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针对车辆横向控制数学模型的非线性和时变特性,在输入输出线性化方法和模糊系统逼近理论的基础上,利用自适应算法实时调整更新模糊系统参数,设计出了基于输入输出线性化的自适应模糊滑模控制系统。对车辆模型进行仿真分析,结果表明:车辆自身参数和外部环境因素虽然变化了,但系统仍能准确地跟踪期望路径,车辆横向偏差和方向偏差都快速趋于零。同时车辆的前轮转角抖振有效降低了82%~93%。
Aiming at the nonlinear and time-varying characteristics of vehicle lateral control mathematical model, based on the input-output linearization method and the fuzzy system approximation theory, the adaptive algorithm is used to adjust and update the fuzzy system parameters in real time. Adaptive fuzzy sliding mode control system. The simulation analysis of the vehicle model shows that although the parameters of the vehicle itself and the external environment change, the system can still track the desired path accurately and the vehicle lateral and direction deviations rapidly tend to zero. At the same time the vehicle front wheel vibration buffering effectively reduced by 82% to 93%.