A New Adaptive Fuzzy Neural Networks Control Using Riccati-Like Equation for Controlling of Magnetorheological Fluid Device

A new proposed control based on the modified Riccati-like equation is developed in this study. The interval type 2 fuzzy model is applied and embedded in the controller for control the uncertainty and also support for calculation progress of the proposed control. To design of the control, the first sliding surface based on the conventional model is established and its elements using for combine with the other elements of the Riccati-like equation. The main input control includes equivalent control and robustness control. The equivalent control is found from the conventional analysis with the first sliding surface. However, the equivalence control is not sufficient for control the internal disturbance such as error approximation of the fuzzy model. Then the robustness control is designed including three components of PID control and matrices of the traditional model of Riccati equation. This approach has relation with the H infinity technique. Hence, the stability of the system is proved following the technique through the Lyapunov function. Model of the proposed control is evaluated by applying to the seat suspension system. In the suspension, a magneto-rheological (MR in short) damper with its stiffness following the variation of applied current is used. The main input control is applied to change the value of the applied current. Belong to the magnitude of vibration, the current is also changed. The results of simulation of the proposed control are shown that the proposed control is better for control real system.