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针对两轮机器人传统PID控制器参数整定困难的问题,设计了一种神经元PID控制器。该控制器利用神经元的自学习和自适应能力,在线实时调整控制器各项参数。建立了两轮机器人的非线性模型,讨论了神经元PID控制系统的结构及其控制算法和各项控制器参数的学习算法。将设计的控制器其应用于两轮机器人的平衡控制中,并且与传统PID控制器进行了比较,仿真结果验证了控制器的正确性和有效性。将该控制器应用于两轮机器人物理系统,取得了良好效果。
Aimed at the difficulty of parameter tuning of traditional PID controller of two-wheeled robot, a neuron PID controller is designed. The controller uses the self-learning and adaptive ability of neurons to adjust the parameters of the controller online in real time. The nonlinear model of two-wheeled robot is established. The structure of the neuron PID control system and its control algorithm and learning algorithm of various controller parameters are discussed. The designed controller is applied to the balance control of two-wheeled robot and compared with the traditional PID controller. The simulation results verify the correctness and effectiveness of the controller. The controller is applied to two-wheel robot physics system and achieved good results.