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

Special Issue on: "Intelligent-based Modelling, Control, Fault Simulation, Detection, Diagnosis and Tolerant Schemes in Electrical and Process Automation Systems"
Guest Editors: Dr. S. Paramasivam, ESAB Engineering Services Limited, India Dr. N. Selvaganesan, Indian Institute of Space Science and Technology (IIST), IndiaC

• Implementation of ADALINE on a DSP for Real-Time Measurement of Current Harmonics
  by VALLUVAN K.R., NATARAJAN A.M. 
  Abstract: The objective of this paper is to implement a ADAptive LINear Element (ADALINE) for real-time measurement of harmonics in load current waveform using a Digital Signal Processor (DSP). Harmonics cause many ill effects and reduce Power Quality. Harmonics are being measured by Fast Fourier Transform (FFT) algorithm executed on a microprocessor or DSP system. The FFT algorithm implemented as per IEC 61000-4-7 requires 1000 samples to be acquired from 10 cycles for a 50 Hz system. This paper presents the results of implementation of ADALINE algorithm on a DSP for measurement of harmonics in real time. The proposed method requires acquisition of only 100 samples from 1 cycle of the load current. Thus the acquisition time in the proposed implementation reduces to 20ms from 200ms. The results obtained using the proposed method are found to be close to that of a standard FFT based Power Quality Analyser.
  Keywords: Harmonics; IEEE:519; IEC-61000-4-7; ADALINE; DSP implementation
   
• Self Organized Maps for online detection of faults in nonlinear processes
  by Maddala Jeevan, Srinivasan Babji, Arun Tangirala 
  Abstract: Fault detection in nonlinear processes is a challenging task and has been an important area of academic and industrial interest for the past two decades . In linear systems, detection and diagnosis of faults has been addressed mainly using the well known principal component analysis and its variants. Further, dynamic PCA (DPCA) is also applied to nonlinear systems with mild nonlinearities, i.e., which can be rea-sonably well approximated with first-order Taylor series expansion. However, there are a wide class of nonlinear systems, especially chemical processes, where DPCA fails to detect faults present in the process. The present work aims at demonstrating the application of self-organizing maps (SOM) for fault detection in such nonlinear pro-cesses. SOM belongs to the class of unsupervised and competitive learning algorithms which handles the nonlinear relationship existing among the variables leading to a classification of the data. It interprets the relationships among variables without any a priori knowledge of the process. Application of SOM for fault detection involves generation of a reference template for the process under normal operating conditions based on the historical data. Online fault detection is performed by providing the new process data to SOM using a time window and a new template is generated. This new template is compared with the reference template using a metric based on the node weights obtained from SOM to detect the possible faults in the process. Simulation studies are performed on the following two nonlinear systems namely (i) continuously stirred tank reactor (CSTR) and (ii) bioreactor process. Results obtained from these processes demonstrate the practicality and utility of the proposed method to detect faults in nonlinear processes
  Keywords: fault detection; nonlinear systems; self organizing maps; principal component analysis
   
• Robust Stabilization of Coprime Factor Plant Description Subject to Plant Perturbations
  by Leesha Paul, Jeevamma Jacob, Abraham T Mathew 
  Abstract: This paper presents a new procedure for the synthesis of linear multivariable system subjected to plant perturbation and external disturbance. Coprime factorization approach is used to model the plant perturbation. External disturbance is treated as exogenous system whose unstable modes are assumed to be disjoint from the system zeros. A stable desired closed loop transfer matrix is obtained which can be expressed as the product of an open loop transfer matrix and any proper rational transfer matrix. Internal model principle is employed to realize the closed loop transfer matrix which simultaneously ensures: 1) robustness with respect to plant perturbation, 2) decoupling, 3) complete and arbitrary closed loop pole placement, 4) internal stability, and 5) disturbance rejection. The compensation scheme is presented in the frequency domain. This is compared with H-infinity control technique and the simulation result shows better robust performance for the frequency domain method.
  Keywords: Decoupling; plant perturbations; feedforward compensation; multivariable control.
   
