Time-varying feedback stabilization of car-like wheeled mobile robots
International Journal of Robotics Research
Design of output feedback controllers for Takagi—Sugeno fuzzy systems
Fuzzy Sets and Systems - Special issue on formal methods for fuzzy modeling and control
Robot Motion Planning and Control
Robot Motion Planning and Control
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Evolution of fuzzy behaviors for multi-robotic system
Robotics and Autonomous Systems
Integral sliding mode control for trajectory tracking of a unicycle type mobile robot
Integrated Computer-Aided Engineering - Informatics in Control, Automation and Robotics
Tracking-error model-based predictive control for mobile robots in real time
Robotics and Autonomous Systems
Robotics and Autonomous Systems
An approach to fuzzy control of nonlinear systems: stability and design issues
IEEE Transactions on Fuzzy Systems
Parameterized linear matrix inequality techniques in fuzzy control system design
IEEE Transactions on Fuzzy Systems
NN'10/EC'10/FS'10 Proceedings of the 11th WSEAS international conference on nural networks and 11th WSEAS international conference on evolutionary computing and 11th WSEAS international conference on Fuzzy systems
Takagi-Sugeno vs. Lyapunov-based tracking control for a wheeled mobile robot
WSEAS Transactions on Systems and Control
A novel trajectory-tracking control law for wheeled mobile robots
Robotics and Autonomous Systems
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This paper presents a new technique for tracking-error model-based Parallel Distributed Compensation (PDC) control for non-holonomic vehicles where the outputs (measurements) of the system are delayed and the delay is constant. Briefly, this technique consists of rewriting the kinematic error model of the mobile robot tracking problem into a TS fuzzy representation and finding a stabilizing controller by solving LMI conditions for the tracking-error model. The state variables are estimated by nonlinear predictor observer where the outputs are delayed by a constant delay. To illustrate the efficiency of the proposed approach a comparison between the TS fuzzy observer and the nonlinear predictor observer is shown. For this study the reference trajectory is built by taking into account the acceleration limits of the mobile robot. All experiments are implemented on simulation and the real-time platform.