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针对随机广义Hammerstein模型,从实际对象的物理意义出发,分析了广义Hammerstein模型不能描述“对称非线性系统”的问题。在广义Hammerstein模型中加入控制输入的符号函数,提出一可描述“对称非线性系统”的随机广义Hammerstein模型,克服了广义Hammerstein模型要求其控制输入最高阶次为奇数的限制。在目标函数中加入控制输入的高次项和其符号函数,提出一超二次型目标函数。给出一自校正控制器算法,实用于开环不稳定且具有“非最小相位”的系统。仿真研究表明控制算法的有效性。
For the generalized generalized Hammerstein model, the generalized Hammerstein model can not describe the problem of “Symmetric Nonlinear System ” from the physical meaning of actual objects. By adding the sign function of control input to the generalized Hammerstein model, a stochastic generalized Hammerstein model describing “symmetric nonlinear system” is proposed, which overcomes the limitation that the generalized Hammerstein model requires the highest order of control inputs to be odd. By adding the high-order term of control input and its sign function into the objective function, a super quadratic objective function is proposed. A self-tuning controller algorithm is presented, which is applicable to a system with open-loop instability and “non-minimum phase”. Simulation studies show the effectiveness of the control algorithm.