• Sensor location with respect to fault tolerance properties
  by abdel AITOUCHE, Belkacem OULD- BOUAMAMA 
  Abstract: This paper deals with the sensor location of nonlinear systems with respect to Fault Tolerance properties. Nonlinear observability and individual observability indices are introduced and used to build minimal and redundant sensor sets. These sets are organized into an oriented graph which contains all the possible reconfiguration paths for which the estimated variables remain observable. The evaluation of fault tolerance is based on Fault Tolerance properties: a structural and a probabilistic criteria, for which observability properties remain satisfied. The developed methodology is applied to a steam generator installation which represents complex nonlinear system widely used in process engineering.
  Keywords: Sensor location; fault tolerance; nonlinear observability; structural analysis, redundancy; reliability, sensor network design, steam generator.
   
• Fuzzy Improved Adaptive Neuro-NMPC for On-Line Path Tracking and Obstacle Avoidance of Redundant Robotic Manipulators
  by ashkan mohammadzadeh jasour, Mohammad Farrokhi 
  Abstract: This paper presents a Nonlinear Model Predictive Control (NMPC) for redundant robotic manipulators. Using NMPC, the end-effector of robotic manipulator tracks a predefined geometry path in the Cartesian space in such a way that no collision with obstacles in the workspace and no singular configurations for the robot occurs. Nonlinear dynamic of the robot including actuators dynamic is also considered. Moreover, the on-line tuning of the weights in NMPC is performed using the fuzzy logic. The proposed method automatically adjusts the weights in the cost function in order to obtain good performance. Furthermore, using neural networks for model prediction, no knowledge about system parameters is necessary and system robustness against changes in parameters is achieved. Numerical simulations of a 4DOF redundant spatial manipulator actuated by DC servomotors shows effectiveness of the proposed method.
  Keywords: Robotic Manipulator, Path Tracking, Obstacle Avoidance, NMPC, Fuzzy Logic, Adaptive, Neural Networks
   
• A Simple Self-Tuning Scheme Using Fuzzy Logic for a Non-Linear Pressure Regulating System
  by kanagaraj nallaiya, Paramasivam S 
  Abstract: A self-tuning control scheme using fuzzy logic has been studied for a pilot pressure regulating system. In this hierarchical control technique, a rule-base supervisory fuzzy system is designed to tune the input scaling factor of a direct fuzzy system according to the process condition. The proposed controller design concentrate more on improving the robustness and stability of the controller during process disturbances and changes in operating level. The proposed control scheme is implemented in an ARM7 microcontroller based embedded target board to study its applicability for real time pressure control application. The performance of the developed control scheme is compared with classical fuzzy controller under different operating level and process disturbance. Results show that the proposed self-tuning fuzzy controller outperforms the conventional method for pressure regulation.
  Keywords: Pressure control, Self-tuning controller, Fuzzy controller, ARM7 microcontroller, Microcontroller based system
   
• Design of an Optimal PI Controller for a Nonlinear Process using Genetic Algorithm
  by DAKSHINAMURTHI SIVAKUMAR 
  Abstract: Many industrial processes have to satisfy different criteria to achieve better quality product and performance. These multiple performance criteria need to be optimized simultaneously. However, in most cases, a suitable optimal solution meeting the entire criteria can hardly be found since these criteria are conflicting. Compared to conventional optimization techniques, Genetic Algorithms (GA’s) are well suited to solve optimization problems that involve multiple performance criteria. This paper presents the application of a GA to optimize the PI controller parameters for a nonlinear process. Least Square Estimation (LSE) method is used to estimate the parameters of the process. Computationally constructive characterizations of all PI controllers that stabilize the given plant in the specified ranges are carried out using the estimated plant parameters. Genetic Algorithm searches the optimal controller parameters within this stabilizing set. Experimental results are provided, showing the efficiency of the multiple performance criteria tuned controller when compared to single performance criterion controller and conventional controller. The results show the improved transient and steady state behavior of the closed loop systems with proposed controller.
  Keywords: Least Square Estimation; Stabilizing Set; Genetic Algorithm; Optimization; Nonlinear process.
   
