International Journal of Automation and Control (25 papers in press)

Regular Issues

• Further improvements on Robust Stability Analysis for Takagi-Sugeno Fuzzy Systems with Time-Varying Delay  
  by Said Idrissi, Youssef E.L. FEZAZI, Nabil E.L. FEZAZI, El Houssaine Tissir 
  Abstract: This paper deals with the problem of robust stability analysis for uncertain Takagi-Sugeno (T-S) fuzzy systems with time varying delays. The approach is based on constructing an appropriate Lyapunov-Krasovskii functional (LKF) combined with state vector augmentation by using the delay-partitioning idea. By dividing uniformly the delay interval into N segment, with N is a positive integer, the LKF is chosen with different weighted matrices corresponding to different segments. The parametric uncertainties are assumed to be norm bounded. On this basis, new sufficient conditions ensuring the robust stability are expressed in terms of linear matrix inequalities (LMIs). Furthermore, the Finsler’s lemma and the Seuret-Wirtinger’s based integral inequality approach have been employed to derive less conservative results. Finally, numerical examples are provided to illustrate the effectiveness and the merit of the obtained results, compared with some previous works in the literature.
  Keywords: Takagi-Sugeno fuzzy systems; delay partitioning approach; stability; Lyapunov-Krasovskii functional; LKF; time varying delays.
  DOI: 10.1504/IJAAC.2023.10053052
   
  
• Decision Optimization of Mobile Robot in Complex Environment Based on Memory Sequence Replay Mechanism  
  by Dongshu Wang, Kai Yang, Xulin Gao, Heshan Wang 
  Abstract: To build a behaviour decision method that can converge to stability in complex environment, this paper constructs an intelligent learning algorithm which can quickly find the shortest path by simulating the memory replay in hippocampus. During the environment identification, a dynamic top-k competition is designed so the agent can consider the influence of multiple obstacles. Meanwhile, a representation layer of the advanced characteristics is added to the algorithm, so the agent can adapt to the complex structural environment. In addition, simulating the memory playback in the hippocampus, through the reverse playback of memory sequence, the reward discount is introduced into the weight updating process of the motor neurons, making the agent understand the relation among the memory fragments and guarantee the global optimal decision. Physical experiment of a mobile robot show that the agent can find the shortest path, demonstrating the agent can make optimal decisions in complex structural environment.
  Keywords: behaviour decision; hippocampus; memory replay; off-task process; developmental network.
  DOI: 10.1504/IJAAC.2023.10053525
   
  
• Design, Modelling, Set-up Fabrication and Control of a Levitation System for a Steel Plate  
  by Janardan Kundu, VINOD KUMAR YADAV 
  Abstract: This paper presents the elementary design, electromagnetic (EM) analysis, system modelling, controller design and fabrication of an electromagnetic levitation setup. The parameters are being evaluated by conventional analytical method and verified by experimental and FE-based results. The finite element (FE) model has been developed using standard software packages. Pohl’s method is extended for the analytical results. The analytical evaluated results are verified with experimental and experimental results too. Controllers have been designed by classical control system methods. Parameter uncertainty and robustness issues have been considered carefully. Analogue controller have been designed, analysed and implemented for the system. Their performances have been simulated and these are practically tested. Finally, the plate has been successfully levitated at an operating gap of 8 mm.
  Keywords: modelling; controller design; system dynamics; restoring force; robustness.
  DOI: 10.1504/IJAAC.2023.10053711
   
  
• Design and implementation of FPGA based integrated missile actuation system and control synthesis  
  by Mohammed Abozied, Sameh Shelan, Yehia Elhalwagy, Hossam Hendy 
  Abstract: The missile's overall accuracy and autonomy are potentially affected by its actuation system and controller design. The current paper presents an integrated missile's actuation system design process in the presence of different mechanical and electrical constraints, a reliable Electric Actuation System (EAS) and its related control system are developed based on missile mechanical and electrical requirements. A real-time motion simulation is performed using solid work software to guarantee compatibility with the actual size, weight, and load constraints. The actuation system model is performed using a system identification technique based on real-time input-output data extraction utilizing a predesigned test and control setup. A real-time floating-point PID controller based on the genetic algorithm optimization approach is designed using MATLAB, simulated using hardware simulation utilizing Modalism software, and then implemented by an embedded FPGA-based board. The novelty of this paper is the design, control, and implementation of a real-time embedded aerodynamic missile actuation.
  Keywords: missile Actuation System; nonlinear modeling,System identification; FPGA; PID controller.
  DOI: 10.1504/IJAAC.2023.10053904
   
