中文摘要：

提出了一种具有无静差跟踪性能的Hénon混沌系统广义预测控制快速算法.采用改进的时变遗忘因子递推最小二乘方法辨识混沌系统,通过在常规广义预测控制性能指标函数中引入前馈增益矩阵与柔化矩阵,并将MP神经元网络与BP算法相结合在线调整柔化因子,实现系统对参考信号的无静差快速跟踪.该算法避免了矩阵求逆计算,能够很好地跟踪参考信号.仿真结果验证了该方法的有效性.

英文摘要：

A kind of fast generalized predictive control algorithm without static error for Hénon chaotic system is proposed. Firstly,the chaotic system is identified by improved recursive least squares parameter of time-varying forget factor. Then the softness factor is adjusted on line through combining MP neural network with BP algorithm,thus the fast tracking without static error of reference signa1 is realized by introducing the feedforward gain matrix and softening coefficient matrix into regular performance index function of generalized predictive control. The algorithm avoids the matrix inversion computation and has strong ability of tracking the reference signal. The simulated results show the effectiveness of this algorithm.