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度和未知度的自适应控制系统的设计方法。在所提出的控制方案中，针对具有此类不确定性的过程构造了自适应镇定控制系统、模型参考自适应控制系统和自适应伺服控制系统。相关文献有I)、3)、5)、7)、8)、15)和17)。(2)研究了一种新的简单自适应控制系统的设计方法。结果表明，利用与相对度相同的高增益观测器，所提出的设计方法可以很容易地应用于一般的相对度情况，并且对于小的非结构不确定性，所提出的自适应控制系统的鲁棒性也得到了保证。相关文献6)和12)。(3)给出了一类新的自适应控制器，它们对于某些有意义的代价泛函是最优或次优的。对于一般的ad…，构造了自适应H2或HoO最优(次优)控制系统更多的适应性控制问题。相关的参考文献是2)、9)、10)、11)和21)。然后，将这些方法应用于时变过程的自适应非线性HOO控制系统的设计。新的控制方案是作为特殊的非线性控制问题的解而得到的，其中未知系统参数被视为对过程的外部扰动，因此所得到的控制系统对于任意大但有界的时变参数变化是有界的。相关的参考文献是13)、14)、16)、18)、20)和24)。将自适应最优控制策略应用于神经网络自适应非线性Hco控制系统的设计。这些控制方案是作为特殊的非线性HCO控制问题的解而得到的，其中未知的系统参数和神经网络逼近器中的建模误差被视为过程的外部扰动。所得到的控制系统对于任意大但有界的时变参数变化和神经网络逼近器的建模误差是有界的。相关文献22)。(4)研究了线性变参数(LPV)系统的自适应增益调度控制方案。在所提出的自适应方案中，连续获得未知预定参数的估计，并将当前估计反馈给控制器以稳定被控对象并自适应地获得HOO控制性能。基于有界实引理中的线性矩阵不等式，利用Lyapunov方法对自适应控制系统进行了稳定性分析。得到了双线性过程的自适应或非线性控制系统的设计方法，并将部分方法应用于实际车辆的半主动悬架系统设计中。相关参考文献为4)和19)。较少

项目成果

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）。

Miyasato, Y.: "Redesign of adaptive control systems based on the notion of optimality"Proceedings of the 38th IEEE Conference on Decision and Control. Vol.4. 3315-3320 (1999)

Miyasato, Y.：“基于最优概念的自适应控制系统的重新设计”第 38 届 IEEE 决策与控制会议论文集。

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)。