET images and the medical image analysis helped medical experts to detect, diagnose and offer treatments for complex disorders and deadly diseases in the human body. Among the various modalities used, Ultrasound imaging is the most widely accepted modality because of its affordability, non-invasive nature and various other features. But the presence of speckle noise in ultrasound image lowers the image quality and reduces diagnostic value. This article states an improved hybrid speckle noise reduction method, a combined application of Kuan and non-local means filters. In this method, Kuan filter is used to sharpen the edges and thereafter the speckle noise elimination is done by using the non-local means. In addition, the performance of the proposed hybrid filter and its design parameters are optimised by using a meta-heuristic called grey wolf optimiser. The performance of hybrid method is evaluated by analysing a chosen set of well-known post filtering methods used for speckle reduction with given ultrasound B-mode images. The comparison of test results using remarkable performance metrics and computation time demonstrate that the hybrid method can be used as the efficient speckle reduction method for image analysis.
Keywords: ultrasound image; speckle noise; multiplicative noise; performance metrics; spatial filter; transform domain filter; Kuan filter; non-local means filter; grey wolf optimisation; hybrid filter.
Parameter settings in particle swarm optimisation algorithms: a survey
by Jing Li, Shi Cheng
Abstract: In swarm intelligence, 'fair comparison' is critical for the performance evaluation of algorithms. In this paper, the setting of parameters in particle swarm optimisation (PSO) algorithms, which include the population size S, topology structure (number of neighbours k), inertia weight w, acceleration coefficient c1, c2, velocity constraint Vmax, and the boundary constraint strategy, are reviewed and analysed. Based on the analysis and discussion of parameters and the variants of PSO algorithms, a list of parameter settings of PSO algorithms and a recommendation of PSO comparison are given. To compare variants of PSO algorithms, a recommended solution maybe that all compared algorithms have the same number of population size and the maximum number of fitness evaluations, and the inertia weight w, acceleration coefficient c1, c2 are the same settings as its original version.
Keywords: swarm intelligence; particle swarm optimisation; PSO; parameter investigation; performance comparison.
Implementation of discrete-time fractional-order derivative controller for a class of double integrating system
by Jaydeep Swarnakar
Abstract: In this paper, a fractional-order derivative controller has been designed to control a double integrator plant towards satisfying the specific design criterions of frequency domain. The design approach employs a reference model. The open loop transfer function of the reference model is given by the Bode's ideal transfer function. The design is accomplished in two stages. At first, the reference model is obtained from the given design specifications and the transfer function of the continuous-time fractional-order derivative controller is derived subsequently. In the next stage, the fractional-order controller (FOC) has been realised in delta-domain involving continued fraction expansion method. The efficacy of the presented design methodology has been established through a comparative study with one of the conventional approaches pertaining to discrete-time implementation of FOC. The robustness of the closed loop controlled system is also tested against the uncertain plant gain. The essential simulation results have been presented using MATLAB.
Keywords: fractional-order derivative controller; double integrator system; continued fraction expansion; delta operator.
IMC-based anti-windup controller for real-time hot air flow and level control loop
by Ujjwal Manikya Nath, Chanchal Dey, Rajani K. Mudi
Abstract: In this study a new designing methodology of internal model control (IMC) with anti-windup feature is suggested. Due to presence of integral action in the conventional IMC structure reset, windup effect is found quite often. This limitation can be overcome by incorporating the proposed anti-windup scheme. Efficacy of the reported technique is experimentally verified on hot air flow process (User Manual, 2014) and level control loop (User Manual, 2010b).
Keywords: internal model control; IMC; IMC-PID; integral windup; anti-windup scheme; model identification; hot air flow process; level control system.
Control of the rated production power of DFIG-wind turbine using adaptive PSO and PI conventional controllers
by Hazem Hassan Ali, Ghada Saeed Elbasuony, Nashwa Ahmad Kamal
Abstract: Production of rated power and protection of generator and power converter from an overload are necessary. Therefore, measuring the accurate value of the pitch angle of the doubly fed induction generator (DFIG) wind turbine is essential. An assessment study between the adaptive particle swarm optimisation (PSO) technique and conventional proportional integral (PI) controller of the pitch control system in limiting the electrical output power at the rated value of DFIG is introduced in this study. Pitch control with PSO is designed by solving the nonlinear equation of pitch angle at each wind speed higher than rated wind speed. The PI controller gains of the pitch system are evaluated to keep the power limited at rated value. Accuracy in measuring pitch angle is essential because a small difference in pitch angle value results in an overload on the generator. The performance of each parameter of DFIG with a detailed analysis is studied. The simulation shows that the pitch control system with PSO technique gives better results in regulating the DFIG output power compared to PI controller method under wind speed variation.
