相对阶n= 3 = 3 的鲁棒直接型模型参考自适应控制

针对相对阶n^*=3具有噪声的一类简单系统，给出了具有未规范化自适应律的鲁棒直接型模型参考自适应控制器的设计，通过引入非线性阻尼项，保证了闭环系统的所有信号都是全局稳定的，而且跟踪误差及参数估计误差均收敛于零。     

多级的模型参考自适应控制器设计

本文将对象分解为串级形式来设计MRACS ,解决了高阶复杂的被控对象在发生大范围和不可测变化时引起的不稳定问题。并进行了计算机仿真。     

飞机纵向运动模型参考反推自适应PID控制

为克服飞行控制系统设计中传统增益规划方案的缺点,提出一类飞机纵向运动模型参考反推自适应PID控制方案,并给出了该方案的具体设计过程和跟踪性能改善方法．理论分析和数值仿真结果表明．该方案兼具反推自适应控制和PID控制的优点．即：无需知道被控对象的精确数学模型,控制器结构简单,鲁棒性强,在不增大控制增益的前提下具有良好的跟踪性能．     

混合的直接型模型参考自适应控制

本文研究了具有混合自适应律的直接型模型参考自适应控制.对这种混合的MRAC方案,我们严格地证明了闭环系统的所有信号都有界,同时得到了跟踪误差满足e1∈S(μ2(△2+△2∞)+d20+1/a20).同文献[1]的控制方案相比,这种具有混合自适应律的直接型模型参考自适应控制具有如下优点:1)实现过程中计算量大大减小;2)具有更好的鲁棒性.     

低增益变结构模型参考自适应控制器设计

就对象相对阶大于1时的变结构模型参考自适应控制（VS－MRAC）系统提出了一种低增益变结构控制方案,主要特点是：1）系统变结构律在低增益状态下仍可保证所有辅助误差在有限时间内收敛到零,从而提高了系统跟踪精度;2）进一步研究了平均值滤波器对系统稳定性的影响。     

一种基于反推技术的鲁棒自适应控制器

对于更一般的一类系统,给出了一种基于反推技术的鲁棒自适应控制器的设计方法.通过重新定义动态规范化信号和重新证明相关的性质,严格地分析了闭环系统的稳定性和跟踪性能;同时指出了相关文献中的错误.     

间接型的混杂模型参考自适应控制

针对相对阶为1的理想系统,本文考虑了具有混杂自适应律的间接型模型参考自适应控制问题.通过建立系统和控制器的离散参数估计和它们的插值四者之间关系的性质,严格地分析了闭环系统的稳定性,证明了闭环系统中所有的信号都一致有界,并且跟踪误差渐进收敛于零.     

模型参考模糊神经网络控制器的开发

给出一种用模糊神经网络控制器作调节器，用模糊逻辑和BP算法的结合作自适应机构的模型参考自适应模糊神经网络控制器。为一类缺乏精确数学模型的被控对象提供了一种有效的自适应控制方法。仿真验证了该方法的合理性。     

具有未知高频增益的鲁棒自适应反推控制器

在高频增益未知的情况下,对一类带有未建模动态和输入、输出干扰的系统,给出了一种基于反推技术的鲁棒自适应控制器的设计方法.通过修正传统鲁棒自适应控制中的动态规范化信号和切换-σ算法,证明了闭环系统的所有信号都有界,同时可以取得较好的跟踪性能.仿真结果表明了该方法的有效性.     

时变系统具有MT-滤波器的反推自适应控制

研究线性时变系统具有MT-滤波器的反推自适应控制问题。给出了具有MT-滤波器和σ修正自适应律的反推自适应控制器的设计，分析了闭环系统的稳定性和跟踪性能。同已有文献相比，难点在于误差系统的构造，并且稳定性的证明更加复杂。     

Design and stability analysis of a variable structure adaptive backstepping controller

This paper presents the design and stability analysis of a Variable Structure Adaptive Backstepping Controller (VS‐ABC) for linear plants with relative degree one, using only input/output measurements. Instead of traditional integral adaptive laws for estimating the plant parameters, switching laws are proposed to increase robustness to parametric uncertainties and disturbances, as well as to improve transient response. Moreover, the controller design is more intuitive when compared with the original adaptive backstepping controller, since the relay amplitudes are related to the plant nominal parameters and their respective uncertainties. Simplified algorithm versions are also presented, named Compact and Relay VS‐ABC, which reduce the practical implementation complexity, and encourage applications in industrial environments. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Direct adaptive control using an adaptive reference model

