A fuzzy biomechanical model for optimal control of sit-to-stand movement

A four link biomechanical model of human stable movement is studied through fuzzy modeling and optimal control. Physiologists describe human sit-to-stand movement in different phases; a local linear model is developed for each phase and integrating all local models with Gaussian membership functions. These local linear models of sit-to-stand movement are generated from the general nonlinear model. The knee flexion during sit to stand movement provides the criterion for determining the weights of fuzzy membership functions. The torque inputs for the fuzzy model are computed by using optimal control techniques. In this paper we study a linear fuzzy model based H₂ controller for linear and nonlinear plant. Linear fuzzy Kalman filter is designed for estimating the states. The measurement noise in knee flexion and input noise in the plant model are analyzed through (linear quadratic Gaussian) LQG methods to determine the control inputs for the biomechanical model