电液伺服系统的非线性鲁棒自适应控制

摘要：针对电液伺服非线性系统的参数不确定性以及模型不确定项，基于Lyapunov稳定方法，提出了一种适用于电液伺服系统的非线性鲁棒自适应控制策略。首先以跟踪误差为基础给出系统目标控制函数的定义方法，然后基于Lyapunov稳定性分析方法，给出了不确定参数的自适应律， 以及自适应控制器的设计。同时引入一种简单的鲁棒设计方法补偿系统的模型不确定项。该方法具有结构简单，鲁棒性强的特点，并且系统控制量平稳，无振动现象出现。仿真结果显示，采用该控制方法可取得良好的控制效果，并进一步证实了理论分析的正确性。     

高压直流输电系统换流站鲁棒自适应输出反馈控制

针对高压直流输电系统,设计了一种鲁棒自适应输出反馈控制器.首先,将高压直流输电系统换流站动态模型转换成用输入输出表示的非线性系统.然后,利用自适应非线性阻尼项来抑制系统的非线性动态不确定性和未知有界扰动,应用Lyapunov稳定性理论构造出控制器和自适应参数的表达式.Lyapunov稳定性分析结果表明,文中所提出的控制器保证了闭环系统的稳定性.最后,将设计的控制器应用到一个3机直流输电系统中,仿真结果表明,与传统的PI控制器相比较,文中控制器可大大提高系统的稳定性和鲁棒性.     

高压直流换流站分散鲁棒自适应控制器的设计

针对高压直流输电系统（HVDC），提出了一种换流站的分散鲁棒自适应控制器的设计方法，设计中引入自适应非线性阻尼项来抑制系统非线性不确定参数和未知有界干扰的影响，同时采用反演设计方法来克服控制器设计的复杂性，最后获得高压直流输电系统换流站的分散鲁棒自适应控制策略的一般表达式，并提供了整个系统的稳定性证明，所得控制器仅利用本地测量量实现，控制策略具有分散性和适应性，通过NETOMAC数字仿真，仿真结果证明该控制器比常规的PI控制器具有更好的控制效果。     

具有电枢反应非线性不确定性的直流电机速度鲁棒跟踪控制研究

该文针对电枢反应引起的非线性不确定性及具有参数变化和负载扰动的直流电机速度跟踪控制问题，构造了一个适当的增广被控对象，将其转化为一标准设计问题，设计了速度控制系统的鲁棒状态反馈控制器，进而利用二自由度鲁棒跟踪设计方法设计了速度鲁棒跟踪控制器。仿真研究结果表明，该文所设计的速度鲁棒跟踪控制系统，不仅对于电机的非线性不确定性有较好的控制效果，而且可以有效地抑制电机负载扰动的影响。     

低频线振动台系统的鲁棒自适应重复学习控制

由于没有传动机构,永磁直线同步电机(PMLSM)作为低频线振动台的驱动部件对扰动和参数不确定性很敏感,摩擦力及纹波推力扰动等非线性因素严重影响了PMLSM的运动精确度.针对上述问题,提出一种鲁棒自适应重复学习控制方法,用于提高低频线振动台系统的精度.所设计的控制律由参数自适应控制、积分滑模控制、重复学习控制组成.参数自适应控制用来估计未知的模型参数并予以补偿;积分滑模控制用来镇定低频线振动台系统,抑制非周期扰动;重复学习控制用来抑制周期性扰动,提高对周期性位置信号的跟踪性能.采用Lyapunov理论设计的鲁棒自适应重复学习控制律能够保证闭环系统的渐近稳定性和位置跟踪性能.仿真结果表明,鲁棒自适应重复学习控制方法明显提高了系统的跟踪性能,改善了加速度失真度.     

