In electric vehicle’s nonlinear dynamic equations, some parameters has uncertainty such as the coefficient of rolling resistance, drag coefficient, armature resistance and field winding resistance. Design of a controller that is robust in the presence of these parametri
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In electric vehicle’s nonlinear dynamic equations, some parameters has uncertainty such as the coefficient of rolling resistance, drag coefficient, armature resistance and field winding resistance. Design of a controller that is robust in the presence of these parametric uncertainties and also in presence of external disturbances, and on the other hand simultaneously satisfies the optimality criteria, is a challenging issue. In practical applications, in addition to the above problem, the computational load of the control input should also be considered and provide a rational interaction between the controller's desirable performance and the calculations volume. In the present paper, a robust optimal stable fuzzy controller based on the parallel distributed compensation is designed, using Takagi-Sugeno fuzzy model of electric vehicle. The stabilizer feedback gains of fuzzy model, the upper bound of the uncertainties, the upper bound of the disturbances effect, and the upper bound of the cost function are obtained completely offline, through the solving of a minimization problem based on the linear matrix inequality. Therefore, the calculation volume of the control input is extremely low. This allows the practical implementation of the proposed controller. The favorable performance of the proposed controller is demonstrated in five-step simulations.
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