Fuzzy observer-based control of MIMO interconnected systems subject to state delay, input nonlinearities, quantized input and output and sensor and actuator faults

This work investigates the design of a fault-tolerant quantized fuzzy observer-based controller for MIMO interconnected non-strict feedback time-delay systems subject to quantized output, sensor and actuator faults, input nonlinearities, and unknown dynamics. Compared to existing controllers for MIMO interconnected systems, the quantization of input and output signals are considered which makes the controller suitable for systems using networks with limited bandwidths. A novel fuzzy observer is proposed based on the quantized sensor fault, quantized fault-free control signal, and estimated sensor fault parameters which makes it more practical for real network applications. Moreover, sensor and actuator faults are taken into account; hence, the proposed controller can be applied to a wide range of real systems. To achieve the desired tracking performance in the presence of sensor faults, a term for estimating sensor fault parameters is included in the Lyapunov function and an adaptation law is derived. The controller can handle an infinite number of actuator failures and three types of input nonlinearities including saturation, back-lash, and dead-zone. The stability of the closed loop system has been established and the tracking errors converge to the neighborhood of the origin. The effectiveness of the proposed control scheme is demonstrated via simulation.