  
• Design of a Backstepping Technique Based Robust State Feedback Optimal Control Law for Autonomous Underwater Vehicle in Depth Plane using Semi-definite Programming  
  by Siddhartha Vadapalli, Subhasish Mahapatra 
  Abstract: This paper depicts the control of an autonomous underwater vehicle (AUV) in the vertical plane by employing the robust backstepping approach based state feedback optimal control. The proposed control algorithm adopts a cascade structure for achieving the desired depth. The inner loop is controlled by robust state feedback optimal control law to control pitch orientation and the outer loop is controlled by the backstepping approach to control the depth. The formulation of a robust optimal control algorithm is implemented using semi-definite programming (SDP). Considering the parameter variation, a polytopic system is developed in the depth plane. The proposed control algorithm is realized in MATLAB/Simulink environment using the YALMIP tool. An efficacious tracking of the desired depth is exhibited from the proposed control algorithm by ensuring robust behavior. Further, the robustness analysis is extended by considering different ranges of parameter uncertainty to highlight the efficacies of the proposed control law.
  Keywords: Autonomous Underwater Vehicle; Diving Control; Optimal Control; Robustness; Linear Matrix Inequalities.
  DOI: 10.1504/IJAAC.2023.10054112
   
  
• Observer-Based 2D Tracking Control for a Vascular Microrobot Based on the T-S Fuzzy Model  
  by Meziane LARBI, El Hadi GUECHI, Ahmed MAIDI, Djamel OUNNAS, Karim BELHARET 
  Abstract: This paper deals with a two-dimensional tracking control of a vascular microrobot in the framework of fuzzy modelling. The proposed control strategy consists in using an observer-based T-S fuzzy state controller that achieves the tracking in conjunction with a disturbance rejection compensator that compensates the effects of disturbances. The T-S fuzzy observer is used to recover the whole state from the measured microrobot position. To overcome the overheat problem of the coils and reject the disturbances, the tuning of the T-S fuzzy controller is carried out by imposing a constraint on the manipulated magnetic field gradient magnitude. Both the T-S fuzzy controller and the T-S fuzzy observer are tuned by solving a set of linear matrix inequalities. The desired trajectory to be followed by the microrobot is determined optimally from an MRI image, using the fast marching method, by specifying both the microrobot injection and target positions. Simulation runs are performed to show the performance of the proposed control strategy both without and with the measurement noise.
  Keywords: Magnetic microrobot; T-S fuzzy model; 2D trajectory tracking; T-S fuzzy control; T-S fuzzy observer; disturbance rejection.
  DOI: 10.1504/IJAAC.2023.10054428
   
  
• Unscented Kalman filter based control strategy for wind turbine systems  
  by Abdelkader Garmat, Guesmi Kamel 
  Abstract: This paper proposes a new control strategy based on an improved $LQ$ multimodel optimal controller for a wind turbine system. The proposed structure is formed of a multimodel base with 8 models and unscented Kalman filter estimator. This last allows the wind speed accurate estimation to improve the controller performance, maximize the delivered power, reduce its fluctuation and participate to the network frequency regulation. This paper demonstrate, through a comparative study, that the unscented Kalman filter is an excellent alternative and gives better results than the Kalman filter and the extended Kalman filter in the case of highly nonlinear systems. The simulation results validate the proposed approach and show its efficiency.
  Keywords: Wind turbine; variable-speed; $LQ$ multimodel optimal control; wind speed estimator; unscented Kalman filter; Newton-Raphson.
  DOI: 10.1504/IJAAC.2023.10054472
   
