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)研究了具有不确定度和未知度的自适应控制系统的设计方法，提出了针对此类不确定度的自适应稳定控制系统、模型参考自适应控制系统和自适应伺服控制系统。 ，3），5），7），8），15）和17）。（2）考虑了一种新型简单自适应控制系统的设计方法，结果表明，所提出的设计方法可以很容易地应用于一般相关系统。通过利用与相对度数相同维度的高增益观测器，并且对于小的非结构化不确定性也保证了所提出的自适应控制系统的鲁棒性。相关参考文献是6)和12)。(3)新类别的自适应。自适应 H2 或 HOO 最优（次优）控制系统是针对一般类型的自适应控制问题而构建的。接下来，这些方法被应用于时变过程的自适应非线性 HOO 控制系统的设计，作为特定非线性 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生干扰，因此所得到的控制系统受限于时变参数的任意大但有界的变化。相关参考文献是 13)， 14)、16)、1 8)、20) 和 24) 也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，这些控制方案是作为特定非线性 Hco 的解而导出的。控制问题，其中神经网络逼近器中的未知系统参数和建模误差被视为对过程的外生干扰，由此产生的控制系统受到时变参数和建模误差的任意大但有界的变化的限制。相关参考文献为22)。 (4) 开发了线性参数变化(LPV)系统的自适应增益调度HOO控制方案。在所提出的自适应方案中，成功地获得了未知调度参数的估计。当前的估计被馈送到控制器以稳定对象并自适应地获得 HOO 控制性能，通过利用基于线性矩阵不等式的 Lyapunov 方法进行自适应控制系统的稳定性分析。相关参考文献为23)。(5)获得了双线性过程的自适应或非线性控制系统的设计方法，其中部分方法应用于实车半主动悬架系统的设计。和 19). 更少

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。