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针对智能车高速行驶下对目标轨迹的快速跟踪要求,结合预瞄跟随理论设计了分数阶PID控制器(FOPID)。分数阶PID比传统PID控制器多两个参数自由度,所以在设计过程中有更大的灵活性。利用改进Oustaloup数字实现算法,框图化实现分数阶PID控制器,通过遗传算法对IAE性能指标寻优整定FOC参数并应用于智能车被控系统。S imu link仿真结果表明,对智能车系统,分数阶PID控制器具有比传统PID控制器更好的动态性能。并且,分数阶PID控制器具有更强的鲁棒性,当模型参数发生变化时,能够更好地保证系统稳定性。通过对比传统PID控制器和分数阶PID控制器的数字实现,证明了分数阶PID控制器在过程控制中的可操作性。
According to the requirement of fast tracking of target trajectory under the high speed of smart car, fractional PID controller (FOPID) is designed with the preview-following theory. Fractional PIDs have two more degrees of freedom than traditional PID controllers, so there is greater flexibility in the design process. The improved Oustaloup digital algorithm was used to realize the fractional order PID controller. The genetic algorithm was used to optimize the IAE performance index to set FOC parameters and apply it to the smart vehicle controlled system. Simulink simulation results show that for smart car systems, fractional PID controllers have better dynamic performance than traditional PID controllers. Moreover, the fractional PID controller is more robust and can better guarantee system stability when the model parameters change. By comparing the digital implementation of traditional PID controller and fractional PID controller, the feasibility of fractional PID controller in process control is proved.