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.     

具有理想跟踪特性的多变量变结构模型参考自适应控制

考虑一个广义相对阶为1的多变量系统之变结构模型参考自适应控制器(VS-MRAC) 设计问题,提出了一种切换控制方案,解决了现有多变量VS-MRAC和多变量模型参考自适应 控制(MRAC)中两个尚未解决的问题:1)使系统跟踪误差的每个分量均满足预先给定的性能指 标;2)无须假定对象高频增益矩阵满足通常的正定性条件.     

具有未规范化自适应律的直接型模型 参考自适应反推控制器

对于相对阶m>3的系统,给出了具有未规范化自适应律的直接型模型参考自适应反推控制器的设计和性能分析,从而解决了对于任意相对阶系统,具有未规范化自适应律的直接型模型参考自适应控制器的设计和性能分析问题.     

时变系统带δ—修正算法的直接自适应控制

考虑连续时变系统的直接自适应控制问题。研究带有δ－修正算法的自适应律，并导出这种自适应律中信号有界的充分条件；证明了δ－修正自适应算法适用于时变系统的模型参考自适应控制，并且控制系统是稳定的。仿真实例表明δ－修正算法是有效的。     

自适应控制对多级库存延迟问题的优化研究

针对在随机需求下交货延迟所导致供应链多级库存系统库存积压、缺货和牛鞭效应等问题,建立了基于自适应控制算法的多级库存动态优化模型。通过泰勒展开和拉布拉斯变换建立了基于APIOBPCS策略考虑延迟的动态多级库存控制模型;由Lyapunov渐进稳定性定理设计了一种适用于多级库存的模型参考自适应控制算法,其中以无交货延迟的参考库存模型作为目标,通过调节线性补偿函数和自适应控制率,逐渐缩小实际库存模型与参考库存模型间的输出误差,以此削弱交货延迟对多级库存模型的影响;通过实证数据验证了模型参考自适应控制对一个三级供应链库存系统的动态优化效果。仿真结果表明,自适应控制下的无信息共享多级APIOBPCS库存系统缺货全部归零,牛鞭效应下降40.7%。在不增加企业运营投入的前提下,通过自适应控制算法,优化资源配置,动态削弱了交货延迟对多级库存的影响,提升了供应链运营效率。     

基于PD增益的模型参考自适应同步控制

在保证自适应控制精度的前提下,找出快速收敛的参数,从而使被控系统和参考系统达到同步.针对传统的PI控制器无法获得参数波动的系统的较高的控制性能.基于模型参考自适应控制,利用PD控制器可以预料到系统误差的方向的优点,设计了一种自适应同步控制器.仿真结果表明,该自适应同步控制器能够使被控系统和参考系统达到同步,并能够较精确地控制被控系统的输出,使被控系统满足系统所要求的动态性能.这对研究组合自适应控制策略和开展多模型自适应控制器的研究提供了基础.     

大柔性飞行器的自适应姿态控制设计

研究系统存在不确定性的大柔性飞行器的姿态跟踪控制问题.针对高阶大柔性飞行器模型,使用平衡实现方法对其降阶,并通过奇异值对比分析系统降阶前后特性.基于降阶模型,设计LQR-PI控制器作为基线控制器.考虑不确定性,利用李雅普诺夫稳定性理论设计模型参考自适应控制器,并对比两种方法的控制效果.仿真结果显示,所提方案对包含不确定性的系统具有较好的控制效果,能使系统完成期望的姿态跟踪目标.     

OCXO高精度时间维持的自适应修正算法

针对广泛使用的低功耗、低成本、小体积恒温晶体振荡器(OCXO)在没有外部高精度时钟源校正的情况下难以长时间维持高精度授时的问题,分析了OCXO驯服系统的噪声特性以及晶体振荡器的老化特性和温度特性;建立OCXO驯服系统的自适应控制模型并采用增广最小二乘算法,解决了OCXO长时间在没有参考时钟的情况下频率精度降低的问题.在考虑参考时钟失锁条件下,对模型和算法进行仿真验证,结果表明:与常用的OCXO驯服保持模型相比,提出的模型具有最佳的逼近性能.     