Keywords: DFIG wind turbine; pitch controller; optimisation; particle swarm optimisation; PSO; conventional controller.
Special Issue on: Advances and Applications of Sliding Mode Control in Engineering
Fuzzy Adaptive Finite-Time Sliding Mode Controller for Trajectory Tracking of Ship Course Systems with Mismatched Uncertainties
by Pooyan Alinaghi Hosseinabadi, Ali Soltani Sharif Abadi, Saad Mekhilef
Abstract: In this paper, a new finite-time robust controller is designed for the ship heading (course) control systems with unknown mismatched external disturbances and uncertainties to fulfil trajectory tracking task. The adaptive method is utilized to estimate the upper bound of these mismatched disturbances and uncertainties. Meanwhile, the fuzzy logic is employed to enhance the tracking performance. In short, the fuzzy controller, adaptive, finite-time stability concepts and Sliding Mode Control (SMC) scheme have been incorporated to propose Fuzzy Adaptive Finite-time SMC (FAFSMC) scheme to utilize their benefits and to compensate the shortages of applying them individually. The finite-time stability analysis is investigated by utilizing the Lyapunov stability theory. The simulation results are carried out for the proposed fuzzy scheme and five other existing non-fuzzy schemes including Simple, Classical, Cubic, Hexagonal, and Switching to reveal the effectiveness of the proposed scheme compared to the other five schemes.
Keywords: fuzzy; sliding mode control; finite-time; adaptive; robust; Lyapunov.
Nonsingular terminal sliding mode control for a class of second-order systems with mismatched uncertainty
by Ning Zhao, Ye Zhang, Xincheng Yang, Dongya Zhao
Abstract: In this study, a novel method is proposed for a class of second-order systems to solve singularity problem and mismatched uncertainty in terminal sliding mode control (TSMC). Firstly, a state transformation method is designed to eliminate the reaching phase of terminal sliding mode, which can avoid the singularity problem fundamentally. In addition, mismatched uncertainty can be transferred to the same channel with control input after state transformation. Secondly, a novel controller is designed to stabilize the new form of the system in finite-time, while the mismatched uncertainty can be compensated effectively. Numerical simulations further validate the effectiveness of the proposed method.
Keywords: terminal sliding mode; second-order systems; singularity; mismatched uncertainty; state transformation matrix.
Adaptive sliding mode controller design for the bipartite consensus tracking of multi-agent systems with actuator faults and disturbances
by Ehsan Nazemorroaya, Mahnaz Hashemi
Abstract: This paper studies the bipartite consensus problem for second-order nonlinear multi-agent systems in the presence of actuator faults, unknown control gains and unknown external disturbances. The actuator faults are considered as partial loss of effectiveness fault and bias fault. For design controller, the control gains and disturbances only need to have unknown upper bounds. Also a signed bipartite directed graph is used for describing the communication topology of the multi-agent system. An adaptive sliding mode controller is developed for bipartite consensus tracking of the multi agent system. The proposed adaptive sliding mode controller ensures the uniformly ultimately bounded cooperative tracking of the multi-agent system. Finally, the correctness and effectiveness of the proposed control method is verified via simulation results.
Keywords: Actuator fault; Bipartite consensus; Adaptive sliding mode control; Uniformly ultimately bounded.
A Relative Analysis of Sliding Mode Control with Reaching Law for the Vector Control of Three Phase Induction Machine
by Jisha Kuruvilla P, Anasraj Robert
Abstract: Induction motor constitutes an established test bed in the automatic
control theory frame-structure as it is a higher order, multiple input- output,
nonlinear system operating under uncertainty conditions. The Sliding Mode
Control (SMC) method is a well-developed, promising control procedure
appropriate for non-linear, time-dependent, uncertain systems. Due to its dynamic
nature and robustness towards uncertainties, SMC is a most suggested technique
for implementing in induction motor drives. This paper focuses on implementing
various continuous- time, SMC strategies characterized by reaching lawapproach
in an induction motor drive. The paper also proposes a comparative analysis of
various continuous-time reaching-laws on the performance of the motor towards
parameter and load variations and the chattering issues.
