New results on output-feedback variable structure model-referenceadaptive control: design and stability analysis

The variable structure model-reference adaptive control(VS-MRAC) redesign and stability analysis, presented previously by the authors (1993) for the case of plants with relative degree n*⩽2, is generalized to the case of arbitrary n*⩾1. This paper presents a complete stability analysis in the general case. The redesign is based on the explicit consideration of input disturbances which may include the disturbance originated by the uncertainty of the plant high-frequency gain. This leads to a considerably simpler and less restrictive stability analysis as well as to a systematic controller design for external disturbance rejection. The overall error system is globally exponentially stable with respect to a small residual set. Robustness to unmodeled dynamics is also discussed     

具有理想跟踪特性的鲁棒变结构模型参考自适应控制1)

针对相对阶为1的定常线性被控对象,提出了一种控制增益可切换的鲁棒变结构模型参考自适应控制方案.该方案在对象参数及高频增益符号均未知的情形下,可确保跟踪误差满足预先给定的过渡过程性能指标,即超调量、过渡过程时间和稳态误差.     

A variable structure MRAC with expected transient and steady-state performance

A new output feedback variable structure model reference adaptive control (VS-MRAC) scheme is proposed in this paper for uncertain plants with relative degree one. The scheme is based on the existing VS-MRAC structure together with a high gain switching mechanism to adjust the variable structure control signal. The main features of the scheme are that (1) the pre-specified transient and steady-state performance specifications for tracking error can be guaranteed, (2) it does not require the plant high frequency gain sign to be known a priori, (3) the usual assumption for MRAC system that the reference model is strictly positive real (SPR) is not needed and (4) the plant input disturbance, which is assumed to be unknown but bounded, can be completely rejected.     

A new adaptive backstepping method for nonlinear control of turbine main steam valve

A new approach for nonlinear adaptive control of turbine main steam valve is developed. In comparison with the existing controller based on ＂classical＂ adaptive backstepping, this method does not follow the classical certaintyequivalence principle in the design of adaptive control law. We introduce this approach, for the first time, to power systems and present a novel parameter estimator and dynamic feedback controller for a single machine infinite bus （SMIB） system with steam valve control. This system contains unknown parameters such as reactance of transmission lines. Besides preserving useful nonlinearities and the real-time estimation of uncertain parameters, the proposed approach possesses better performances with respect to the response of the system and the speed of adaptation. The simulation results demonstrate that the proposed approach is better than the design based on ＂classical＂ adaptive backstepping in terms of properties of stability and parameter estimation, and recovers the performance of the ＂full-information＂ controller. Hence, the proposed method provides an alternative for engineers in applications.     

Multirate digital adaptive control

A design method is developed which involves the use of several adaptive controllers working in parallel at different sampling rates while maintaining the asymptotic stability of the overall adaptive scheme, as well as the boundedness of all the signals within the system. The use of adaptive sampling is considered as an additional loop in a hierarchical organization of the scheme. This strategy allows the designer to take advantage of the suitable properties of such schemes which are well known in classical multirate control designs. These advantages arise from the need for alleviating control computer throughput requirements of accommodating sensor information available at multiple rates and for compensating excitations of the fast modes of the plant in the presence of high-frequency disturbances. As a direct consequence of the involved methodology, the transient behaviour of the adaptive system becomes in some cases greatly improved.     

A discrete-time parameter estimation based adaptive actuator failure compensation control scheme

This article studies discrete-time adaptive failure compensation control of systems with uncertain actuator failures, using an indirect adaptive control method. A discrete-time model of a continuous-time linear system with actuator failures is derived and its key features are clarified. A new discrete-time adaptive actuator failure compensation control scheme is developed, which consists of a total parametrisation of the system with parameter and failure uncertainties, a stable adaptive parameter estimation algorithm, and an on-line design procedure for feedback control. This work provides a new design of direct adaptive compensation of uncertain actuator failures, using an indirect adaptive control method. Such an adaptive design ensures desired closed-loop system stability and tracking properties despite uncertain actuator failures. Simulation results are presented to show the desired adaptive actuator failure compensation performance.     