• Online Implementation of Wavelet-based Identification and Dynamic Matrix Control in a Heat Exchanger Unit
  by Hare Krishna Mohanta, Ram Krishna Gupta 
  Abstract: This paper presents an online implementation of Wavelet-based Least Square Identification (WLSI) and Wavelet-based Dynamic Matrix Control (WDMC) in a plate-type Heat Exchanger Unit. Wavelet domain “blocking” and “condensing” (B & C) techniques are used to reduce the computation time for optimization of Dynamic Matrix Control (DMC) performance index. Algorithms for WLSI and WDMC are developed and implemented in the online identification and control of temperature in a heat exchanger unit. The results are compared with conventional PID and DMC controllers. It is observed that the WDMC is better and robust than the other controllers.
  Keywords: DMC; Wavelet-based DMC (WDMC); Wavelet-based Least Square Identification (WLSI)
   
• Failure detection schemes in Control actuation systems for launch vehicles
  by Jaya Balakrishnan, Swapna Surendran, Narayanan Namboothiripad, Thomas Kurian 
  Abstract: Control actuation systems are used for the attitude control of launch vehicles. They are basically closed loop position servo systems by means of which the engine or nozzle of the rocket is vectored based on the commands coming from onboard computer. The two important elements of a typical control actuation system are the control electronics and the actuators. Control Electronics plays a vital role in the success of a launch vehicle mission. In order to avoid single point failures and hence to improve the reliability of the system, various redundancy schemes are used in control actuation systems. In this paper a case study of a typical dual redundant electromechanical control actuation system is highlighted.
  Keywords: Control system, Actuator, Failure detection, redundancy, motor, power amplifier,position sensor
   
• Robust Fault Diagnosis of Networked Control Systems via Kalman Filtering
  by Karim Chabir, Dominique Sauter, Naceur Abdelkrim, Mohamed Bengayed 
  Abstract: The fault detection problem of a class of linear Networked Control Systems (NCS) with communication delays will be studied in this paper. The aim of the study is to generate residual signals which, in the fault free case, are supposed to be identically zero. In practice, this condition is not satisfactory due to various factors such as measurements noise, model uncertainties, and more specifically the NCS communication induced delays. The effect of unknown networked induced delays on conventional observed residue generator is also studied in this paper. It is shown that the detection performances may be deteriorated because of the sensitivity of the residuals to the delays. The proposed approach is based on robust residual generation based on Kalman Filtering.
  Keywords: Fault diagnosis, Kalman filtering, networked control systems, robustness, delays.
   

• EXPERIMENTAL INVESTIGATION TO PREDICT THE CONDITION OF CUTTING TOOL BY SURFACE TEXTURE ANALYSIS OF IMAGES OF MACHINED SURFACES BASED ON AMPLITUDE PARAMETERS
  by B S PRASAD, M M M SARCAR 
  Abstract: In this paper an experimental investigation is presented for accomplishing surface texture analysis using machine vision based system for predicting the condition of cutting tool. Texture of machined surface provides reliable information regarding the extent of the tool wear because tool wear affects the surface roughness dramatically. Analysis of machined surface images of different materials by turning process at different wear conditions cutting tool are grabbed using CCD camera are presented. In this paper, we propose an amplitude parameters based approach for analysis of machined surfaces. Machined surfaces with different wear conditions of the cutting tool i.e., sharp, semi-dull and dull are investigated by using surface metrology software Truemap and also with conventional method using stylus instrument for comparative purpose. Since a machined surface is the negative replica of the shape of the cutting tool, and reflects the volumetric changes in cutting edge shape, it is more suitable to analyze the machined surface than to look at a certain portion of the cutting tool. However, considerably less work has been performed on the development of surface texture of machined work piece that provide information on the condition of the cutting tool, employed in machining the surface. In this paper, a non contact method using machine vision for inspecting surface roughness of machined surfaces produced by varying conditions of turning process is studied to monitor and to predict the cutting tool condition has been presented. Through our experiments, we found a strong correlation between tool wear and surface roughness (surface texture) of the machined surfaces. Results proved that the approach is effective in predicting the condition of the cutting tool through amplitude parameters.
  Keywords: Machine Vision, tool condition monitoring, surface metrology, CCD camera, amplitude parameters.
   
