αth-Order Inverse Control Based on Online Least Square Support Vector Machines
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摘要: 提出基于最小二乘支持向量机在线算法的α阶逆控制方法.引入系统控制误差不敏感函数,在控制误差大于不敏感函数时,利用增量-剪枝学习算法,对已建立的离线逆控制器实施在线学习,以增强控制系统的鲁棒性.仿真结果表明:在系统没有受到噪声干扰时,在线逆控制器可以很好地使被控对象跟踪参考输入信号;在系统受到噪声干扰时,在线逆控制器比离线逆控制器具有更强的鲁棒性.Abstract: An αth-order inverse control method based on online least square support vector machines (LS-SVM) algorithm was proposed. An insensitive function of control system error was introduced. The controller constructed off-line is retrained online with the incremental and decremental algorithm when the control error is beyond the insensitive function to enhance the robustness of the control system. Simulation results show that the online inverse controller can track the reference signal accurately when there is no noise,and it is more robust than off-line controller when the system is disturbed by noises.
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