Fuzzy Nonlinear Predictive Control of Stewart Platform

In this paper a fuzzy robust nonlinear model predictive controller based on state estimation for Stewart platform is designed. The control law is based on prediction model, which is carried out via Uncertainties fuzzy estimator. The optimal control is computed directly from the minimization of receding horizon cost function. There is no need to an online optimization. A fuzzy estimator is designed to deal with system uncertainties such as unknown external disturbances, unmodeled quantities and parametric uncertainties. The global stability closed loop system is proved analytically via Lyapunov stability theory. The performance of the proposed method is compared with PID controller.