Keywords: Sliding Mode control; Reaching Law;constant reaching law;proportional reaching law;,power rate reaching law;exponential reaching law;enhanced exponential reaching law; Vector control; Motor drives.
A new form of a class of MIMO linear systems for nonsingular terminal sliding mode control
by Ning Zhao, Shouli Gao, Yuankai Song, Dongya Zhao
Abstract: In this study, a novel method is proposed for a class of MIMO linear systems nonsingular terminal sliding mode control to solve singularity problem. A state transformation matrix is designed properly to transfer a class of MIMO linear systems into a new form without changing its controllability and observability, the design method and application conditions are given. Based on it, the traditional nonsingular method of second-order nonlinear systems can be used in the new form of MIMO linear systems by adjusting the dimension of coefficients appropriately. Then an example is given to validate the effectiveness of the proposed form. Stability analysis and numerical simulations show that the proposed method can guarantee system states to converge to equilibrium point with strong robustness in finite time, and the singularity problem can also be avoided appropriately.
Keywords: Terminal sliding mode; Nonsingular; MIMO linear system; State transformation matrix.
Power Control of a Stand-Alone Electric Generation Hybrid System using Integral Sliding Mode Controller
by Fatima Ez-Zahra Lamzouri, El-Mahjoub Boufounas, Aumeur El Amrani
Abstract: This paper proposes a novel strategy for output power control of an electric generation hybrid system (EGHS), composed of a photovoltaic generation system, a storage battery bank and a variable load. According to different atmospheric conditions and load changes, a robust control based on sliding mode control (SMC) is designed to satisfy the total power demand in different power system operation modes. Thus, the proposed controller is modified by introducing the integral action in the switching surface, in order to improve transient response with minimum steady state error. Numerical simulations are presented and discussed to demonstrate the performance of the proposed method, using a nonlinear model of the plant. Finally, the simulation results show that the proposed Integral SMC (ISMC) strategy ensures better response speed and smaller steady-state error compared to standard SMC.
Keywords: hybrid power generation system; maximum power point tracking; power control; integral sliding mode control.
Fixed-Time Sliding Mode Flight Control with Model-Based Switching Functions of Quadrotor Unmanned Aerial Vehicles
by Charles Fallaha, Yassine Kali, Maarouf Saad, Jawhar Ghommam
Abstract: This paper proposes the design of a new sliding mode controller of the attitude fast inner-loop of a drone quadrotor type system. The controller uses the novel model-based switching functions approach, which leads to important simplifications of the pitch, roll and yaw torques control inputs fed to the quadrotor. The model-based switching functions approach forces as well a complete chattering decoupling of these three torque inputs and enhances the robustness of the closed-loop system. The proposed approach is combined with the fixed-time sliding mode approach, and is experimentally implemented and successfully validated on a quadrotor system.
Keywords: Sliding Mode Control; Model-Based Switching Functions; Fixed-Time Sliding Mode; Quadrotor; UAV.
Modified Sliding Mode Control for Universal Active Filter based Solar Microgrid System
by Buddhadeva Sahoo, Sangramkeshari Routray, Pravat Kumar Rout
Abstract: This manuscript presents a larger signal model by combining the universal active filter (UAF) and the solar system with a vector switching operation (VSO) in a novel frame. The detailed modeling of the S-UAF using VSO and modified sliding mode control (MSMC) is proposed for achieving better power quality (PQ) operation. MSMC based novel frame is used to estimate the accurate reference signals for SHAF during dynamic state conditions such as sag/swell, change in irradiance, fault and sensitive load condition. SEAF control is based upon the conventional dq control strategies and it adjusts the load voltage during dynamic conditions. SHAF is used to balance the grid side current and reduces the harmonic distortion by injecting the appropriate current in quadrature with the load current and facilitates fast transient response during sudden load change by providing better tracking capability and reduction in the switching losses. To validate the proposed controller and S-UAF approach with different test conditions, it is tested in Matlab/Simulink environment and the related results are discussed.
Keywords: Vector switching operation (VSO); modified sliding mode controller (MSMC); universal active filter (UAF); dynamic nonlinear transformation (DNT); Power quality (PQ).