具有超稳定结构的鲁棒自适应控制器

针对结构和参数未知的非线性系统,提出了一种具有神经网络的超稳定鲁棒自适应 控制器.控制器基于一阶线性模型,采用Popov超稳定理论设计,其建模误差由BP网在线辨 识,辨识结果在前馈补偿器中加以补偿,有效地实现了鲁棒自适应控制.文中还给出了仿真 结果.     

基于超稳定理论的小型无人机自适应控制策略研究

介绍一种基于Popov超稳定理论的无人机自适应控制策略,用于增强飞行控制系统的抗干扰性和对于时变参数的适应性.该控制方案首先根据LQR(linear quadratic regulator)原理对某无人机的纵向模型进行闭环反馈补偿,使被控模型满足Popov超稳定理论所要求的完全跟踪条件.然后,利用超稳定理论设计了模型参考自适应控制器,实现全部纵向飞行状态的无静差跟踪控制.最后,在系统存在参数摄动和外界干扰的情况下,对所提出的控制系统进行仿真研究.仿真结果表明,该控制方案能有效抑制受控对象自身参数摄动和外部干扰对于飞行状态的影响,具有较好的适应能力.     

交流定速比传动系统的前馈自适应控制*

针对工程机械定速比传动的特点，提出一种交流双机定速比传动自适应控制方法，控制器由一个比例反馈控制器和前馈自适应补偿器组成，构成一个定速比跟踪自适应复合控制系统。按Ｐｏｐｏｖ超稳定判据确定比例控制增益和自适应控制律系数，利用优化方法寻求最佳值。通过仿真验证了这种定速比自适应控制方法的有效性。     

模型参考自适应控制系统的两种简化方案

基于波波夫超稳定理论进行模型参数自适应控制系统设计,分别采用参考模型极点和零点做滤波器,设计了两种不用线性补偿器的简化模型参考自适应控制方案,避免了分解系统的繁琐工作,仿真验证本方案能实现渐进跟踪,且控制效果令人满意。     

基于超稳定理论克服对象扰动自适应模型跟随控制*

基于超稳定理论与自适应逆控制理论,提出了一种新的能够克服对象扰动的自适应控制算法.该算法既简化了线性补偿器的计算,又能克服确定性和随机扰动,使系统输出能快速、稳定地跟随参考模型输出.仿真结果证实了算法的可行性.     

基于MRAC的电阻炉温度控制系统

以工业电阻炉为研究对象，对系统进行分析，建立系统的离散数学模型，用超稳定理论设计了一个结构简单的参考模型自适应（MRAC）系统，仿真结果表明该系统超调量小，跟踪速度快。又以AT89C52单片机为核心实现了该温度控制器的硬件设计，具有一定的实际应用价值。     

模型参考自适应控制系统的两种简化方案

基于波波夫超稳定理论进行模型参考自适应控制系统设计,分别采用参考模型极点和零点做滤波器,设计出了两种不用线性补偿器的简化模型参考自适应控制方案,避免了分解系统的繁琐工作,仿真验证本方案能实现渐进跟踪,且控制效果令人满意     

高阶系统跟踪低阶模型的MRAC方案及在机械手伺服系统中的应用

基于popov超稳定理论，采用滤波器降阶的方法，设计了一种高阶系统跟踪低阶参考模型的模型参考自适应控制（MRAC）方案。使用低阶参考模型简化了系统结构，应用到机械手伺服系统中，验证了方案的有效性。     

对建模误差具有鲁棒性的MRAC方案

研究了模型参考自适应控制系统存在未建模动态的鲁棒性问题。基于Popov超稳定理论,采用从模型取状态技术,并将系统的建模误差转化为已知干扰,设计出一种对建模误差具有鲁棒性的MRAC方案。     

对建模误差具有鲁棒性的MRAC方案

研究了模型参考自适应控制系统存在未建模动态的鲁棒性问题。基于Ｐｏｐｏｖ超稳定理论,采用从模型取状态技术,并将系统的建论为已知干扰,设计出一种对建模误差具有鲁棒性的ＭＲＡＣ方案。     

Adaptive control of delay system

The result of exact model matching for delay systems developed by the author is extended to the adaptive control of delay systems. Likewise, using results from the adaptive control of systems without delay, the principle of constructing adaptive systems for delay plants is also very simple and clear.     

