Reference model decomposition in direct adaptive control

This paper introduces the method of ‘reference model decomposition’ as a way to improve the robustness of model reference adaptive control systems (MRACs) with respect to unmodelled dynamics with a known structure. Such unmodelled dynamics occur when some of the nominal plant dynamics are purposely neglected in the controller design with the aim of keeping the controller order low. One of the effects of such ‘undermodelling’ of the controller is a violation of the perfect model-matching condition of the primary controller. The decomposition can be seen as a way to adjust the reference model output (and hence the control goal) to the actual model-matching capabilities. It is shown that the decomposition alleviates the negative effects unmodelled dynamics have on the error equation. Simulation examples illustrate the decomposition design steps and show the obtained improvements.     

A cautious approach to robust adaptive regulation

The problem of estimated model controllability in robust pole placement adaptive regulation is investigated. The adaptive control law is modified in the sense that some measure of the parameter estimates error is incorporated into the design, leading to ‘cautious’ control actions. Two pole placement adaptive control algorithms are presented and shown to be BIBO stable in spite of bounded disturbances, time-varying parameters and unmodelled dynamics.     

Self-tuning control of robot manipulators

We consider the tracking control problem for robot manipulators whose parameters are not exactly known. It is assumed that some unmodelled friction is acting at the actuated joints. The proposed solution guarantees that the disturbances on the outputs (the joint positions) can be attenuated by an arbitrary factor k. For the setpoint regulation problem a self-tuning controller is proposed. In this case the disturbances (uncertain parameters and unmodelled non-linearities) on the outputs are completely rejected asymptotically. Some simulation results are included.     

永磁直线同步电动机速度环自抗扰控制器的设计

针对永磁直线同步电动机具有强耦合性,存在未建模动态和不确定外部扰动的特点,首先运用矢量控制方法对模型进行解耦化简,将未建模动态和不确定外扰视为一个综合扰动项,然后利用自抗扰控制技术对综合扰动项进行观测和补偿,设计出了一种不依赖于对象模型的速度环鲁棒控制器.仿真结果证明,该控制器不仅具有良好的抗外扰能力,同时对系统的内部参数如动子质量、主磁极磁链等的摄动也具有较强的鲁棒性.     

Model reference adaptive control applied to electrical machines

This contribution reports about a discrete-time robust adaptive control strategy for single-input/single-output systems with arbitrary zeros. The adaptive algorithm is mainly based on a direct model reference method. The basic idea presented here is to divide the feedback law into a direct adaptive and a fixed part. By a certain choice of the non-adaptive controller parameters the robustness of the adaptive control loop with respect to unmodelled dynamics of the plant may be increased. The non-adaptive part of the controller can be reformulated as a bypass to the plant and will be denoted as the ‘correction network’ owing to its action on the open-loop zeros of the augmented plant. The new adaptive control strategy removes the major drawbacks of model reference control and is investigated for speed control of a DC motor and voltage control of a synchronous generator.     

Robust model reference adaptive control for multivariable plants

A complete procedure for generating and analysing robust model reference adaptive control schemes for multivariable plants is developed. The procedure consists of two parts: the first part involves the characterization of the integral structure of the modelled part of the plant, and the associated parametrization of the controller structure; and the second part involves the development of a general robust adaptive law for adjusting the controller parameters so that the closed-loop plant is globally stable despite the presence of unmodelled dynamics and bounded disturbances. The use of dominantly rich signals for improving convergence and the bounds for the tracking and parameter error is also analysed.     

Enhancement of power system dynamic performance through an on-line self-tuning adaptive SVC controller

Static VAr compensators (SVC) are used for voltage control of long distance bulk power transmission lines. By using a supplemental control loop an SVC can also be used to improve the dynamic and transient stability of a power system. Use of a self-tuning adaptive control algorithm as a supplementary controller for the SVC is presented in this article. The control derived is based on a pole-shifting technique employing a predicted plant model. Simulation studies on a simple power system model showed rapid convergence of the estimated plant parameters with an extremely good damping profile. The controller has been tested for ranges of operating conditions and for various disturbances. The effectiveness of the adaptive damping controller was also evaluated through an ‘optimized’ PI controller.     

Robustness of VS-MRAC with respect to unmodelled dynamics and external disturbances

A variable structure model reference adaptive controller (VS-MRAC) using only input and output measurements was recently proposed and shown to be globally asymptotically stable with superior transient behaviour and disturbance rejection properties. In this paper a singular perturbation approach is used in order to establish the robustness of the controller in the presence of unmodelled dynamics (parasitics) and disturbances. We develop a new Lyapunov-based technique to analyse the overall system and show that for sufficiently small parasitics the system remains stable and the output error is small in some sense.     

