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脉冲响应广义Hammerstein模型的约束模型算法控制

Constrained model algorithm control for the generalized Hammerstein model with impulse response
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摘要 提出一可描述"对称非线性系统"的脉冲响应广义Hammerstein模型。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。对控制输入加入饱和限幅限制,给出一约束多步模型算法控制,适用于开环稳定的"非最小相位"系统。提出一控制策略使算法无稳态偏差,且控制输入收敛于以原点为中心的变化域内。求解当前控制输入归结为线性不等式约束最优化问题,采用投影梯度法结合变尺度法寻优,证明了可行域内所有点均可做为投影梯度法的初始可行点,并证明线性不等式约束的任意紧约束组合其可行域即为正则域。仿真研究表明了上述研究的合理性和有效性。 A generalized Hammerstein model with impulse response for symmetric nonlinear systems is presented.A hyper-quadratic object function is developed by adding highest order control input term with a symbolic function into the object function,and a constrained multi-step model algorithmic control for the non-minimum phase systems with open-loop stable characterization is established by forcing the control input with saturated limitation.The algorithm with one control policy can guarantee the simulative results without steady state deviation and the control input being converged to a varying region centered in the zero-point.Determination of the current control input is associated to the linear unequal constrained optimization.Optimization results of the object function using the projection gradient algorithm combining the variable metric algorithm indicates that any point in the feasible region can be employed as the initial feasible point for the projection gradient algorithm and the feasible region consisted of any closely-constraints combination is a regular domain.The simulation results show that the constrained model algorithm control for generalized hammerstein model with impulse response is reasonable and applicable.
出处 《电气传动自动化》 2010年第5期18-22,共5页 Electric Drive Automation
基金 黑龙江省教育厅科学技术研究项目(11544045)
关键词 非线性系统 模型算法控制 目标函数 最优化 symmetric nonlinear system model algorithmic control object function optimization
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参考文献9

  • 1R. Isermann, K-H. Lachmann, D. Matko. Adaptive control Systems[M]. Prentice Hall International Ltd, 1992. 被引量:1
  • 2Maurath P R, Mellichamp D A, Seborg D E. Predictive Controller Design for SISO Systems [C]. Proc. A. C. C. Boston, 1985. 被引量:1
  • 3Bruijin P M, Bootsma L J. Predictive Control Using Impulse Response Model [C ]. 6th IFAC/IFIP Conference. Dusseldorf, 1980. 被引量:1
  • 4Clarke D W, et al. Generalized Predictive Control, Par Ⅰ, The Basic Algorithm; Part Ⅱ. Extensions and Interpretations[ J ]. Automatica, 1987,23(2): 137-148. 被引量:1
  • 5Rosen J. B. The Gradient Projection Method for Nonlinear Programming. Part 1: Linear Constraints [J], J. SIAM, 1960,8:181-217. 被引量:1
  • 6Davidon W C. Variable Metic Method for Minimization [M]. Argonne Nat. Iab.ANL-5990Rev. 1959. 被引量:1
  • 7Fletcher R, Powell M J D.A rapidly Convergent Descent Method for Minimization [ J ]. Computer Jour. 1963,6:163. 被引量:1
  • 8Cauchy A,Method General Pour La Resolution des Systems d/Equations Simultaneous [J]. Comp.Rend.Acod.Sci.Paris. 1847:536-538. 被引量:1
  • 9华罗庚著..优选学[M].北京:科学出版社,1981:179.

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