自适应控制的发展动态

近年来,自适应控制领域取得的主要成果是:解决了大范围稳定性问题,弄清了自适应控制各种实现方法之间的等价性。这些发展成果使我们能用统一的方式来研究自适应控制的各种问题。 模型参考自适应控制(MRAC)和自校正调节器(STR)是解决自适应控制问题的两种主要方法。模型参考自适应控制已经被用于连续时间系统和离散时间系统,而自校正调节器仅能用来分析离散时间系统。不过到目前为止,模型参考自适应控制主要只用于确定性系统,而随机自校正调节器则是研究不确定性系统的有效方法。随着这两种方法之间等价性的建立,必将导致模型参考自适应控制和自校正调节器乏间的互相补充和互相促进。 本文的目的是简要地回顾一下近年来自适应控制的发展情况,并为将来的研究指出可能的方向。     

欠驱动船舶路径跟踪的神经网络稳定自适应控制

针对三自由度欠驱动船舶模型参数不确定的路径跟踪问题, 设计了神经网络稳定自适应控制器. 首先应用微分同胚等效变换和Lyapunov直接法设计参考航向和参考速度, 然后对船舶模型参数不确定的操纵环路和推进环路分别设计神经网络稳定自适应控制器跟踪参考航向和参考速度, 并对外界风浪流干扰进行自适应补偿.Lyapunov稳定性分析证明了船舶路径跟踪闭环系统的所有误差信号一致最终有界. 仿真研究验证了神经网络稳定自适应路径跟踪器的有效性.     

Imperfect model reference adaptive control: deadbeat output error approach

It is well known that while the perfect model matching condition (i.e. unstable plant zeros must be zeros of the reference model) is not met, the model reference adaptive control cannot easily be implemented. In adaptive control systems, since the plant is assumed to be unknown previously, it is a difficult task to choose an adequate reference model such that the perfect model matching condition is guaranteed in every adaptive step. In this paper, a new design algorithm for model reference adaptive control systems is proposed to synthesize an adaptive controller such that the error between the reference model output and the plant output can vanish in a deadbeat manner. In this situation, the stringent matching condition can be relaxed in every adaptive step, so our design algorithm is also suitable for unstable or non-minimum phase systems. Several simulation results are presented to illustrate the good behaviour of our design algorithm.     

对象参考参数自适应时滞补偿器

基于模型参考自适应控制原理,提出对象参考参数自适应时滞补偿器,以线性大时滞不确定被控对象为参考模型综合出自适应律,使预估补偿器的参灵敏逐步逼近被控对象的参数直至相等,仿真研究表明,在参数不匹配和出现负荷扰动的情况下,参数自适应时滞补偿器均有良好的预估补偿能力。     

Identifier-tracking model reference adaptive control

Model reference adaptive control is a major design method for controlling plants with uncertain parameters. The primary objective of this paper is to develop a new design approach for a differentiator-free model reference adaptive control of a single-input single-output linear time-invariant plant. The proposed method, called the “Identifier-tracking model reference adaptive control”, uses a stacked identifier structure that is new to the field of adaptive control. The goal is to make the output of the plant asymptotically track the output of the first identifier, and then driving the output of the first identifier to track that of the second identifier, and so forth, up to the qth identifier where q is the relative degree of the plant. Lastly, the output of the qth identifier is forced to converge to that of the reference model. Simulation results show the superiority of the proposed method over the traditional model reference adaptive control with augmented error in terms of the transient response. Since the resulting control systems are non-linear and time-varying, the stability analysis of the overall system plays a central role in developing the theory.     

An output error identification interpretation of model reference adaptive control

The task of discrete model reference adaptive control is manipulated into an output error identification problem. Strictly causal output error identifiers recently developed as adaptive recursive filters are therefore proposed for unique provision of a model reference adaptive control algorithm relying only on input-output data.     

