A novel adaptive backstepping design of turbine main steam valve control

The problem of transient stability for a single machine infinite bus system with turbine main steam valve control is addressed by means of a novel adaptive backstepping method in this paper. The recursive design procedure of the proposed controller is much simpler than that of the existing controller based on conventional adaptive backstepping method. In the system, the damping coefficient is measured inaccurately, and the reactance of transmission line also contains a few uncertainties. A nonlinear robust controller and parameter updating laws are obtained simultaneously. The system does not need to be linearized, and the closed-loop error system is guaranteed to be asymptotically stable. The design procedure and simulation results demonstrate the effectiveness of the proposed design.     

基于扩展自适应Backstepping设计的TCSC非线性控制的新方法

首先针对一般的参数反馈型非线性系统提出一种扩展自适应Backstepp ing方法.该方法不仅保留系统的非线性特性和对未知参数的实时在线估计,而且突破经典的确定性等价性原理来设计参数估计器和动态反馈控制器.该方法可用于带有TCSC(thyristor controlled series compensation)的单机无穷大系统.仿真结果表明,该方法在系统响应和自适应速度方面优于传统的Backstepp ing方法.     

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.     

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.     

基于系统浸入和流形不变自适应方法的静止无功补偿器非线性鲁棒自适应控制方法

本文提出一种将系统浸入和流形不变(I&I)自适应控制方法与L2-增益抑制鲁棒控制方法相结合的静止无功补偿器(SVC)的非线性鲁棒自适应控制方法.所提方法首先通过参数估计误差和鲁棒控制律的设计,使得所构造的表示参数估计误差函数的流形不变且吸引,从而使参数估计误差在这一流形上收敛于零.然后,通过所设计的可调参数对参数估计误差的收敛性能进行控制,以此来保证参数估计器对不确定参数的自适应估计能力.最后,采用自适应逆推算法推导鲁棒控制律,并通过使不确定外部扰动满足从输入到输出的耗散性来保证系统对不确定扰动的鲁棒性.仿真结果表明,利用所提方法设计的SVC控制器和参数替换律在参数估计、发电机功角动态响应方面优于传统自适应逆推算法,从而提高了输电系统的稳定水平.     

Adaptive fuzzy backstepping control of three-phase active power filter

A backstepping controller (BC) and an adaptive fuzzy backstepping controller (AFBC) are proposed for three-phase active power filter (APF) in this paper. Firstly, the dynamic model for APF is build in which both the system parameter variations and external disturbance are considered. Then, the backstepping method is applied in the design of current control system to deal with the nonlinearity of APF. Moreover, the AFBC is developed by combining the backstepping approach with adaptive fuzzy strategy to attenuate the effect of parameter uncertainties and external disturbances. Fuzzy logic system is designed to estimate the unknown nonlinear function in the AFBC where the parameters are adjusted online by the adaptive law derived from the Lyapunov stability analysis to guarantee the tracking performance and stability of the closed-loop system. Simulation studies using the MATLAB/SimPower Systems Toolbox demonstrate that the proposed control strategies exhibit excellent performance in both steady state and transient operation.     

具有参数不确定性的轮式移动机器人自适应backstepping控制

针对参数不确定的轮式移动机器人的轨迹跟踪问题,设计自适应跟踪控制器.基于移动机器人的动力学模型,采用backstepping积分方法,通过逐步递推选择适当的Lyapunov函数,设计基于状态反馈的自适应控制器,并进行了相应的稳定性分析.与传统PID控制进行仿真对比,结果表明提出的自适应控制策略能较好地补偿系统参数摄动的影响,提高了移动机器人的轨迹跟踪性能和鲁棒性.     

自适应反推神经网络的转台鲁棒控制器设计

针对未知非线性、外界干扰和参数摄动等不确定因素对实际转台控制系统的影响,提出了自适应反推神经网络的转台鲁棒控制器设计.首先给出自适应Backstepping控制器的设计方法及步骤,接着采用RBF神经网络对转台对象参数的不确定因素上界值加以辨识,实现转台系统的鲁棒控制.其中Backstepping鲁棒控制作为主控制器,RBF神经网络实现了不确定上界值的在线辨识.仿真结果表明,自适应Backstepping神经网络控制很好地克服了对象的不确定性,实现控制系统的较强鲁棒性,适于高精度飞行仿真转台系统的实时鲁棒控制.     

