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Dynamic-free robust adaptive intelligent fault-tolerant controller design with prescribed performance for stable motion of quadruped robots

In this article, a robust adaptive intelligent fault-tolerant controller with prescribed performance is proposed for an uncertain quadruped robot with actuator fault. The control system comprised of three terms: (1) a full-state feedback controller which includes the prescribed performance function, (2) an adaptive intelligent wavelet-based Takagi-Sugeno fuzzy network (TSFN), and (3) a robust control term. The proposed controller does not utilize the robot dynamic model. A wavelet-based TSFN is utilized to approximate adaptively the lumped nonlinear terms, parameter uncertainties, and defective torque signal. The wavelet block acts as a feature extractor, reduces the number of fuzzy rules, and also acts as a normalization function. The parameters of TSFN are tuned online by an adaptive law based on Lyapunov stability theory. The proposed controller guarantees the desired specification such as minimum speed of convergence, maximum steady-state error, overshoot concerning the position tracking error, and also bounded closed-loop signals. Numerical simulations on MATLAB/SimMechanics environment demonstrate the stable walking of the quadruped robot in the presence of the actuator faults and parameter uncertainties.