一类非线性系统的间接自适应模糊滑模控制

基于启发式知识的模糊控制是一种解决非线性系统控制问题的有效方法。然而其设计缺乏系统性,并且系统的稳定性和鲁棒性难以保证。本文利用滑模控制的概念和Lyapunov综合方法提出一种针对一类非线性系统的间接自适应模糊滑模控制（IAFSMC）方法。仿真研究表明即使在缺少系统先验知识和不确定性干扰的情况下,系统性能也十分理想。     

Fuzzy-enhanced Adaptive Control for Flexible Drive System with Friction Using Genetic Algorithms

When a mechatronic system is in slow speed motion, serious effect of nonlinear friction plays a key role in its control design. In this paper, a stable adaptive control for drive systems including transmission flexibility and friction, based on the Lyapunov stability theory, is first proposed. For ease of design, the friction is fictitiously assumed as an unknown disturbance in the derivation of the adaptive control law. Genetic algorithms are then suggested for learning the structure and parameters of the fuzzy-enhancing strategy for the adaptive control to improve system's transient performance and robustness with respect to uncertainty. The integrated fuzzy-enhanced adaptive control is well tested via computer simulations using the new complete dynamic friction model recently suggested by Canudas de Wit et al. for modeling the real friction phenomena. Much lower critical velocity of a flexible drive system that determines system's low-speed performance bound can be obtained using the proposed hybrid control strategy.     

Globally stable adaptive system design for minimum phase SISO plants with input saturation

Model reference adaptive control problem for single-input single-output time-invariant continuous-time plants with input saturation is considered with main attention focused on global properties. A sufficient condition is presented and a new design method of adaptive control systems is proposed. If a priori information about the plant is available to choose the reference model and the reference input so that the sufficient condition holds, the closed-loop adaptive control system designed by the proposed method can have global stability and globally output tracking property. It is shown that the sufficient condition becomes necessary in some cases.     

鲁棒自适应控制系统的设计

本文提出了鲁棒自适应控制系统的两种设计方案。第一方案为具有逻辑决策环节的模型参考自适应控制系统,即使在被控对象结构不确知的情况下此方案仍能保证全局稳定。在第二种方案中采用混合式自适应控制,采用一种新的参数估计器,利用参数估计结果在离散时刻调节控制器参数。     

离散时间间接型模型参考自适应控制的一种系统化的分析方法

This paper presents the design and analysis of indirect model reference adaptive control(MRAC)with normalized adaptive law for a class of discrete-time systems.The main work includes three parts.Firstly,the constructed plant 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 finding the relationship between the plant parameter estimate and controller parameter estimate and using the properties of plant parameter estimate,the similar properties of controller parameter estimate are also established. Thirdly,based on the relationship properties between the normalizing signal and all the signals in the closed-loop system and on some important mathematical tools on discrete-time systems,as in the continuous-time case,a systematic stability and convergence analysis approach to the discrete indirect MRAC scheme is developed rigorously.     

An improved stable adaptive fuzzy control method

Stable adaptive fuzzy control is a self-tuning concept for fuzzy controllers that uses a Lyapunov-based learning algorithm, thus guaranteeing stability of the system plant-controller-learning algorithm and convergence of the plant output to a given reference signal. In the paper, two new methods for stable adaptive fuzzy control are presented. The first method is an extension of an existing concept: it is shown that a major drawback of that concept, the necessity for new adaptation at every change of the reference signal, can be avoided by a simple modification. The main focus of the paper is on the presentation of a second method, which extends the applicability of stable adaptive fuzzy control to a broader class of nonlinear plants; this is achieved by an improved controller structure adopted from the neural network domain. Performance and limitations of the proposed methods, as well as some practical design aspects, are discussed and illustrated with simulation results     

考虑输入约束的发电机汽门非线性自适应控制

研究具有汽门控制和阻尼系数不确定的单机无穷大系统的暂态稳定性问题. 通过引入切换机制, 解决了输入控制量幅值约束问题. 基于主汽门控制和快速汽门控制思想, 建立了一个由汽门控制的单机无穷大汽轮发电机切换系统模型. 应用本文提出的改进自适应Backstepping方法设计了切换子系统的非线性自适应控制器和参数替换律, 同时构造出切换系统的共同Lyapunov函数, 从而保证了切换系统的稳定性. 由于设计过程中, 未用到任何线性化方法, 因而所得控制器充分利用了系统的非线性特性. 仿真结果表明了设计方法的有效性和优越性.     