时延变化的滞后系统的HMRAC的设计

首次把混合自适应算法应用到时延变化的滞后系统中,实现了对时延变化的滞后系统的混合自适应控制,增强了该系统的鲁棒性.解决了以往由于时延变化而引起的滞后系统不稳定问题.     

Robust switching adaptive control of multi-input nonlinear systems

During the last decade a considerable progress has been made in the design of stabilizing controllers for nonlinear systems with known and unknown constant parameters. New design tools such as adaptive feedback linearization, adaptive back-stepping, control Lyapunov functions (CLFs) and robust control Lyapunov functions (RCLFs), nonlinear damping and switching adaptive control have been introduced. Most of the results developed are applicable to single-input feedback-linearizable systems and parametric-strict-feedback systems. These results, however, cannot be applied to multi-input feedback-linearizable systems, parametric-pure-feedback systems and systems that admit a linear-in-the-parameters CLF. In this paper, we develop a general procedure for designing robust adaptive controllers for a large class of multi-input nonlinear systems. This class of nonlinear systems includes as a special case multi-input feedback-linearizable systems, parametric-pure-feedback systems and systems that admit a linear-in-the-parameters CLF. The proposed approach uses tools from the theory of RCLF and the switching adaptive controllers proposed by the authors for overcoming the problem of computing the feedback control law when the estimation model becomes uncontrollable. The proposed control approach has also been shown to be robust with respect to exogenous bounded input disturbances     

A hyperstability criterion for model reference adaptive control systems

This paper considers the stability problem of the model reference adaptive control systems by means of the properties of hyperstable systems. A theorem concerning the hyperstability of model reference adaptive control systems is presented. This theorem directly gives a structure of the adaption mechanism. The results presented here include all the results obtained by Butchart, Shackcloth, Parks, Winsor, Roy, and Dressler. The hyperstability approach presented in this paper also allows for other solutions to the adaption mechanism and represents a general method for studying this type of adaptive systems. The results are directly applicable to the design of model reference adaptive control systems and they were verified for some particular cases by analogical simulation.     

连续时间混沌系统的参数自适应控制1)

研究了连续时间混沌系统的参数自适应控制,提出了关于多重参数混沌非线性系统的参数自适应控制的新方法.考虑系统参数是线性形式的自适应控制,利用Lyapunov方法证明了参数控制方程是全局渐近稳定的.研究结果表明该控制方法是分析混沌参数自适应控制的一个十分有效的方法.     

连续时间混沌系统的参数自适应控制

研究了连续时间混沌系统的参数自适应控制,提出了关于多重参数混沌非线性系统 的参数自适应控制的新方法.考虑系统参数是线性形式的自适应控制,利用Lyapunov方法 证明了参数控制方程是全局渐近稳定的.研究结果表明该控制方法是分析混沌参数白适应控 制的一个十分有效的方法.     

自适应超媒体技术及其在智能化CAI中的应用

将自适应超媒体的方法和技术应用于智能教学系统,可充分体现因材施教的思想,提高学生的学习效果。文章介绍了自适应超媒体系统的关键方法和技术,描述了智能教学系统的组成与结构,然后结合自适应教学系统KDAES的研制讨论了自适应技术对教学系统智能化的支持及系统核心模块——学生模型的构建。     

Adaptive control systems with robustness optimization to non-linear time-varying unmodelled dynamics

In this paper, the robustness properties of adaptive controllers to non-linear time-varying unmodelled dynamics are presented. A new robust stability criterion will be derived for analysing the robustness of adaptive control in deterministic systems under non-linear time-varying model errors. The concept of the excess robustness of adaptive systems is introduced, and the theory of the minimum H^∞ norm will be employed to solve the problem of robustness optimization in adaptive control systems. The results of simulations, which display the good performance of the robust adaptive controller according to our design algorithm, are also presented.