  
• Power Quality Improvement and Seamless Transfer in a Grid-connected Microgrid System using H∞ Controller  
  by Lavanya V, Senthil Kumar.N. 
  Abstract: In this paper, an H∞ controller-based cascaded control strategy has been discussed and analysed for the improvement of power quality and smooth seamless transition between the operating modes in a grid-connected microgrid system. The control strategy involves two control loops namely, an outer grid current control loop and an inner local load voltage control loop. Both the control loops are designed using H∞ repetitive controllers. Particle Swarm Optimization (PSO) technique is used to optimize the weighting parameters of the H∞ controller to design an optimal controller for achieving the desired performance. The main objective of the control strategy is to minimize the harmonic content present in the load voltage and the grid current ensuring smooth transition between the operating modes of the microgrid without any noticeable transients. The H∞ repetitive controller with optimized weighting parameters outperforms the other traditional controllers in achieving better dynamic response with reduced THD.
  Keywords: Microgrid; Seamless Transfer; H-infinity (H∞) controller; Grid-connected; Islanded; three-phase inverter; Power Quality.
  DOI: 10.1504/IJAAC.2024.10054473
   
  
• Observer Controller-Based for Modified Flower Pollination Algorithm for Wind Power Generation  
  by Akwasi Amoh Mensah, Xie Wei, Duku Otuo-Acheampong 
  Abstract: A proposed two-stage Luenberger observer controller-based structure is used by the pollinators in the flower pollination algorithm (FPA) to search for global and local pollination. The FPA moves in only one direction in search of the best solution and has a slow speed which is unable to properly find the best solution at longer distances. The modified FPA with the Luenberger method observes the best and optimal proliferation of specific flower species based on the combination of global and local pollination which is used in the search for the best solution by the pollinators in both forward and backward movement with fast speed in search for the local and global best solution at both shorter and longer distances which measures the input and output power generated by the wind turbine. The output MATLAB/Simulink simulation results show the effectiveness and high performance of the proposed method.
  Keywords: wind power generation; Luenberger observer controller; modified flower pollination algorithm; global and local pollination; forward and backward pollination.
  DOI: 10.1504/IJAAC.2024.10054838
   
  
• New Optimal Fast Terminal Sliding Mode Control Combined with Neural Networks for Modelling and Controlling a Drone Quadrotor  
  by Najlae Jennan, El Mehdi Mellouli 
  Abstract: This study concerns the modelling and control of a drone quadrotor which is a multi-input multi-output nonlinear system. The fast terminal sliding mode controller combined with particle swarm optimisation and neural network is presented to control the system, in order to solve high nonlinearity and cross-coupling problems. Generalising the control laws requires the complete state and all the system dynamics. However, not all states are accessible to the control laws and some dynamics cannot be modelled. Therefore, a triangular observer is proposed to estimate the system hidden states based on neural network to approximate the unmodelled dynamic part. We join a supplementary term in the control laws to reduce modelling errors and disturbances. Then, we use particle swarm optimisation to optimise important coefficients to achieve better results. The control laws come from the stability study in sense of Lyapunov. The results simulations confirm the effectiveness of the proposed control strategy.
  Keywords: MiMo nonlinear system; drone quadrotor; fast terminal sliding mode control; triangular observer; neural network; particle swarm optimisation.
  DOI: 10.1504/IJAAC.2023.10054839
   
  
• Identification between broken rotor bars and low-frequency load torque fluctuations in a three-phase induction motor  
  by Ranjan Pal, Amiya Mohanty 
  Abstract: Motor current signature analysis is an efficient methodology for fault diagnosis of induction motors. Appearance of broken rotor bars creates pole pass frequency (fPPF). Applied load torque creates low-frequency load torque fluctuations at frequency (fL) which tends to exist in vicinity of fPPF. Hitherto, techniques have been proposed wherein synchronised monitoring of three-phase currents and three-phase voltages are measured by three current and three voltage sensors. This leads to a requirement for a data acquisition (DAQ) unit with atleast six channels that makes the overall system expensive and cumbersome in the field. However, in the present article, a new fault diagnostic approach has been proposed, which considers current data being monitored only from one single phase and thus requires only one single channel of DAQ which makes overall system economical and portable for easy field deployment. The proposed analytical study has been verified with experimental results and finite element method.
  Keywords: broken rotor bars; BRBs; load torque fluctuations; motor current signature analysis; MCSA; three-phase induction motors.
  DOI: 10.1504/IJAAC.2024.10054887
   