• Identification of Fuzzy Model of Refrigerant Condenser via ANFIS in Vapour Compression Air conditioning System
  by Jagdev Singh, Nirmal Singh, J.K. Sharma 
  Abstract: In this paper fuzzy model has been identified to study the effect of refrigerant flow and condenser temperature on condenser superheat. Fuzzy model of two input variables mass flow rate, and condensing temperature, one output variable condenser superheat was developed to describe its significance in vapour compression air conditioning system. Adaptive Neuro-Fuzzy Inference System (ANFIS) was used to study the trend of condenser superheat depending upon condensing temperature and refrigerant mass flow rate. To develop an effective MISO model, fuzzy rule base was designed for vapour compression air conditioning system. The effect of input parameters on condenser superheat through the developed fuzzy model was studied. Simulation of fuzzy and mathematical model was carried which showed that the MISO control can significantly improve the superheat behavior at condenser pressure and hence energy efficiency of vapor compression refrigeration cycle.
  Keywords: Refrigerant condenser;Vapour compression cycle; Fuzzy modeling;ANFIS; R-134a.
   
• A Sliding Mode Controller for SSSC to Delay Hopf Bifurcation in a Differential Algebraic Power System Model
  by D. Padma Subramanian, R. P. Kumudini Devi 
  Abstract: A novel Sliding Mode Controller (SMC) is proposed for Static Synchronous Series Capacitors (SSSC) to delay Hopf bifurcation (HBF) in a differential-algebraic power system model. The proposed controller consists of an equivalent control term and a switching term. The major drawback of SMC approach, viz, the undesired chattering is eliminated by introducing a continuously changing switching term instead of the conventional switching function. The effectiveness of the controller is demonstrated in a bifurcation perspective. Steady state bifurcation diagrams are constructed by the application of an algorithm based on continuation method for the entire Jacobian matrix of structure preserving power system model. From the bifurcation diagram, existence of HBF is identified with the help of eigen value analysis. Occurrence of HBF is confirmed through computation of HBF index. The effectiveness of the proposed sliding mode controller over the conventional PI controller for SSSC in delaying HBF and maintaining load voltage constant for higher reactive power loading is illustrated for a 3 machine, 9 bus system.
  Keywords: SSSC, SMC, algorithm, steady state bifurcation diagram, HBF
   
• Robust H^∞ decentralized intelligent control with new learning algorithm for robot manipulators
  by Yi Zuo, Yaonan Wang, Lihong Huang 
  Abstract: A novel robust H^∞ decentralized intelligent control (RHDIC) strategy is proposed for the trajectory following problem of robot manipulators. The proposed system is comprised of a computed torque controller and neural robust controller with new learning algorithm. Based on Lyapunov stability theorem, it is shown that the proposed controller can guarantee stability of closed-loop systems and satisfactory tracking performances. The proposed approach indicates that computed torque control method is also valid for controlling uncertain robotic manipulators as long as compensative controller is appropriately designed.
  Keywords: intelligent decentralized control; computed torque; Lyapunov stability theorem; trajectory following problem
   