NONLINEAR ROBUST CONTROL FOR PARALLEL AC/DC TRANSMISSION SYSTEMS: A NEW ADAPTIVE BACK-STEPPING APPROACH

ABSTRACT

By utilizing the controllability of High Voltage Direct Current (HVDC), which means that the power delivered can be modulated, to improve the stability and operation performances of the parallel AC/DC transmission system, a new adaptive back-stepping approach for this system is developed. Compared with the existing controller based on “classical” adaptive back-stepping, the approach does not follow the classical certainty-equivalence principle. We introduce this approach, for the first time, into parallel AC/DC systems containing unknown parameters and present a novel parameter estimator and dynamics feedback controller. Besides the preserving useful nonlinearities and the real-time estimation of uncertainty parameter, the proposed approach possesses better performances with respect to the response of the system and the speed of adaptation. Simulation results demonstrate that the proposed approach is better than the design based on “classical” adaptive back-stepping in terms of properties of stability and parameter estimation and that it recovers the performance of the “full-information” controller, which is obtained by assuming that the parameters are known and apply standard back-stepping, hence it will be an alternative to practice engineering and applications.     

TCSC控制的一种新自适应Backstepping方法

针对带有TCSC（Thyristor Controlled Series Compensator）的单机无穷大电力系统,提出一种新的TCSC自适应非线性控制Backstepping方法．该方法不仅保留了系统的非线性特性和对未知参数的实时在线估计,而且突破了经典的确定性等价性原理来设计参数估计器和动态反馈控制器．仿真结果表明,与基于传统自适应Backstepping得到的控制设计相比较,这种新方法在系统响应和自适应速度方面具有更优越的性能,从而为工程应用提供了一种有效的选择．     

带有灰色补偿的Backstepping控制

针对一类二阶非线性不确定系统提出了一种新的控制方法,即带有灰色补偿的Backstepping控制,该方法分为两个阶段进行.第一阶段采用Backstepping控制方法进行控制,对不确定部分的模型参数进行估计.第二阶段经过N步参数估计之后,在上述控制律基础上,按估计参数加上补偿控制,构成带有灰色补偿的Baekstepping控制.该方法解决了非线性不确定系统的Backstepping控制问题.该方法不仅能精确估计出系统的不确定参数,而且经过补偿的控制器使系统的性能大为改善,并增强了系统的鲁棒性.仿真结果表明了该方法的有效性.     

Model-Reference Fuzzy Adaptive Control as a Framework for Nonlinear System Control

The paper presents a general methodology of adaptive control based on fuzzy model to deal with unknown plants. The problem of parameter estimation is solved using a direct approach, i.e. the controller parameters are adapted without explicitly estimating plant parameters. Thus, very simple adaptive and control laws are obtained using Lyapunov stability criterion. The generality of the approach is substantiated by 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 control parameters. The proposed control algorithm may be viewed as an extension of classical adaptive control for linear plants, but compared to the latter it provides higher adaptation ability and consequently better performance if the plant is nonlinear. The global stability of the control system is assured and the tracking error converges to the residual set that depends on fuzzification properties. The main advantage of the approach is simplicity that suits control engineers since wide range of industrial processes can be controlled by the proposed method. In the paper, the control of heat exchanger is performed.     

汽轮发电机主汽门开度非线性鲁棒控制

由于外界干扰以及各种故障的影响, 电力系统的结构并不是不变的, 因此其中的一些重要参数, 如输电线路电抗等, 总是包含某种不确定性. 针对含有参数不确定性的汽轮机调速系统, 使用自适应逆推方法及Lyapunov方法设计了非线性鲁棒汽门控制器, 基于该方法的设计, 设计过程系统、简明, 且不必对原系统进行线性化, 通过对单机无穷大系统的仿真表明了该控制器的有效性.     

倒立摆的自适应积分反步控制策略

针对直线单级倒立摆在模型参数不确定和外部扰动情况下的稳定控制问题,提出一种自适应积分反步控制策略。采用拉格朗日方程建立倒立摆系统的运动学模型,为减少稳态误差,将误差积分项引入反步法,设计了倒立摆的控制器;对含有未知参数的系统非线性状态微分方程,设计适当的Lyapunov函数推导出系统未知参数的自适应更新律,削弱了参数不确定性的影响。将自适应积分反步控制与一般的反步法控制、模糊控制及神经网络控制的仿真结果进行了对比,并在LabVIEW开发环境下进行了实物实验。结果表明,自适应积分反步法可以较为迅速且精确地完成稳定控制,较好地克服系统参数不确定及外部扰动的影响,具有较强的鲁棒性。     

Adaptive backstepping sliding mode control with tuning functions for nonlinear uncertain systems