  
• Few-Shot Reasoning Based Safe Reinforcement Learning Framework for Autonomous Robot Navigation  
  by Weiqiang Wang, Xu Zhou, Benlian Xu, Siwen Chen, Mingli Lu, Jun Li, Yuejiang Gu 
  Abstract: Unsafe explorations in the training phase hinder the practical deployment of reinforcement learning (RL) on autonomous robots. Some safe RL methods use safety constraints from prior or external knowledge to reduce or avoid unsafe explorations, but such knowledge is usually unavailable in practice, especially in unknown environments. In this work, we propose a few-shot reasoning-based safe reinforcement learning framework that includes a new few-shot learning method with dynamic support set to reason the safety of unexplored actions and hence guide safer action selection. Additionally, it endows robots with the capability of reverting to previous safe states and reflecting on failures to update the dynamic support set and further improve the accuracy of safety reasoning. Experiment results show that our new few-shot learning method is more accurate, and our proposed framework can significantly reduce the number of failures in the learning phase, especially for long-term autonomy.
  Keywords: safe reinforcement learning; few-shot learning; dynamic support set; autonomous robots.
  DOI: 10.1504/IJAAC.2024.10055043
   
  
• Machine Learning based Fault Estimation of NonLinear Descriptor Systems  
  by Tigmanshu Patel, Meka SrinivasRao, Dhrumil Gandhi, Jalesh L. Purohit, Vipul Shah 
  Abstract: This article focuses on the problem of fault estimation of nonlinear descriptor systems (NLDS) using intelligent approaches. Firstly, an extended Kalman filter for descriptor systems is employed for state estimation. Further, the residuals are generated and mapped to detect and confirm the fault. Finally, machine learning approach and neural network models are used to estimate faults. For machine learning approach, Gaussian process regression is employed to estimate fault magnitude. Additionally, a back propagation neural network is also applied for fault estimation. The efficacy of the proposed methods are demonstrated with the help of benchmark chemical mixing tank descriptor system (Yeu et al., 2008) and two phase reactor and condenser with recycle (Kumar and Daoutidis, 1996). It is observed that the Gaussian process approach outperforms neural network-based approach for fault estimation.
  Keywords: descriptor systems; differential algebraic equations; DAEs; fault detection; fault diagnosis; fault estimation.
  DOI: 10.1504/IJAAC.2024.10055128
   
  
• H∞ Stabilization of Discrete Time-Delayed Systems with Anti-windup Approach  
  by Komal Agrawal, Nehal Srivastava, Richa Negi, VIPIN CHANDRA PAL 
  Abstract: This paper is devoted to analysing the stability of a discrete time-delayed system subjected to saturation. To ensure the asymptotic stability of the closed-loop system, an anti-windup compensator has been designed where the anti-windup gains are calculated via linear matrix inequality (LMI) technique. The accomplishment of the system has been investigated using H∞ technique to tackle external interference. By employing Wirtinger inequality with reciprocal convex inequality, delay-dependent solution of the system ensures the asymptotic stability of the system. An optimisation methodology is given to maximise the basin of attraction. Numerical illustrations prove the efficacy of the proposed criterion.
  Keywords: discrete-time system; time delay; actuator saturation; asymptotic stability; anti-windup; H∞.
  DOI: 10.1504/IJAAC.2024.10055336
   
  
• Frequency Regulation of Time-delayed Power System utilizing Nonlinear Resilient Controller  
  by Vivek Patel, Dipayan Guha, Shubhi Purwar 
  Abstract: In this work, an effort has been made to investigate the frequency regulation problem of a time-delayed interconnected power system (IPS) having redox flow battery (RFB). Frequency control is necessary for satisfactory output of power systems. An improved super twisting-based integral sliding mode controller (IST-ISMC) has been designed and incorporated in the IPS to actively compensate power-frequency oscillations in the wake of uncertain/unknown system disturbances. RFB has been introduced in the undertaken IPS because of high gain and smaller time constant, resulting in faster response. The stability of the closed-loop system has been affirmed by applying the Lyapunov-Krasovskii functional approach. Linear matrix inequality feasibility problem has been solved for designing the proposed controller. Simulation results show that IST-ISMC outperforms ISMC in terms of faster system dynamics, reduced chattering, and robustness against system uncertainty. The performance of the proposed controller is compared the controller presented in Sun et al. (2018).
  Keywords: frequency regulation; super twisting sliding mode controller; adaptive law; redox flow battery; RFB; linear matrix inequality; LMI.
  DOI: 10.1504/IJAAC.2024.10055534
   