Robust adaptive control of synchronous generators with SMES unit via Hamiltonian function method†

Superconducting Magnetic Energy Storage (SMES) units can be used to enhance the stability of power systems. Using Hamiltonian function method, this article investigates robust adaptive control design for synchronous generators with such a unit, and proposes an energy-based robust adaptive controller for the systems with disturbances and unknown parameters. The generator used in this article is a 4th order model with both excitation and steam valve controls. It is shown that the generator with one SMES unit can be changed as a dissipative Hamiltonian system, with which the energy-based robust adaptive control law can be designed for the system by using the structural properties of dissipative Hamiltonian systems. Study on simulations shows that the controller proposed in this article works very well.     

Nonlinear adaptive control of master–slave system in teleoperation

This paper is devoted to the nonlinear control design problem to achieve stability of master–slave manipulators in teleoperation system and its transparency in the sense of motion/force tracking. Nonlinear adaptive controllers are bilaterally designed for both master and slave sites to guarantee the stability of whole system and motion tracking performance. Global boundedness of the overall adaptive system and asymptotic motion (velocity/position) tracking are established. Especially, the concept of “virtual master manipulator” is introduced to increase degree of freedom of control design for force tracking performance. The resulting force tracking error depends only on the acceleration of the designed virtual master manipulator. Accurate dynamic parameters of manipulators, their acceleration information as well as models of human operator and environment are not required in the control design. Another important feature of our approach is the relaxation for the trade-off between motion and force tracking performances.     

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.     

Robust adaptive regulation with minimal prior knowledge

A robust adaptive regulator is designed under minimal prior knowledge, namely, the order of a nominal plant model (in a well defined sense). The involved robustness means that the closed-loop stability is guaranteed in the presence of some class of time-varying parameters and unmodeled dynamics. The main design feature of the proposed adaptive regulator consists in its self-excitation capability together with an appropriate identification-stabilization time splitting. Unlike in the available literature concerning robust adaptive control, the involved self-excitation is established independently of the parameter estimator properties. The use of the robustness-oriented modifications as deadzone and parameter projection or contraction, which are aimed at achieving the parameter estimates boundedness, is no longer required beforehand, thereby reducing the underlying prior knowledge     

Neural model-based adaptive control for systems with unknown Preisach-type hysteresis

An adaptive control scheme is presented for systems with unknown hysteresis. In order to handle the case where the hysteresis output is unmeasurale, a novel model is firstly developed to describe the characteristic of hysteresis. This model is motivated by Preisach model but implemented by using neural networks (NN). The main advantage is that it is easily used for controller design. Then, the adaptive controller based on the proposed model is presented for a class of SISO nonlinear systems preceded by unknown hysteresis, which is estimated by the proposed model. The hws for model updating and the control hws for the neural adaptive controller are derived from Lyaptmov stability theorem, therefore the semi - global stability of the closed-loop system is guaranteed. At last, the simulation results are illuswated.     

Theory and design of robust direct and indirect adaptive-control schemes

A general approach for designing and the theory for analysing robust direct and indirect adaptive-control schemes for continuous-time plants is presented. The design approach involves the development of a general robust adaptive law and the use of the certainty equivalence principle to combine it with robust model reference and pole placement control structures. The global stability properties and robustness of the developed adaptive control schemes are established by using a general theory which relates the properties of signals in the mean sense over intervals of time. The developed theory and design approach are used to analyse and compare the robustness properties and performance of a wide class of robust adaptive laws which employ a dead-zone, fixed-σ, ε₁, and a switching-σ modification as well as their variations.     

自适应机翼的神经网络控制系统设计与试验

随着自适应结构和机敏材料的发展,如何从结构设计角度来提高飞机的飞行效能受到了重视,其中的一个关键环节就是控制器的设计和开发.针对自适应机翼姿态控制的要求与物理特点,采用神经网络和自适应控制理论,设计了神经网络逆复合控制器,完成了相应的控制系统开发,进而进行了物理试验分析和研究.结果表明,系统能有效、准确、快速地在线满足设计目标跟踪和设计状态回归两项重要指标,系统的鲁棒性、收敛性和稳定性都得到明显地改善,具有良好的可靠性和工程实用性.