永磁直线伺服系统非线性自适应鲁棒控制器设计

对永磁直线伺服系统提出非线性自适应鲁棒控制器的设计方法。在永磁直线伺服系统非线性数学模型的基础上,为实现对速度和电流的准确跟踪,建立了误差系统的动态模型。将跟踪和干扰抑制归结为非线性自适应鲁棒控制器设计问题,通过构造存储函数得到包含电阻辨识算法的自适应鲁棒控制器的定理,证明定理给出的控制器能满足干扰抑制和系统的渐进稳定。仿真结果表明,用该方法设计的系统能很好的抑制扰动和跟踪给定,满足对高性能永磁直线伺服系统控制的要求。     

STATCOM鲁棒非线性控制

讨论了STATCOM的鲁棒非线性控制设计问题。利用直接反馈线性化技术（DFL）把STATCOM非线性模型转换成线性模型,并利用鲁棒控制器的设计方法消除模型中不确定参数的影响。设计过程中只需要不确定参数的边界,所设计控制器简单、有效,并能保证系统在所有参数范围内的渐进稳定性。3母线电力系统的仿真结果表明该控制器在系统具有不确定参数时能取得良好的电压调节性能。     

一种锅炉系统模型分析及其非线性控制

文中从控制系统设计的角度，对锅炉系统模型进行全面分析，并应用非线性控制方法，解决大范围、全工况、多扰动优化运行。首先分析线性化模型的可控可观性、非最小相位特性、基于相对增益矩阵的耦合性、配对策略和基于相对非线性测度的非线性度等，认为该非线性锅炉模型是控制器设计和控制算法评价的标准问题；然后给出状态反馈线性化设计步骤、控制系统结构和鲁棒稳定性的理论保证；最后，仿真验证该非线性控制策略具有良好的设定值跟踪性能，对外扰和负荷扰动以及参数摄动均具有鲁棒性。     

开关磁阻电机伺服系统的L2增益鲁棒控制方法

通过对开关磁阻电机非线性特性分析,提出了开关磁阻电机(SRM)伺服系统L2鲁棒控制器设计方法.建立速度误差动态方程,结合L2鲁棒控制器理论,通过L2控制器的设计解决了SRM的负载扰动和转速跟踪问题.设计存储函数证明L2控制器实现了扰动抑制和渐进稳定.仿真结果表明,该控制器能够保证系统达到很好的扰动抑制和转速跟踪效果.     

基于结构保留模型的静止无功补偿器鲁棒非线性控制

采用Hamilton函数方法研究了静止无功补偿器(SVC)的鲁棒非线性控制问题。首先基于系统网络结构特点,建立了包含SVC、恒功率负荷和有界外部扰动的电力系统的结构保留不确定非线性控制数学模型,然后通过坐标变换和预置状态反馈控制完成了系统的耗散Hamilton实现。最后,基于该耗散实现设计了鲁棒控制器,并分析了闭环系统的渐近稳定性。由于充分利用了系统的内在耗散结构特性,所设计的鲁棒控制器物理意义明确,易于实现。与常规PID控制器的仿真比较表明,该鲁棒控制器作用下系统的超调量小、响应速度快,能有效抑制外部干扰对系统暂态稳定性的影响,有效提高了系统的动态性能。     

Robust nonlinear control of wind energy conversion systems

This paper presents stability analysis for a class of uncertain nonlinear systems and a method for designing robust fuzzy controllers to stabilize the uncertain nonlinear systems. First, the Takagi–Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the uncertain nonlinear system. Next, new stability conditions for a generalized class of uncertain systems are derived from robust control techniques such Linear Matrix Inequalities (LMIs). The derived stability conditions are used to analyze the stability of Takagi and Sugeno’s fuzzy control systems with uncertainty which can be regarded as a generalized class of uncertain nonlinear systems. The design method employs the so-called Parallel Design Approach (PDA). TS fuzzy systems are classified into three families based on the input matrices and a robust fuzzy controller’s synthesis procedure is given for each family. In each family, sufficient conditions are derived for robust stabilization in the sense of Taylor series stability, for the TS fuzzy system with parametric uncertainties. Important issues for the stability analysis and design are remarked. The effectiveness of the proposed controller design methodology is finally demonstrated through the two different models of Wind Energy Systems (WES) to illustrate the effectiveness of the proposed method.     