  
• Sliding mode control of Two-link Flexible Manipulator for reduced vibration in the presence of unmatched uncertainty and time-varying external disturbance  
  by Sanjay Thakur, Ranjit Kumar Barai 
  Abstract: Accurate positioning of the flexible links is a major challenge for a flexible link manipulator because of the presence of vibration, model uncertainty, and external disturbances. In this work a popular robust controller, i.e., sliding mode controller (SMC) has been developed for joint trajectory tracking and vibration reduction of the two-link flexible manipulator. Due to the payload’s variability, which makes the issue even more challenging, the mass of the payload has been treated as uncertainty. Proof of the matching condition of the uncertain parameter has also been provided. The system’s dynamics have been modelled using the Assumed mode method. Closed-loop stability has been verified using the Lyapunov method. Lyapunov-based controller (LBC) has also been developed for comparison purposes. Payload has been varied to show the effectiveness of the developed controller. The simulation results have exhibited better performance of the SMC over the LBC.
  Keywords: assumed mode method; Lyapunov-based controller; LBC; matching condition; sliding mode controller; SMC; two-link flexible manipulator; TLFM; uncertainty.
  DOI: 10.1504/IJAAC.2024.10055581
   
  
• Trajectory tracking control for uncertain agricultural quadrotor based on combining ASMC and NFTSMC  
  by Falu Weng, Hui Wei, Yongji Huang, Leilei Hou 
  Abstract: In this paper, the trajectory tracking problem of an agricultural quadrotor UAV subjected to parametric uncertainty, system uncertainties and wind disturbances is studied. Firstly, because the agricultural quadrotor UAV system is a nonlinear system that makes it difficult to control, the system is divided into two subsystems based on its dynamic model: a position-signal-followed subsystem and an attitude-adjusted subsystem. Secondly, a control scheme that combines two parts: an adaptive sliding mode control (ASMC) and a non-singular fast terminal sliding mode control (NFTSMC), is used to control the subsystems. The ASMC is applied to control the position-signal-followed subsystem, in which three self-turning laws are used to estimate the mass change, system uncertainties and wind disturbances. The NFTSMC is used to control the attitude-adjusted subsystem, in which lumped disturbances are estimated by linear extended state observers (LESO). Finally, simulations are given to demonstrate the effectiveness of the developed control scheme.
  Keywords: agricultural quadrotor UAV; adaptive sliding mode control; ASMC; self-turning laws; non-singular fast terminal sliding mode control; NFSTMC; linear extended state observer; LESO.
  DOI: 10.1504/IJAAC.2023.10055612
   
  
• A Quadrotor Controlled in Real Time Using Hand Gestures and ROS2 Multi-Node Communication within GAZEBO 3D Environment  
  by Hamza Djizi, Abdelaziz Lakehal, Zoubir Zahzouh 
  Abstract: This paper introduces a novel way of designing and controlling a quadrotor prototype using hand gestures, utilising the Robotic Operating System 2 (ROS2) and GAZEBO11 3D environment. A C++-based plug-in was created for GAZEBO, while the cross-platform pipeline framework Media-Pipe was used to manage the quadrotor’s movements through hand gestures. The PID regulator was utilised to enhance the movements’ accuracy and responsiveness, leading to a more efficient and precise response to user commands for a better user experience. The obtained results demonstrated that the PID regulator improved the response of the quadrotor to hand gestures with greater accuracy.
  Keywords: Robotic Operating System 2; ROS2; quadrotor; GAZEBO; control; communication; hand gestures.
  DOI: 10.1504/IJAAC.2024.10056000
   