基于扰动观测器的电力系统鲁棒滑模控制器设计

针对多机电力系统中的励磁系统,设计一种基于扰动观测器的滑模控制(Perturbation Observer based Sliding-mode Control, POSMC)以提高系统稳定性。首先,将系统的非线性、参数不确定性、未建模动态和外部时变扰动聚合为一个扰动,同时由一个滑模状态扰动观测器(Sliding-mode State and Perturbation Observer, SMSPO)对该扰动进行实时快速估计。随后,通过滑模控制器对该扰动估计进行在线完全补偿以实现全局一致的控制能力。POSMC具备结构简单、可靠性高、不依赖系统精确模型以及仅需测量发电机功角一个状态量等优点。最后,基于机械功率阶跃变化、三相短路以及发电机参数不确定性三个算例验证了POSMC的有效性和鲁棒性,其能在各种工况下实现最佳的动态性能,有利于电力系统发生故障后恢复稳定运行。     

A new robust model reference control with improved performance for a class of multivariable unknown plants

Motivated by recent works on parametrization of multivariable plants for model reference adaptive control (MRAC), a new robust model reference control (MRC) scheme for a class of multivariable unknown plants is presented. The salient feature of this control scheme is the improved performance of the output-tracking property, which is hardly attainable by the traditional MRAC schemes. The controller here is devised using the concept of variable structure design which prevails in the robust control context. It is shown by a Lyapunov approach that without any persistent excitation the global stability of the overall system is achieved and the tracking errors will converge to a residual set. The size of that set can be directly related to the size of unmodelled dynamics and output disturbances explicitly as long as a set of control parameters is chosen properly (large).     

Robust adaptive control of robotic manipulators without the regressor matrix

A new adaptive controller is presented here for rigid-body robotic manipulators. It is stable and robust with respect to a class of external disturbances. The robustness of the adaptive controller is established without the ‘slow-varying’ assumption and the computationally demanding regressor matrix. The control law consists of a non-adaptive PD control part and an adaptive control part. It uses two adaptive matrices to compensate two uniformly bounded coefficient matrices derived from the original dynamics. A α σ|q?|-modified adaptive law is designed to adjust the adaptive matrices. A Lyapunov-type stability analysis indicates that the closed-loop system is uniformly ultimately bounded. The tracking error and compensation error will eventually converge into a closed region, which can be made arbitrarily small by adjusting the controller parameters. Simulation results are included to demonstrate the performance of the proposed controller.     

超级电容储能系统鲁棒分数阶PID控制设计

针对超级电容储能系统(supercapacitor energy storage system, SCES)设计了一款鲁棒分数阶PID (robust fractional-order PID control, RFOPID)控制。首先,利用高增益扰动观测器(high-gain perturbation observer, HGPO)对SCES的非线性、未建模动态和参数不确定性所聚合的扰动进行实时快速估计。接着,该扰动由分数阶PID (fractional-order PID, FOPID)控制器进行完全补偿。所提控制器不依赖于精确的SCES模型,仅需测量dq轴电流,易于硬件实现。最后,通过3种算例对RFOPID控制的控制性能进行评估。仿真结果表明:与其他控制器相比,RFOPID控制在各种工况下均具有最佳的控制性能和最强的鲁棒性。     

同步发电机最优非线性自适应励磁控制器设计

设计了一款最优非线性自适应励磁控制器(Optimal Nonlinear Adaptive Excitation Controller, ONAEC)用于多机电力系统以提升系统故障恢复能力。首先,通过一个高增益扰动观测器(High-Gain Perturbation Observer, HGPO)对由发电机的非线性、不确定性、未建模动态等效聚合而来的扰动进行实时快速估计。随后,该扰动由ONAEC进行在线完全补偿并通过改进樽海鞘群算法(Modified Salp Swarm Algorithm, MSSA)获取其最优控制参数。另外ONAEC具备结构简单、易于实现等优点,且仅需测量发电机功角一个状态量便可实现全局一致的控制性能。最后,进行了两种算例研究,即标称模型以及参数不确定下的三相短路。其仿真结果表明,与比例-积分-微分(Proportional-Integral-Derivative, PID)控制和反馈线性化控制(Feedback Linearization Control, FLC)相比,ONAEC能在各种工况下实现最佳的动态性能,有利于系统受到较大扰动后快速恢复稳定运行。     

基于Riccati法的静止无功补偿器变结构鲁棒控制

为了抑制电力系统静止无功补偿器(SVC)的非线性特性、未建模动态、系统参数变化及外部扰动影响,应用变结构控制理论与鲁棒控制理论,设计了能同时改善电力系统功角稳定与装设点电压动态性能的SVC非线性变结构鲁棒控制器.控制器考虑了含SVC的单机--无穷大系统(SMIB)模型可能的不确定性项,以其标称系统所对应的代数Riccati方程的解来构造滑动模态超平面,进而给出变结构鲁棒控制算法.设计的控制规律简洁,鲁棒性强且易于工程实践.仿真结果表明,与传统PI控制方式相比,变结构鲁棒控制器能够更有效地阻尼系统振荡,提高系统暂态稳定性能.     

