Liu Zhangxing, Jin Hongzhe, Zhao Jie
School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China.
Sensors (Basel). 2024 May 16;24(10):3178. doi: 10.3390/s24103178.
Control design for the nonlinear cascaded system is challenging due to its complicated system dynamics and system uncertainty, both of which can be considered some kind of system nonlinearity. In this paper, we propose a novel nonlinearity approximation scheme with a simplified structure, where the system nonlinearity is approximated by a steady component and an alternating component using only local tracking errors. The nonlinearity of each subsystem is estimated independently. On this basis, a model-free adaptive control for a class of nonlinear cascaded systems is proposed. A squared-error correction procedure is introduced to regulate the weight coefficients of the approximation components, which makes the whole adaptive system stable even with the unmodeled uncertainties. The effectiveness of the proposed controller is validated on a flexible joint system through numerical simulations and experiments. Simulation and experimental results show that the proposed controller can achieve better control performance than the radial basis function network control. Due to its simplicity and robustness, this method is suitable for engineering applications.
由于非线性级联系统复杂的系统动力学特性和系统不确定性,其控制设计具有挑战性,而这两者都可被视为某种系统非线性。本文提出了一种结构简化的新型非线性近似方案,其中系统非线性仅利用局部跟踪误差由一个稳态分量和一个交变分量来近似。每个子系统的非线性被独立估计。在此基础上,针对一类非线性级联系统提出了一种无模型自适应控制方法。引入了平方误差校正程序来调节近似分量的权重系数,这使得整个自适应系统即使在存在未建模不确定性的情况下也能保持稳定。通过数值模拟和实验在一个柔性关节系统上验证了所提控制器的有效性。仿真和实验结果表明,所提控制器能比径向基函数网络控制实现更好的控制性能。由于其简单性和鲁棒性,该方法适用于工程应用。