This paper investigates the feasibility of applying the stochastic method to the evaluation and design of vehicle control systems. Vehicle motion is modeled by nonlinear dynamic equations containing 10 uncertain parameters. The system robustness is characterized by the probability of instability and probabilities of violation of prescribed performance indexes, subject to the variation of uncertain vehicle parameters. These probabilities are estimated by applying the Monte Carlo method to the results of a large number of vehicle dynamics simulations. Four types of vehicle control strategies are chosen to demonstrate the effectiveness of stochastic method to analyze the robustness of the control systems. Then the stochastic method is applied to the design of the nonlinear vehicle control systems. A stochastic cost function containing engineering design criteria is minimized by Genetic Algorithm, producing optimal controller parameters for given control structures. The stochastic approach improves the robustness of the vehicle control systems.
Stochastic Robustness Analysis and Synthesis of Nonlinear Vehicle Dynamics Controller
Vehicle System Dynamics ; 37 , sup1 ; 183-196
2002-01-01
14 pages
Article (Journal)
Electronic Resource
English
Stochastic robustness analysis and synthesis of nonlinear vehicle dynamics controller
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