  
• Improving Ride Comfort approach by Fuzzy and Genetic Base PID Controller in Active Seat Suspension  
  by Hamid Gheibollahi, Masoud Masih-Tehrani, Amin Najafi 
  Abstract: This article investigates the influence of two active seat suspension controllers on the ride comfort of an articulated truck semi-trailer. This paper presents a linear truck model with 13 degrees of freedom (DOF). This model is coupled with a four-DOF biodynamic model. GA-PID and Fuzzy-PID controllers are defined and applied to the seat suspension to provide more ride comfort under different road conditions. The genetic algorithm (GA) extracts the first PID controller parameters, and the second PID controller parameters are achieved by fuzzy logic control (FLC). The optimization function was considered a linear combination of some ride comfort factors. Simulation results reveal that GA-PID and Fuzzy-PID controllers have had similar results and could improve ride comfort and health by declining Motion Sickness Dose Value (37.42%), Vibration Dose Value (37.53%), Excess Kurtosis (14.41%), Crest Factor (4.95%), whole body RMS acceleration(37.40%) and its peak(39.51%) compared to the passive suspension systems.
  Keywords: Motion Sickness Dose Value (MSDV); Vibration Dose Value (VDV); Excess Kurtosis (EK); Crest Factor (CF); Whole-body vibration (WBV); Ride comfort.
  DOI: 10.1504/IJAAC.2024.10056050
   
  
• Chaos Control of RESs Integrated Power System Model using Adaptive Higher Order PID SMC and Comparison Among Different Adaptive SMC Techniques  
  by Prakash Chandra Gupta, Piyush Pratap Singh 
  Abstract: In this paper, the analysis and control of renewable energy sources (RESs) integrated 4D power system model are reported. Wind energy systems and photovoltaic panels are integrated as RESs into the power system model. A power system is a very complex, dynamic system that exhibits nonlinear behaviours. Consequently, the power system may experience serious scenarios like voltage instability or voltage collapse. The bifurcation and chaos behaviours of the RESs integrated power system model are studied and verified using the Lyapunov exponent, Lyapunov spectrum, and bifurcation diagram. Since chaotic oscillations are unlike and highly dangerous for stable operation of a power system, an adaptive higher order PID sliding mode control (SMC) technique is designed to control the chaotic oscillation. The required asymptotic stability condition is derived using Lyapunov stability theory. A comparative study is done based on different performance indices to analyse the performance of the designed control with four existing adaptive SMC techniques.
  Keywords: power system; chaos; bifurcation; renewable energy sources; RESs; adaptive control; sliding mode control; SMC.
  DOI: 10.1504/IJAAC.2024.10056205
   
  
• An experimental study of spatial temperature profile control of a distributed parameter heating system using model predictive control  
  by Jaivik Mankad, Nitin Padhiyar 
  Abstract: The problem of profile control is important owing to its industrial significance. This problem is viewed as a multi-objective problem and solved using different approaches such as augmentation of objectives or prioritised solving of each objective separately. The focus in our work is to experimentally study the lexicographic optimisation approach for prioritised control of different objectives. An experimental rig has been designed for the purpose of priority driven spatial property control of a distributed parameter system (DPS). The setup consists of a thin metal plate with four temperature sensors and four electric heaters located axially. Through this experimental rig, we demonstrate the concept of controlling the spatial profile in a DPS and address the relevant issues. Specifically, when the desired spatial profile is unachievable, we may be interested in controlling different parts of the profile depending upon their importance. We show an MPC formulation to achieve such a spatial profile control with user defined priority using lexicographic optimisation approach in this work.
  Keywords: model predictive control; MPC; distributed parameter system; prioritised MPC; lexicographic optimisation; spatial temperature profile.
  DOI: 10.1504/IJAAC.2023.10048889
   
