基于非线性模型预测控制的移动机器人实时路径跟踪

针对移动机器人路径跟踪模型预测控制中,存在线性化预测模型削弱控制器对参考路径曲率突变和航向突变响应能力的问题,从非线性模型预测控制出发,提出了两种实时性优化方案,即减少控制步数或降低控制频率。仿真与实验结果表明,采用减少控制步数或降低控制频率方案优化后,非线性模型预测控制器在每一控制周期内的解算时间小于控制周期;减少控制步数相比降低控制频率或线性化预测模型具有更小的横向误差和航向误差,可以更好地保证控制器在跟踪曲率、航向变化较快的参考路径时的控制精度。因此,相比其他实时性优化方案,减少控制步数更加适用于农用机器人等对灵活性要求较高的移动装备。

Real-time Path Tracking of Mobile Robot Based on Nonlinear Model Predictive Control

The application of model predictive control in the path tracking control of mobile robots is increasingly widespread, and the real-time performance of controllers is gradually being noticed. At present, the common real-time optimization scheme is a linearizing prediction model scheme, which converts the nonlinear model predictive control into the linear time-varying model predictive control. However, the linearizing prediction model scheme will weaken the ability of the controller to respond to sudden changes in the curvature and heading of the reference path. Therefore, from the nonlinear model predictive control, two real-time optimization schemes were proposed, namely reducing the number of control steps or reducing the control frequency. In the results of simulation and experiment, in each control period, the calculation time of the nonlinear model predictive controller, which was optimized by reducing the number of control steps or reducing the control frequency, was shorter than the control period. At the same time, it can be known from the simulation and experiment that the scheme of reducing the number of control steps had smaller displacement errors and heading errors than the scheme of reducing the control frequency or the linearizing prediction model. That was, adopting the scheme of reducing the number of control steps can better ensure the control accuracy when tracking the reference path which with rapid changes in curvature and heading. Therefore, the scheme of reducing the number of control steps was more suitable than other real-time optimization schemes, for mobile equipment such as agricultural robots that require higher flexibility.