Further evaluation of partial,state model reference adaptive design

This paper is a follow up to Reference 1. It presents further evaluation of the partial state model reference adaptive control approach proposed in Reference 2. This evaluation involves suitable benchmark examples that have been proposed in Reference 3 to illustrate the essence of today's adaptive control design techniques. Particular emphasis is put on the ability of the considered adaptive controller to accommodate state disturbances, sensor noise and unmodelled dynamics.     

为提高轮廓加工精度采用DOB和ZPETC的直线伺服鲁棒跟踪控制

为了提高轮廓加工精度,本文针对高精度直线伺服系统,提出了一种将零相位误差跟踪控制器(ZPETC)和干扰观测器(DOB)相结合的鲁棒跟踪控制策略.ZPETC作为前馈跟踪控制器,保证了快速性,使系统实现准确跟踪;基于DOB的鲁棒反馈控制器补偿了外部扰动、未建模动态、系统参数变化和机械非线性等,保证了系统的强鲁棒性能.仿真结果表明了所提出的控制方案是有效的,既能实现完好跟踪,又有较强的鲁棒性能.从而有效地减小了轮廓误差,提高了轮廓加工精度.     

Robust nonlinear adaptive backstepping excitation controller design for rejecting external disturbances in multimachine power systems

This paper proposes a new approach to design a robust adaptive backstepping excitation controller for multimachine power systems in order to reject external disturbances. The parameters which significantly affect the stability of power systems (also called stability sensitive parameters) are considered as unknown and the external disturbances are incorporated into the power system model. The proposed excitation controller is designed in such a way that it is adaptive to the unknown parameters and robust to external disturbances. The stability sensitive parameters are estimated through the adaptation laws and the convergences of these adaptation laws are obtained through the negative semi-definiteness of control Lyapunov functions (CLFs). The proposed controller not only provides robustness property against external disturbances but also overcomes the over-parameterization problem of stability sensitive parameters which usually appears in some conventional adaptive methods. Finally, the performance of the proposed controller is tested on a two-area four machine 11-bus power system by considering external disturbances under different scenarios and is compared to that of an existing nonlinear adaptive backstepping controller. Simulation results illustrate the robustness of the proposed controller over an existing one in terms of rejecting external disturbances.     

Identification for the robust control of robot manipulators

In this paper an identification scheme, which yields bounds on unmodelled dynamics along with an estimate for the parameters of a nominal dynamic model, has been presented. These estimates are useful for designing a robust controller for trajectory control of robot manipulators, if they satisfy certain conditions. These conditions have been stated mathematically. Guidelines are provided for selecting a data set for identification such that the obtained estimates satisfy the above conditions. Simulation results are presented for a two‐link serial manipulator, when frictional torques are treated as unmodelled. Copyright © 2001 John Wiley & Sons, Ltd.     

具有不确定性参数的轧机主传动系统自抗扰控制器设计

轧机主传动系统通常由直流电机驱动,其性能好坏直接影响板带材的产量和质量.针对轧机主传动系统存在不确定性负荷扰动和未建模动态的特点,首先建立了轧机主传动系统的模型,将不确定性负荷扰动和未建模动态视为一个综合扰动项,然后利用扩张状态观测器对综合扰动项进行观测和补偿,基于自抗扰控制技术设计了一个不依赖于对象模型的轧机速度鲁棒控制器.仿真结果表明:该控制器不仅有效地抑制了不确定负荷扰动的影响,同时对系统内部参数如电机转动惯量、电枢电阻等的摄动也具有较强的鲁棒性.     

永磁同步发电机自适应分数阶变桨距角控制

提出了一款基于扰动观测器的分数阶比例-积分-微分(Perturbation observer based Fractional-order ProportionalIntegral-Derivative, PoFoPID)控制策略,以在永磁同步发电机(Permanent Magnetic Synchronous Generator, PMSG)高于额定风速的工况下,通过变桨距角控制,将发电机输出功率维持在其额定值附近。首先,将PMSG的系统非线性、参数不确定性和未建模动态等聚合为新的扰动,并采用扰动观测器对其进行在线估计。然后,设计分数阶PID控制对该扰动估计进行实时完全补偿,以提高系统动态特性。此外,PoFoPID控制器参数通过群天牛算法寻优获得,避免了常规PID控制参数依赖人工整定的缺陷。斜坡风速、随机风速和参数不确定算例下的仿真结果表明,与矢量控制、基于扰动观测器的PID控制和反馈线性化控制相比,所提PoFoPID控制具有满意的输出功率稳定效果。最后,基于dSpace进行的硬件在环实验(Hardware-in-loop, HIL)验证了所提方法的硬件可行性。