摘要
To overcome the disadvantage that the standard least squares support vector regression(LS-SVR) algorithm is not suitable to multiple-input multiple-output(MIMO) system modelling directly,an improved LS-SVR algorithm which was defined as multi-output least squares support vector regression(MLSSVR) was put forward by adding samples' absolute errors in objective function and applied to flatness intelligent control.To solve the poor-precision problem of the control scheme based on effective matrix in flatness control,the predictive control was introduced into the control system and the effective matrix-predictive flatness control method was proposed by combining the merits of the two methods.Simulation experiment was conducted on 900HC reversible cold roll.The performance of effective matrix method and the effective matrix-predictive control method were compared,and the results demonstrate the validity of the effective matrix-predictive control method.
To overcome the disadvantage that the standard least squares support vector regression （LS-SVR） algorithm is not suitable to multiple-input multiple-output （MIMO） system modelling directly, an improved LS-SVR algorithm which was defined as multi-output least squares support vector regression （MLSSVR） was put forward by adding samples＇ absolute errors in objective function and applied to flatness intelligent control. To solve the poor-precision problem of the control scheme based on effective matrix in flatness control, the predictive control was introduced into the control system and the effective matrix-predictive flatness control method was proposed by combining the merits of the two methods. Simulation experiment was conducted on 900HC reversible cold roll. The performance of effective matrix method and the effective matrix-predictive control method were compared, and the results demonstrate the validity of the effective matrix-predictive control method.
基金
Project(50675186) supported by the National Natural Science Foundation of China
关键词
支持向量回归
平整度控制
回归算法
最小二乘
智能控制
多输入多输出
控制矩阵
预测控制
least squares support vector regression
multi-output least squares support vector regression
flatness
effective matrix
predictive control
