Robust controller design for a class of MIMO nonlinear systems using TOPSIS function-link fuzzy cerebellar model articulation controller and interval type-2 fuzzy compensator

This research suggests a novel controller capable of achieving satisfactory tracking control performance for a class of multiple-input multiple-output (MIMO) systems. It aims to approximate an impracticable ideal controller to design directly due to insufficient knowledge about the plant or lack of data. The primary control unit is a function-link fuzzy cerebellar model articulation controller (FLFCMAC), applying the technique for order of preference by similarity to the ideal solution (TOPSIS) to eliminate less dominant rules in the fuzzy inference engine. A Function-link network (FLN) is added to this controller to enhance the tracking performance. Moreover, an interval type-2 fuzzy logic controller (IT2FLC) is proposed to improve the closed-loop system performance. Due to the caterpillar robot’s highly nonlinear dynamics and undesirable factors such as external disturbance and parametric uncertainties, online tuning laws are offered. In other words, the control system is designed to be robust. A Lyapunov stability approach is presented to show the stability of the controlled nonlinear plant. Furthermore, the adaptation laws are derived through this approach. Finally, numerical simulations are employed to validate the effectiveness and robustness of the controller for the caterpillar robot and the inverted double pendulum.