摘要
通过中值定理将一类非线性系统近似为时变线性系统,然后将提出的在线最小二乘支持向量机回归(OLS-SVMR)与广义预测控制相结合,提出了一种基于OLS-SVMR的自适应直接广义预测控制.利用OLS-SVMR直接设计预测控制器,并基于广义误差估计对控制器参数和广义误差估计中的未知向量进行自适应调整.理论证明了该方法可使广义误差估计值收敛到原点的一个小邻域内.仿真算例也验证了该方法的有效性.
A class of nonlinear system is replaced by a time varying linear system based on the mean value theorem. Then by combining the presented online least square support vector machine regression （OLS-SVMR） with the generalized predictive control （GPC）, an adaptive direct generalized predictive control method based on the OLS- SVMR is presented. The OLS-SVMR is used to design the controller directly. The controller parameters and unknown vectors in the estimation of generalized error are adjusted adaptively. It is proved that the presented method can make the eatimation of generalized error converge to a small neighborhood of the origin. The simulation results show the effectiveness of the presented method.
出处
《控制与决策》
EI
CSCD
北大核心
2009年第4期520-525,531,共7页
Control and Decision
基金
国家自然科学基金重点项目(60534020)
国家973计划项目(2002CB312205)
北京市重点学科基金项目(XK100060526)
高等学校博士学科点专项科研项目(20070006060)
中国博士后科学基金项目(20070410359)
