仿生四足机器人自适应粒子群优化控制

Adaptive Particle Swarm Optimization Control of Bionic Quadruped Robot

针对仿生四足机器人液压伺服驱动所带来的非线性和参数时变性等问题,有效抑制基于位置内环PID控制液压伺服系统过程中产生的高频振动对仿生四足机器人稳态行走的影响,采用自适应粒子群(PSO)算法优化位置内环PID控制的仿生四足机器人液压伺服系统。该方法能让PID控制器快速通过粒子种群的随机搜索和全局通讯来寻找最优解作为仿生四足机器人实时控制中的PID控制参数,优化液压伺服系统的传动性能。在分析仿生四足机器人结构和液压驱动模型的基础上,建立了液压伺服系统仿真模型。通过Mat Lab/Simulink软件对所建立的模型作为目标函数进行了正弦响应跟踪仿真试验,并在所设计的仿生四足机器人试验样机上进行了对角步态行走测试。实验结果表明:与传统的PID控制器相比,采用自适应粒子群(PSO)算法优化PID控制的液压伺服系统,具有更好的动态响应和鲁棒性,能够有效地提高对仿生四足机器人液压伺服系统的控制精度,保证仿生四足机器人能够平稳行走。

Aiming at the nonlinear and parameter caused by the bionic quadruped robot driven by hydraulic servo time-varying problems,and effectively suppress the high frequency vibration of PID position inner loop control of hydraulic servo system in the process of bionic quadruped robot based on steady-state walking effect,using adaptive particle swarm optimization（ PSO） algorithm of bionic quadruped robot hydraulic servo system position inner loop PID control. This method can be used to search for the optimal solution of the parameters of the PID controller in the real-time control of the bionic quadruped robot through the random search and global communication of the particle swarm,and optimize the performance of the PID controller. In this paper,the simulation model of the hydraulic servo system is established based on the analysis of the structure and the hydraulic drive model of the bionic quadruped robot. Matlab/Simulink software is used as the objective function to carry out the sine response tracking simulation test,and the test results are carried out on the experimental prototype. The test results show that compared with the traditional PID controller,using adaptive particle swarm optimization（ PSO） algorithm of hydraulic servo system PID control,has better dynamic response and robustness,can effectively improve the control precision of the hydraulic servo system of the bionic quadruped robot,bionic quadruped robot can ensure smooth walking.