Direct model reference adaptive control is considered when the plant-model matching conditions are violated due to large changes in the plant or incorrect knowledge of the plant's mathematical structure. Because of the mismatch, the plant can no longer track the original reference model, but may be able to track a modified reference model that still provides satisfactory performance. The proposed approach uses a time-varying ‘adaptive’ reference model that reflects the achievable performance of the changed plant. The approach consists of direct adaptation of state feedback gains for state tracking and simultaneous estimation of the plant-model mismatch. The reference model adapts to the changed plant, and is redesigned if the estimated plant-model mismatch exceeds a bound determined via robust stability and/or performance criteria. The resulting controller offers asymptotic state tracking in the presence of plant-model mismatch as well as matched parameter deviations.     

Robustness analysis of discrete-time indirect model reference adaptive control with normalized adaptive laws

For a class of discrete-time systems with unmodeled dynamics and bounded disturbance, the design and analysis of robust indirect model reference adaptive control (MRAC) with normalized adaptive law are investigated. The main work includes three parts. Firstly, it is shown that the constructed parameter estimation algorithm not only possesses the same properties as those of traditional estimation algorithms, but also avoids the possibility of division by zero. Secondly, by establishing a relationship between the plant parameter estimate and the controller parameter estimate, some similar properties of the latter axe also established. Thirdly, by using the relationship between the normalizing signal and all the signals of the closed-loop system, and some important mathematical tools on discrete-time systems, as in the continuous-time case, a systematic stability and robustness analysis approach to the discrete indirect robust MRAC scheme is developed rigorously.     

发电机的非线性自适应逆推综合控制

发电机励磁和汽门系统是一个典型的多变量、非线性、强耦合、不确定复杂系统,其综合控制将会改善电力系统稳定性和动态品质,所以设计简单、有效的综合控制器既必要又困难.针对单机无穷大励磁与汽门系统,运用自适应逆推方法和系统的Lyapunov函数,获得了发电机的非线性综合控制器和参数替换律,文中给出了该控制器的具体设计步骤.由于在控制器设计中没有运用任何线性化方法,因而所得控制器充分利用了系统的非线性特性;同时考虑了发电机阻尼系数的不确定性,使得控制器对系统参数的变化具有很强的鲁棒性.数字仿真结果表明,所设计的控制器具有鲁棒性,并可有效地提高电力系统的稳定性.     

船舶动力定位非线性自适应反步控制器设计

针对扰动不确定非线性船舶动力定位问题,提出了一种带观测器的不确定扰动非线性船舶动力定位自适应输出反馈控制.设计了一个非线性观测器,从附有噪声的输出中估计出船舶位置以及运动速度.用滤波后的位置信号,针对扰动不确定非线性船舶设计带观测器的自适应反步控制器,该控制在Backstepping设计方法的基础上引入积分环节,对存在未知参数和动态不确定扰动的船舶能有效的改善系统性能.根据Lyapunov稳定性理论证明所设计的控制器是全局渐近稳定的,仿真结果验证了该方法的有效性.     

Iterative learning of model reference adaptive controller for uncertain nonlinear systems with only output measurement

In this paper, a model reference adaptive control strategy is used to design an iterative learning controller for a class of repeatable nonlinear systems with uncertain parameters, high relative degree, initial output resetting error, input disturbance and output noise. The class of nonlinear systems should satisfy some differential geometric conditions such that the plant can be transformed via a state transformation into an output feedback canonical form. A suitable error model is derived based on signals filtered from plant input and output. The learning controller compensates for the unknown parameters, uncertainties and nonlinearity via projection type adaptation laws which update control parameters along the iteration domain. It is shown that the internal signals remain bounded for all iterations. The output tracking error will converge to a profile which can be tuned by design parameters and the learning speed is improved if the learning gain is large.     

基于后推设计的直接自适应模糊控制

针对一类严格反馈不确定非线性动态系统，提出一种直接鲁棒自适应模糊控制新方案．利用模糊系统的逼近能力、后推设计方法和积分型李亚普诺夫函数，依次确定各虚拟控制及模糊系统中可调参数的自适应律，并最终确定出控制律．为改善控制系统的性能，引入逼近误差的自适应补偿项．通过李亚普诺夫方法，证明了闭环系统是一致终结有界的．仿真结果表明了该方法的有效性。