STUDY ON OPTIMIZATION AND INTELLECTUALIZATION OF NONLINEAR ROBUST ADAPTIVE CONTROL

非线性鲁棒自适应控制的优化与智能化研究

• 批准号: 10650443
• 负责人: MIYASATO Yoshihiko
• 金额: $ 1.22万
• 依托单位: The Institute of Statistical Mathematics
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 1998
• 资助国家: 日本
• 起止时间: 1998 至 2001
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-10650443/
• 关键词: adaptive control; nonlinear control; H-infinity control; neural network; gain scheduled control; relative degree; parameter varying system; high gain observer; 線形行列不等式; ハイブリッドシステム; ゲインスケジュールリング; 最適制御; ニューラル・ネットワーク

(1) Design methods of adaptive control systems with uncertain relative degrees and unknown degrees were studied. Adaptive stabilizing control systems, model reference adaptive control systems and adaptive servo control systems for processes with such uncertainties are constructed in the proposed control schemes. The related references are I), 3), 5), 7), 8), 15) and 17).(2) A design method of new simple adaptive control systems was considered. It was shown that the proposed design method can be easily applied to general relative degree cases by utilizing high-gain observers with same dimensions as relative degrees, and that the robustness of the proposed adaptive control systems is also assured for small unstructured uncertainties. The related references are 6) and 12).(3) New classes of adaptive controllers which are optimal or sub-optimal to some meaningful cost functionals, were derived. Adaptive H2 or HOO optimal (sub-optimal) control systems are constructed for general class of ad … More aptive control problems. The related references are 2), 9), 10), 11) and 21). Next, those approaches were applied to the design of adaptive nonlinear HOO control systerns for time-varying processes. The new control schemes are derived as solutions of particular nonlinear HOO control problems, where unknown system parameters are regarded as exogenous disturbances to the processes, and thus the resulting control systems are bounded for arbitrarily large but bounded variations of time-varying parameters. The related references are 13), 14), 16), 1 8), 20) and 24). The adaptive optimal control strategies were also applied to the design of adaptive nonlinear Hcocontrol systems with neural networks (NN). Those control schemes are derived as solutions of particular nonlinear Hco control problems, where unknown system parameters and modeling errors in NN approximators are regarded as exogenous disturbances to the processes. The resulting control systems are bounded for arbitrarily large but bounded variations of time-varying parameters and modeling errors in NN approximators. The related reference is 22).(4) Adaptive gain-scheduled HOO controb schemes of linear parameter-varying (LPV) systems are developed. In the proposed adaptive schemes, the estimates of unknown scheduled parameters are obtained successively, and the current estimates are fed to the controllers to stabilize the plants and to attain HOO control performance adaptively. Stability analysis of the adaptive control systems is carried out by utilizing Lyapunov approaches based on linear matrix inequalities in the bounded real lemma. The related reference is 23).(5) Design methods of adaptive or nonlinear control systems for bilinear processes were obtained, parts of which were applied to the design of semi-active suspension systems in real vehicles. The related references are 4) and 19). Less

（1）研究了具有不确定相对程度和未知程度的自适应控制系统的设计方法。在建议的控制方案中构建了自适应稳定控制系统，模型参考自适应控制系统和具有此类不确定性的过程的自适应伺服控制系统。相关的参考为i），3），5），7），8），15）和17）。（2）一种新的简单自适应控制系统的设计方法。结果表明，提出的设计方法可以通过使用与相对程度相同的高度观察者来轻松地应用于一般相对程度的情况，并且还假定提出的自适应控制系统的鲁棒性对于小的非结构性不确定性。相关的参考为6）和12）。（3）得出了最佳或最佳的一些有意义的成本功能的新型自适应控制器。自适应H2或HOO最佳（亚最佳）控制系统是为AD的一般类别构建的……更具辅助控制问题。相关的参考为2），9），10），11）和21）。接下来，将这些方法应用于自适应非线性HOO控制系统的设计，以进行随时间变化的过程。新的控制方案被推导为特定非线性HOO控制问题的解决方案，其中未知的系统参数被视为对过程的外源性干扰，因此所得的控制系统是针对时间变化参数的任意较大但有界变化的。相关的参考为13），14），16），1 8），20）和24）。自适应最佳控制策略还应用于具有神经网络（NN）的自适应非线性HCO控制系统的设计。这些控制方案被推导为特定非线性HCO控制问题的解决方案，其中未知的系统参数和NN近似值中的误差被视为对过程的外源性干扰。所得的控制系统是针对随时间变化参数的任意较大但有界变化的绑定的，并在NN近似值中构建误差。相关参考为22）。（4）开发了线性参数变化（LPV）系统的自适应增益式HOO组合方案。在提出的自适应方案中，成功获得了未知的计划参数的估计值，并且当前的估计值被馈送到控制器中以稳定植物并自适应地获得HOO控制性能。自适应控制系统的稳定性分析是通过利用基于界面实际引理中线性基质不等式的Lyapunov方法进行的。相关参考是23）。（5）获得双线性过程的自适应或非线性控制系统的设计方法，其中一部分应用于实际车辆中半活性悬架系统的设计。相关的参考为4）和19）。较少的

项目成果

Miyasato, Y.: "Model reference adaptive control for a class of nonlinear systems with unknown degrees and uncertain relativedegrees"Proceedings of 1999 American Control Conference. Vol.1. 571-571 (1999)

Miyasato, Y.：“一类具有未知度和不确定相对度的非线性系统的模型参考自适应控制”1999 年美国控制会议论文集。

Miyasato, Y.: "Adaptive nonlinear H^∞ control for processes with bounded variatoins of parameters general relative degree case"Proceedings of the 39th IEEE Conference on Decision and Control. 1453-1458 (2000)

Miyasato, Y.：“具有参数一般相对度情况的有界变量过程的自适应非线性 H^∞ 控制”第 39 届 IEEE 决策与控制会议论文集 1453-1458 (2000)。

Miyasato, Y.: "A simple redesign of model reference adaptive control system and its robustness"Proceedings of the 37th IEEE Conference on Decision and Control. 2880-2885 (1998)

Miyasato, Y.：“模型参考自适应控制系统的简单重新设计及其鲁棒性”第 37 届 IEEE 决策与控制会议论文集。

宮里義彦: "CLF(Control Lyapunov Function)"計測と制御. Vol.38,No.11. 731 (1999)

Yoshihiko Miyazato：“CLF（控制李亚普诺夫函数）”测量与控制，第 38 卷，第 731 期（1999 年）。

Shigeru Hanba, Yoshihiko Miyasato: "Output feedback stabilization of bilinear systems using dead-beat observers"Automatica. Vol.37, No.6. 915-920 (2001)

Shigeru Hanba、Yoshihiko Miyasato：“使用无差拍观测器的双线性系统的输出反馈稳定性”Automatica。