A model-free self-tuning controller (STC) based on online support vector regression (SVR) is proposed to control nonlinear and multi-input multi-output (MIMO) systems in this paper. MIMO proportional–derivative–integral (PID) controller parameters are optimized via introduced MIMO STC architecture based on SVR. The closed-loop margin notion is enhanced for MIMO type STC architectures. The adjustment mechanism is composed of only STC structure, and system model is not needed. Optimal values of STC parameters are obtained using the tracking error without any need to estimate the controlled system dynamics. In the proposed control architecture, the prediction capability of SVR and the robustness of the PID controller are combined. The success of the introduced SVR-based MIMO STC has been assessed by simulations carried out on the nonlinear Van de Vusse benchmark system. Acquired results justify that proposed structure achieves good control performance.

本文提出了一种基于在线支持向量回归 (SVR) 的无模型自调整控制器 (STC) 来控制非线性和多输入多输出 (MIMO) 系统。MIMO 比例微分积分 (PID) 控制器参数通过引入的基于 SVR 的 MIMO STC 架构进行优化。MIMO 类型的 STC 架构增强了闭环裕度概念。调整机构仅由STC结构组成，不需要系统模型。STC 参数的最佳值是使用跟踪误差获得的，无需估计受控系统的动态特性。在所提出的控制架构中，SVR 的预测能力和 PID 控制器的鲁棒性相结合。引入的基于 SVR 的 MIMO STC 的成功已经通过在非线性 Van de Vusse 基准系统上进行的模拟进行评估。获得的结果证明所提出的结构实现了良好的控制性能。