• A Generalized Control Metaheuristic Framework for Industrial Processes
  by Fotis Koumboulis, Maria Tzamtzi 
  Abstract: A metaheuristic control design scheme is proposed to solve control design problems formulated as optimization under constraints. Actuator, state and/or output variable constraints are considered. The algorithm utilizes process simulation blocks without specific characteristics. Candidate controllers are randomly selected within a search area, whose range and location change adaptively. The proposed generalized control design framework may be easily applied for a variety of industrial application, since it does not use any assumptions regarding the structure of the controlled plant or the controller or the performance indices. The application of the control framework requires the following main steps from the designer: a) Determination of a cost criterion, whose minimization corresponds to the required closed-loop performance. b) Formulation of any performance or configuration constraints on the plant’s variables. c) Determination of any other desired closed-loop properties, as for example stability, that may be checked using algorithmic criteria. d) Development of closed-loop simulation blocks, based either on the nonlinear plant’s model or on linearized approximations. e) Determination of the initial search area within the controller parameter space, following one of the four approaches, also proposed within the present work. The control framework is based on a metaheuristic search algorithm that solves numerically the optimization under constraints problem. The algorithm may be easily implemented in an high level programming environment and provides a computationally efficient generic control design tool, whose performance has been tested using simulation results on several industrial applications, including a robotically controlled pouring process, a heating system, an activated sludge process and an automated manufacturing system.
  Keywords: Industrial control, Intelligent Control, Optimization methods, Nonlinear systems, Search methods
   
• Stability analysis and control synthesis of uncertain neutral delay systems with actuator failures
  by Limin Wang, Cheng Shao 
  Abstract: The problems of delay-dependent robustly exponential stability and stabilization of a class of special neutral systems with interval time-varying delays, and subject to actuator failures, are investigated in this paper. For the special switched system resulting from actuator failures, a class of switching laws incorporating the average dwell time method is proposed. Based on the switching strategy of average dwell time method, delay-dependent sufficient conditions for exponential stability and stabilization of the special switched systems are established in terms of linear matrix inequalities by choosing appropriate piecewise Lyapunov-Krasovskii functional. Also, the synthesis of stabilizing hybrid state-feedback controllers is done such that the closed-loop system is robustly exponentially stable. The effectiveness of the proposed robust control scheme is demonstrated by simulation example.
  Keywords: Robustly exponential stability; actuator failures; average dwell time; delay-dependent; linear matrix inequalities; switched neutral systems.
   
• Hybrid Bacterial Foraging and Particle Swarm Optimization for Fuzzy Precompensated Control of Flexible Manipulator
  by Srinivasan Alavandar, Tushar Jain, Nigam M J 
  Abstract: Control problem of robots with flexible members is more complex compared to rigid robots due to vibrations during the motion. This paper presents hybrid approach combining the social foraging behavior of Escherichia coli bacteria and particle swarm optimization for optimizing hybrid Fuzzy Precompensated Proportional – Derivative (PD) controller in trajectory control of two link rigid-flexible manipulator. Numerical simulation using the dynamic model of the two link rigid-flexible manipulator shows the effectiveness of the approach in trajectory tracking problems and the use of fuzzy precompensation has superior performance in terms of improvement in transient and steady state response, robustness to variations in loading conditions and ease to use in practice. Comparative evaluation with respect to genetic algorithm, particle swarm, and bacterial foraging based optimization is presented to validate the controller design. The proposed algorithm performs local search through the chemotactic movement operation of bacterial foraging whereas the global search over the entire search space is accomplished by a particle swarm operator and so satisfactory tracking precision could be achieved using the approach.
  Keywords: Bacterial Foraging, Particle swarm optimization, Fuzzy logic, rigid-flexible manipulators, Hybrid optimization, PD control
   
