基于单神经元PID的并联机构稳定控制研究

摘要

Parallel mechanism is a closed loop system, it 's composed of multiple parallel chains.Compared with the traditional mechanism, it has a series of advantages, such as high stiffness, high precision, high bearing capacity and so on. However, because of its strong nonlinearity and complicated control process, the control parameters of conventional PID are difficult to set. To solve the above problem, on the basis of traditional PID control theory, an adaptive PID control strategy based on single neuron is proposed, in order to realize the real-time tuning of PID control parameters. The semi-physical simulation is designed to verify the correctness of algorithm. The simulation results show that the control effect of the single neuron PID controller is better than that of the traditional PID controller.%并联机构由于非线性强、控制过程复杂, 导致常规PID控制参数难以整定.为了实现对二自由度并联机构更精确的控制, 结合神经网络, 文中提出了一种基于单神经元的自适应PID控制策略, 以实现PID控制参数的实时整定.通过dSPACE对被控对象进行半实物仿真, 仿真结果表明, 设计的单神经元PID控制器控制效果优于传统PID控制器.