STUDY ON RECONSTRUCTION OF INTELLIGENT CONTROL SYSTEMS BY UTIUZING NONLINEAR H-INFINITY CONTROL AND COPUTATIONAL STATISTICS

非线性H无穷控制与计算统计重构智能控制系统的研究

基本信息

批准号：
14550457
负责人：
MIYASATO Yoshihiko
金额：
$ 2.5万
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：
2002
资助国家：
日本
起止时间：
2002 至 2005
项目状态：
已结题

项目摘要

1.New class of adaptive controllers which are optimal or sub-optimal to certain meaningful cost functionals, were derived. The adaptive H2 or H-infinity optimal (or sub-optimal) control systems are constructed for genoral daises of adaptive control problems.2.By extending the study result of 1, the nonlinear adaptive H-infinity control schemes are developed for nonlinear time-varying processes. The resulting control strategy is derived as a solution for certain class of H-infinity control problems, where estimation errors of tuning parameters and time-varying elements of system parameters are regarded as external disturbances.3.By extending the study result of 2, the nonlinear adaptive H-infinity control schemes are developed for nonlinear parametric models including three-layered neural networks. The resulting control strategy is derived as a solution for certain class of H-infinity control problems, where approximation errors and algorithmic errors in the estimation structures of non … More linear parametric models, are reqarded as external disturbances.4.The adaptive gain-scheduled H-infinity control strategy is developed for linear parameter-varying (LPV) systems. In the proposed control schemes, estimates of unknown scheduled parameters are obtained recursively, and those are fed to the controllers to stabilize plants and attain H-infinity control performance adaptively. Stability analysis is carried out via Lyapunov approaches based on linear matrix inequalities (LMI) in "Bounded Real Lemma".5.By applying the study results of 2 and 3 into 4, the robust control version of the adaptive gain-scheduled H-infinity control scheme is developed for LPV systems. Stabilizing control signals are added to regulate the effect of time-varying scheduling parameters, and those are derived as a solution of certain H-infinity control problems. The same control schemes are applied to the gain-scheduled control for LPV systems with nonlinear parametric models and time-delayed elements.6.The iterative learning control schemes by utilizing hybrid adaptation laws are developed for motion control of robotic manipulators. The gradient and least squares hybrid adaptation laws are proposed, and stability analysis of overall systems is carried out. Additionally, by extending hybrid adaptation schemes, two-dimensional adaptive control procedures are proposed. The two-dimensional adaptice control structures contain 2 types of adaptation processes, off-line tuning and on-line tuning, simultaneously, and provide more skillful learning properties where adaptive processes themselves are improved adaptively. Less

1. 推导了对于某些有意义的成本函数而言最优或次优的新型自适应控制器。自适应 H2 或 H-无穷最优（或次优）控制系统是针对自适应控制问题的一般问题而构建的。2。通过扩展1的研究结果，针对非线性时变过程开发了非线性自适应H-无穷大控制方案，导出了所得的控制策略作为某类H-无穷大控制问题的解决方案，其中估计误差为。 3.通过扩展2的研究结果，针对包括三层神经网络的非线性参数模型开发了非线性自适应H无穷控制方案。该策略是作为某类 H 无穷大控制问题的解决方案而导出的，其中非线性参数模型估计结构中的近似误差和算法误差被视为外部干扰。4.自适应增益调度 H 无穷大控制策略是针对线性参数变化 (LPV) 系统而开发的。在所提出的控制方案中，递归地获得未知调度参数的估计，并将这些估计值馈送到控制器以稳定对象并实现 H 无穷大。通过基于“有界实数引理”中的线性矩阵不等式（LMI）的Lyapunov方法进行自适应控制性能的稳定性分析。5.将2和3的研究结果应用到4中，针对LPV系统开发了自适应增益调度H无穷控制方案的鲁棒控制版本，添加稳定控制信号来调节时变调度参数的影响，并导出这些作为某些H无穷控制的解决方案。相同的控制方案也适用于具有非线性参数模型和时滞元件的LPV系统的增益调度控制。6.开发了利用混合自适应律的迭代学习控制方案用于机器人的运动控制。提出了梯度和最小二乘混合自适应法则，并对整个系统进行了稳定性分析，通过扩展混合自适应方案，提出了二维自适应控制结构。自适应过程、离线调整和在线调整同时进行，并提供更熟练的学习属性，其中自适应过程本身得到自适应改进。