Robust tracking control for a class of uncertain electrically driven robots

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Robust tracking control for a class of uncertain electrically driven robots

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The problem of designing robust tracking controls for a large class of robots actuated by brushed direct current motors is addressed. This class of electrically driven robots can be perturbed by plant uncertainties, unmodelled time-varying perturbations and external disturbances. Adaptive neural network (or fuzzy) systems are employed to approximate the behaviours of uncertain dynamics, and the variable structure system control algorithm is used to efficiently eliminate the effect of both the approximation error and the time-varying perturbation. Consequently, a hybrid robust adaptive dynamic feedback tracking controller is developed such that all the states and signals of the closed-loop system are bounded and the asymptotic bound on the trajectory tracking error can be made arbitrarily small. Finally, simulation examples are presented to demonstrate the effectiveness and the tracking performance of the proposed control algorithm.

Inspec keywords: tracking; robust control; control system synthesis; mobile robots; path planning; adaptive control; fuzzy systems; feedback; fuzzy control; variable structure systems; neurocontrollers; electric actuators; asymptotic stability; robot dynamics; DC motors; time-varying systems; closed loop systems

Other keywords: uncertain electrically driven robot; actuator dynamics; variable structure system control algorithm; fuzzy system; asymptotic bound; closed-loop system; trajectory tracking error; adaptive neural network; hybrid robust adaptive dynamic feedback tracking controller design; brushed direct current motor; robust motion tracking control; approximation error; time-varying perturbation

Subjects: Electric actuators and final control equipment; Self-adjusting control systems; Time-varying control systems; Spatial variables control; Neurocontrol; Mobile robots; Multivariable control systems; Stability in control theory; Control system analysis and synthesis methods; Robot and manipulator mechanics; Fuzzy control

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