基于自适应算法的IPMSM无速度传感器研究

针对电动汽车中电机的速度传感器成本高,安装繁琐,受复杂工况影响,提出将电流模型自适应算法应用于内置式永磁同步电机(IPMSM)转速和位置的估算,以替代机械式速度传感器。在传统的模型参考自适应基础上加入滑模变结构控制,以取代PI控制器;设计软开关函数替代符号开关函数,以减小滑模变结构控制造成的系统抖动。仿真试验表明,在加有负载扰动情况下和速度突变情况下,使用新型变结构模型参考自适应(SM-MRAS)估算的转速较传统模型参考自适应的抗干扰性能力更好,系统的鲁棒性更强。     

Set-theoretic model reference adaptive control with time-varying performance bounds

One of the fundamental problems in model reference adaptive control design is the ability of the controlled system to achieve not only stability but also a user-defined performance in the presence of exogenous disturbances and system uncertainties. To this end, we recently proposed a set-theoretic model reference adaptive control framework, which guarantees the norm of the system error to be less than a user-defined constant performance bound. The contribution of this paper is to generalise the set-theoretic model reference adaptive control framework for enforcing user-defined time-varying performance bounds on the system error, which gives the control designer a flexibility to control the closed-loop system performance as desired on different time intervals (e.g. transient time interval and steady-state time interval). Two adaptive command following control architectures are proposed and their stability and performance properties are rigorously established using system-theoretic methods.     

Model reference adaptive control of a nonlinear oscillator

A model reference adaptive system (MRAS) is applied to a nonlinear oscillator to achieve adaptive control. Since the model and plant of the system are not linearized to achieve the adaptive laws, the true behavior of the strongly nonlinear system is not lost. By considering important properties of the reference model describing a well-behaved nonlinear oscillator, it is possible to derive the error-equation, which is linear in the state variables. Liapunov synthesis is used to achieve adaptive control, and stability is thus guaranteed. The technique is simulated using an adaptive autopilot for a ship.     

Discrete-time deadbeat model reference adaptive control of an adjustable-speed DC motor drive system

An imperfect model reference adaptive control for a DC motor drive system having bounded disturbances is proposed. The discrete-time model reference adaptive control algorithm proposed by Chiang and Chen (1987) with bounded disturbances is introduced to an Elettronica Veneta Mod. IBS-4/EV DC motor. This work shows that the adaptive controller can maintain good performance during startup, anticlockwise, or clockwise winding in the regulating reference signals.     

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.     

Direct fuzzy model‐reference adaptive control

Intelligent systems may be viewed as a framework for solving the problems of nonlinear system control. The intelligence of the system in the nonlinear or changing environment is used to recognize in which environment the system currently resides and to service it appropriately. This paper presents a general methodology of adaptive control based on multiple models in fuzzy form to deal with plants with unknown parameters which depend on known plant variables. We introduce a novel model‐reference fuzzy adaptive control system which is based on the fuzzy basis function expansion. The generality of the proposed algorithm is substantiated by the Stone‐Weierstrass theorem which indicates that any continuous function can be approximated by fuzzy basis function expansion. In the sense of adaptive control this implies the adaptive law with fuzzified adaptive parameters which are obtained using Lyapunov stability criterion. The combination of adaptive control theory based on models obtained by fuzzy basis function expansion results in fuzzy direct model‐reference adaptive control which provides higher adaptation ability than basic adaptive‐control systems. The proposed control algorithm is the extension of direct model‐reference fuzzy adaptive‐control to nonlinear plants. The direct fuzzy adaptive controller directly adjusts the parameter of the fuzzy controller to achieve approximate asymptotic tracking of the model‐reference input. The main advantage of the proposed approach is simplicity together with high performance, and it has been shown that the closed‐loop system using the direct fuzzy adaptive controller is globally stable and the tracking error converges to the residual set which depends on fuzzification properties. The proposed approach can be implemented on a wide range of industrial processes. In the paper the foundation of the proposed algorithm are given and some simulation examples are shown and discussed. © 2002 Wiley Periodicals, Inc.