• Neural Network Inverse Decoupling Control of Stator Flux and Torque for Induction motor Drives
  by Wu Qinghui 
  Abstract: This paper focuses on the development of a stator flux and torque decoupling mechanism based on ANN inverse system for induction motor (IM). First, the existance of the inverse system for IM drives is approved by inverse system theory. However, the analytic inverse model is hardly applied in the engineering fields because it excessively depends on the IM parameters. Therefore a neuro network inverse model is deeply researched, and the method of synthetizing neuro-network and analytic function is suggested in this paper. To accelerate the convergence speed of neuro-network and enhance its generalization ability, the nonlinear operations are realized by the analytic operation method and the corresponding results act as the inputs of network. A three-layered feed-forward ANN with 11-40-2 structure is introduced to approach the inverse mode of IM drives. In order to eliminate the coupling between stator flux and torque, an ANN based inverse decoupling control scheme is constructed. In addition, simulation results are provided to validate the effectiveness of the proposed scheme.
  Keywords: Induction motor drives; Decoupling control; Neural network inverse system
   
• Computation of Frequency Responses for Uncertain Fractional-order Systems
  by P. S. V. Nataraj, Rambabu Kalla 
  Abstract: Present paper proposes an algorithm for computation of Bode magnitude and phase responses for a large class of linear uncertain fractional-order systems using interval constraint propagation technique. It is first shown that the problem of finding the magnitude and phase of the uncertain fractional-order system over a frequency range can be formulated as a interval constraint satisfaction problem and then solved using branch and prune algorithm. The algorithm guarantees that the magnitude and phase responses are computed to prescribed accuracy. The other advantage of the method is the magnitude and phase can be computed without any kind of integer-order approximation of the given fractional-order system. The proposed algorithm is demonstrated on three examples including a practical application of a gas turbine plant.
  Keywords: Constraint satisfaction problems, Control system analysis, Fractional-order systems, Interval analysis, Parameter uncertainty, Reliable computation, Robust control.
   
• A model based control development for optimising the driving performance of a cone ring transmission in a vehicle
  by Nikolaos Papakonstantinou 
  Abstract: Since 1995 GIF - Gesellschaft für Industrieforschung mbH has been involved in the development of the cone ring transmission (KRG), which is a new traction based continuously variable transmission (CVT). The KRG is suitable for small to medium class vehicle applications and is characterised by high efficiency, high dynamics and low costs. In this manuscript, we present the functional description of the KRG as well as the development of the control system for the ratio adjustment. Using model based techniques a robust control system is developed that ensures a high dynamic response of the ratio adjustment. Additionally to control qulality, comfort is an important factor for ensuring the acceptance of the KRG. Using a vehicle model the driving behaviour of the vehicle equipped with KRG can be predicted and optimised before the vehicle application. The developed control algorithms and strategies are validated on a vehicle equipped with KRG using a prototype transmission control unit.
  Keywords: automotive transmission, continuously variable transmission (CVT), controls, simulation, model based development.
   
• A FUZZY DECISION TREE BASED ROBUST MARKOV GAME CONTROLLER FOR ROBOT MANIPULATORS
  by Hitesh Shah, M. Gopal 
  Abstract: Two-player zero-sum Markov game framework offers an effective platform for designing robust controllers. In the Markov game-based learning, theoretical convergence of the learning process with the function approximator cannot be guaranteed. However, fusing Q-learning with decision tree function approximator has shown good learning performance and more reliable convergence. It scales better to larger input spaces with lower memory requirements, and can solve problems that are infeasible using table lookup. This motivates us to introduce decision tree function approximator in Markov game reinforcement learning framework. This approach works, though it deals with only discrete actions. In realistic applications, it is imperative to deal with continuous state-action spaces. In this paper, we propose Markov game framework for continuous state-action space systems using fuzzy decision tree as a function approximator. Simulation experiments on a two-link robot manipulator bring out the importance of the proposed structure in terms of better robust performance and computational efficiency.
  Keywords: Markov game; Reinforcement learning control; Decision tree; Fuzzy Q-learning
   