An adaptive backstepping tuning functions sliding mode controller is proposed for a class of strict-feedback nonlinear uncertain systems. In this control design, adaptive backstepping is used to deal with unknown or uncertain parameters and the matching condition restricting the Lyapunov based design. The main drawback of the Lyapunov based adaptive backstepping which is the overparametrisation is eliminated by the tuning functions. The adaptive backstepping tuning functions design is combined with the sliding mode control in order to overcome quickly varying parametric and unstructured uncertainties, and to obtain chattering free control. The proposed controller not only provides robustness property against uncertainty but also copes with the overparametrisation problem. Experimental results of the proposed controller are compared with those of the standard sliding mode controller. The proposed controller exhibits satisfactory transient performance, good estimates of the uncertain parameters, and less chattering.     

Adaptive backstepping‐based control design for uncertain nonlinear active suspension system with input delay

This paper addresses the control problem of adaptive backstepping control for a class of nonlinear active suspension systems considering the model uncertainties and actuator input delays and presents a novel adaptive backstepping‐based controller design method. Based on the established nonlinear active suspension model, a projector operator–based adaptive control law is first developed to estimate the uncertain sprung‐mass online, and then the desirable controller design and stability analysis are conducted by combining backstepping technique and Lyapunov stability theory, which can not only deal with the actuator input delay but also achieve better dynamics performances and safety constraints requirements of the closed‐loop control system. Furthermore, the relationship between the input delay and the state variables of this vehicle suspension system is derived to present a simple and effective method of calculating the critical input delay. Finally, a numerical simulation investigation is provided to illustrate the effectiveness of the proposed controller.     

双电机驱动伺服系统的反推自适应控制

针对存在未知齿隙等非线性的双电机驱动伺服系统的控制问题,给出了双电机驱动伺服系统的模型,应用反推控制方法,引入虚拟控制量的概念,通过逐步递推选择Lyapunov函数,在不用知道系统内部不确定性参数的前提下,设计了基于状态反馈的自适应控制器,并进行了稳定性分析.通过与常规PID控制的仿真结果比较,表明提出的控制策略提高了系统的位置跟踪性能和鲁棒性.最后在实际系统中进行实验,结果表明所提出的控制策略是有效的.     

非匹配不确定非线性系统的自适应反演滑模控制

针对一类具有非匹配不确定性的最小相位仿射非线性系统,研究其在未知扰动作用下的调节问题。基于自适应反演设计方法和变结构控制设计了控制方案,实现不确定系统的鲁棒调节。与经典反演设计相比,本方案允许非参数化不确定性,增强了控制系统的鲁棒性。     

Indirect adaptive robust control of nonlinear systems with time‐varying parameters in a strict feedback form

Without any prior knowledge of the physical bounds of unknown parameters and uncertain nonlinearities, an indirect adaptive robust controller is constructed for uncertain nonlinear time‐varying systems in a strict‐feedback form. Firstly, an adaptive strong robust controller is derived based on the command filtered adaptive backstepping approach. This controller not only can guarantee the boundedness of the closed‐loop system signals in the presence of time‐varying (TV) parameters and uncertain nonlinearities but also obviate the need to compute analytic derivatives of virtual control functions. Thus, the problem of “explosion of terms” in the standard adaptive backstepping technique is avoided. Through introduction of a simple adaptation law on the upper bound of uncertainties, a smooth robust control term is used to realize the disturbance attenuation. Afterwards, based on the nonlinear X‐swapping techniques, a modular approach in which the controller and the identifier can be designed separately is exploited. A novel algorithm is proposed to estimate the TV parameters accurately. By adopting the variation trend of the covariance matrix as an indicator of the driving signals' persistent excitation level, this online parameter estimation law is switched between a modified least‐squares algorithm and a gradient algorithm based on fixed σ‐modification. Finally, a series of properties on the asymptotic stability and the global uniform ultimate boundedness of the closed‐loop system is established. Simulation results verify the effectiveness of the suggested method.     

Nonlinear adaptive control of robotic manipulators - hyperstability approach

A nonlinear model reference adaptive controller based on hyperstability approach, is presented for the control of robot manipulators. Use of hyperstability approach simplifies the stability proof of the adaptive system. The unknown parameters of the system, as well as its variable payload, are estimated on line and are adaptive to their actual values; tending to reduce the system error. In addition, any sudden change in the system parameters or payload is detected by the proposed intelligent controller. Robot path tracking, with unknown parameter values and variable payload, is simulated to show the effectiveness of the proposed adaptive control algorithm. Both system output error and parameter estimation error vanish under the proposed parameter adaptation algorithm.