  
• Novel adaptive control for avoiding fuzzy rule explosion in nonlinear systems  
  by Ashwani Kharola 
  Abstract: The study highlights three different control techniques namely proportional integral derivative (PID), adaptive neuro fuzzy inference system (ANFIS) and neural networks (NNs) for the control of highly nonlinear triple inverted pendulum system mounted on a carriage. The objective is to control the complete system within 3.0 sec using above mentioned controllers. The controllers were compared in terms of performance attributes like settling time, steady state error and overshoot responses. The results indicate better performance of ANFIS controller compared to PID and NN controllers. The study also highlights the effect of shape, number and type of membership function on training of ANFIS controller. The study further proposes an ANFIS controller which has been designed using only three membership functions and can successfully solve the problem of rule explosion associated with fuzzy controllers.
  Keywords: triple inverted pendulum; fuzzy rule explosion; artificial neural networks; proportional integral derivative; PID; ANFIS; MATLAB; Simulink; simulation.
  DOI: 10.1504/IJAAC.2023.10049482
   
  
• Design of a new hybrid linearising-backstepping controller using quantum state equations and quantum spins  
  by Nadjet Zioui, Aicha Mahmoudi, Mohamed Tadjine 
  Abstract: Automatic control theory has brought many new innovative process control strategies and solutions to stability and trajectory tracking problems in engineering, for linear as well as for nonlinear systems. With the emergence of quantum computing concepts and technologies, quantum versions of conventional modelling techniques, control tools and strategies are needed to take full advantage of the future quantum computers. This work presents firstly the new quantum formulation of a special class of state-space equations. Secondly, quantum state feedback making it possible to control a desired qubit state is introduced based on quantum spins. This new method uses the Hermitian quantum rotations operators. The state variables can also be computed using the inherent property of reversibility of the quantum operators. Thirdly, simulation results considering both constant and time-varying references demonstrated the effectiveness of the method compared to the conventional competitor with very satisfactory results in terms of speed and resources use efficiency.
  Keywords: qubit states; quantum spins; state space equations; quantum linearising control; QLC; backstepping methodology; quantum state feedback control.
  DOI: 10.1504/IJAAC.2023.10051373
   
  
• Design of an optimal tracking controller with unmeasured states for electro-hydraulic actuation system using 4/3 proportional DC valve  
  by Ashok Kumar Kumawat, Raja Rout, Renu Kumawat, Manish Rawat 
  Abstract: In this paper, an optimal tracking control is designed considering the unknown states for an electro-hydraulic actuator system driven by a proportional directional control valve. Given the practicality of the algorithm, the control voltage applied to the proportional directional control valve satisfies the actuation limits. Furthermore, a discrete Kalman observer is used to overcome the limitation of unmeasured states. The efficacy of the proposed algorithm is verified in simulation as well as in experimental environments. Both simulation and experimental results confirm that the tracking performance of the electro-hydraulic actuator system is improved, and tracking error converges to an arbitrarily small neighbourhood.
  Keywords: optimal tracking control; electro-hydraulic actuation system; Kalman state estimator; proportional directional control valve.
  DOI: 10.1504/IJAAC.2023.10052883
   
  
• Adaptive controller design based on grasshopper optimisation technique for BG regulation in TIDM patient  
  by Girija Sankar Panigrahi, Akshaya Kumar Patra, Anuja Nanda, Sanjeeb Kumar Kar 
  Abstract: This article demonstrates the design of the grasshopper optimisation-variable parameter-tilt integral-derivative-filter (GO-VPTIDF) controller to inject an ideal dose of insulin via artificial pancreases (AP) for control of blood glucose (BG) level in the type-I diabetes mellitus (TIDM) patients. The grasshopper optimisation technique (GOA) is utilised to adjust the controller gains for better BG control in the proposed patient model. This classical controller with GOA is seen to enhance the patient performance and robustness. The nonlinearities present in patient model cause BG control issues. The use of AP based GOA efficiently to overcome the nonlinearities in the patient model and to maintain BG level in the range of normo-glycemia (70-120 mg/dl). This proposed patient model with GO-VPTIDF is analysed for upgraded accuracy, stability, robustness, noise suppression, and better ability to handle uncertainties. The comparative results investigation with different control techniques discloses the cause of advanced control execution of the proposed approach.
  Keywords: insulin; glucose; blood; type-I diabetes; GO-VPTIDF controller.
  DOI: 10.1504/IJAAC.2023.10052842