• Minimizing total flow time in permutation flow shop scheduling using a simulated annealing-based approach
  by Dipak Laha, Uday Chakraborty 
  Abstract: This paper presents an efficient simulated annealing algorithm for minimizing the total flow time in n-job, m-machine permutation flow shop scheduling problems. Empirical results demonstrate that the proposed approach is competitive with the best three methods in the flow shop literature. Statistical tests of significance are used to validate the improvement in solution quality.
  Keywords: Flow shop scheduling; simulated annealing; heuristics; optimization; total flow time
   
• Design of PID Controllers for Dead-Time Systems using Simulated Annealing Algorithms
  by Kanthaswamy Ganapathy, Jovitha Jerome 
  Abstract: The method of simulated annealing based optimization provides a non oscillatory bounded solution closed loop response for a large class of optimization problems. The idea is to find a PID controller setting based on minimization of cost function that makes the response from the set point to plant output as close as possible. In this paper, the performance of a PID controller designed using the Simulated Annealing, Directed Search Simulated Annealing (DSSA) based on Simplex Simulated annealing (SSA), Heuristic Pattern Search based Simulated Annealing (HPSSA) algorithms are exhaustively discussed and the results are found promising compared to the earlier non heuristic methods proposed by Ioannis Kookos and George Syrcos (2005), Luyben (1996,2001), Visioli (2001) and Chidambaram (1998,2003).
  Keywords: Proportional-Integral-Derivative (PID) Control, Simulated Annealing, Simplex Simulated Annealing, Directed Search Simulated Annealing, Heuristic Pattern Search based Simulated Annealing, Time-delay systems, Integral Square Error (ISE).
   
• Tracking of Non Stationary Distorted Power Signals using Complex H∞ Filter
  by P. K. Dash, H.K. Sahoo 
  Abstract: -The present study proposes a novel method of tracking the time varying frequency and amplitude of a distorted power signal using a Complex H∞ Filter. A new model structure is proposed for estimation of different power quality disturbances of a distorted power signal. The amplitude and phase of different harmonics are also estimated which shows the robustness of the filter. The performance of Complex H∞ Filter has been compared with those of ECKF (Extended Complex Kalman Filter) considering signals, which can represent worst case measurement and network conditions in a typical power system. State Space Representation with three states is used for estimation of amplitude and frequency in presence of white noise. Results of simulation demonstrate that under identical conditions, the performance of Complex H∞ Filter is better compared to ECKF.
  Keywords: Distorted signals, Complex H∞ filter, Frequency Estimation, Additive White Gaussian Noise.
   
• POTENTIAL FIELD BASED NAVIGATION TASK FOR AUTONOMOUS FLIGHT CONTROL OF UNMANNED AERIAL VEHICLES
  by Ömer CETIN, Sefer KURNAZ, Okyay KAYNAK, Hakan TEMELTAS 
  Abstract: This paper proposes to generate potential fields for navigation task of Unmanned Aerial Vehicles (UAVs) which have fuzzy logic based autonomous flight controls. Three fuzzy logic modules are developed under the main navigation system for the control of the altitude, the speed, and the heading, through which the global position of the air vehicle is controlled. A potential field block is used before the fuzzy logic based main navigation system. Three potential fields are generated by using sigmoid and normal functions. The output of this block produces a two dimensional elliptical shape as the fight pattern of the UAV with the target point being in the center of the shape. The third dimension of the three dimensional space is the altitude, which is taken to be a constant. Limiting functions are defined to provide the circling pattern and to limit the elliptical shape. The flight pattern of the UAV in the potential field is controlled by adjusting a set of tuning parameters of limiting functions. Despite the simple design procedure, the simulated test flights indicate the capability of the approach in achieving the desired performance.
  Keywords: Potential Fields, Fuzzy Logic Flight Control, Navigation Task of UAV