基于LS-SVM的仿射非线性系统的最优跟随控制

Optimal tracking control for affine nonlinear systems based on LS-SVM

针对仿射非线性系统的最优跟随控制问题,提出了一种基于最小二乘支持向量机(least squares support vector machine,LS-SVM)的数据驱动方法.通过非线性系统已知信息和期望轨迹的离散数据构建LS-SVM模型,获得最优跟随轨线的近似解并求得最优跟随控制器,使系统达到期望的动态性能.数值算例仿真证实,该方法具有优化和学习能力,能够实现在较小误差范围内对期望轨迹的准确跟踪.

A data-driven approach based on least squares support vector machine （LS-SVM） is proposed to design optimal tracking controller for affine nonlinear systems. According to the information of the system and discrete data of the desired trajectory, the LS-SVM model is employed to obtain the approximate solution of optimal tracking trajectory and optimal tracking controller, which allows the system to achieve the desired dynamic performance. The numerical simulation examples are provided to verify that the proposed approach is an intelligent control method with optimization and learning ability and the system can track the desired trajectory in a small error bound.