一类MIMO非线性系统的直接鲁棒自适应模糊控制

针对一类多输入多输出非线性系统,基于后推设计方法,提出了一种新的直接自适应控制方案。该方案中引入连续鲁棒项对系统的摄动部分直接进行抑制,并在自适应律中利用了Leakage项以防止参数漂移。采用修改的积分型Lyapunov函数,取消了每个子系统高频控制增益一阶导数上界已知的假设。通过理论分析,证明了闭环系统是半全局一致终结有界的,跟踪误差收敛到一个小的残差集内。仿真结果表明了该方法的有效性。     

Adaptive control design for MIMO switched nonlinear systems with full state constraints

This paper presents an adaptive fuzzy control approach of multiple‐input–multiple‐output (MIMO) switched uncertain systems, which involve time‐varying full state constraints (TFSCs) and unknown disturbances. In the design procedure, the fuzzy logic systems are adopted to approximate the unknown functions in the systems. The adaptive fuzzy controller is set up by backstepping technique. According to the tangent barrier Lyapunov function (BLF‐Tan), a novel adaptive MIMO switched nonlinear control algorithm is designed. Under the rule of arbitrary switchings and the proposed control laws, it is demonstrated that all signals in the resulted system are semiglobally uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of zero with TFSCs. Furthermore, the simulation example validates the effectiveness of presented control strategy.     

Adaptive fuzzy backstepping dynamic surface control for a class of MIMO nonlinear systems with input delays and state time‐varying delays

In this paper, an adaptive fuzzy backstepping dynamic surface control (DSC) approach is developed for a class of MIMO nonlinear systems with input delays and state time‐varying delays. The unknown continuous nonlinear functions are expressed as the linearly parameterized form by using the fuzzy logic systems, and then, by combining the backstepping technique, the appropriate Lyapunov–Krasovskii functionals, and the ‘minimal learning parameters’ algorithms with the DSC approach, the adaptive fuzzy tracking controller is designed. Our development is able to eliminate the problem of ‘explosion of complexity’ inherent in the existing backstepping‐based methods. It is proven that the proposed design method can guarantee that all the signals in the closed‐loop system are bounded and the tracking error is smaller than a prescribed error bound. Finally, simulation results are provided to show the effectiveness of the proposed approach. Copyright © 2014 John Wiley & Sons, Ltd.     

一类非线性系统的自组织模糊神经网络控制

针对一类MIMO不确定非线性有干扰且控制增益符号未知的系统进行跟踪控制的问题,提出了一种在线自组织模糊神经网络的改进算法,用以克服参数选择困难的问题,并基于该算法给出了一种自适应鲁棒控制方法。首先基于主导输入的概念将MIMO系统分解为多个SISO系统构成的系统,然后结合自组织模糊神经网络在线对系统中的未知函数进行逼近,对网络结构和参数实现在线调节,再利用Nussbaum函数来克服控制增益符号未知,并且引入鲁棒项及复合误差的估计来补偿复合误差。最后基于Lyapunov稳定性理论证明了整个闭环系统半全局一致最终有界。理论和仿真结果表明提出方法的有效性。     

A combined backstepping and dynamic surface control to adaptive fuzzy state‐feedback control

This paper studies an adaptive fuzzy dynamic surface control for a class of nonlinear systems with fuzzy dead zone, unmodeled dynamics, dynamical disturbances, and unknown control gain functions. The unknown system functions are approximated by the Takagi‐Sugeno–type fuzzy logic systems. There are 3 main features for the presented systematic design scheme. First, by adopting an integrated method, a novel adaptive fuzzy controller is constructed for the nonlinear system with fuzzy dead zone. Second, only 3 online learning parameters need to be tuned, which significantly reduces the computation burden. Third, the possible controller singularity problem in some of the existing adaptive control methods with feedback linearization techniques can be avoided. On the basis of the backstepping technique and dynamic surface control, all the signals of the closed‐loop system are guaranteed to be semiglobally uniformly ultimately bounded. Finally, 2 simulation examples are provided to illustrate the effectiveness of the proposed scheme.     

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.     

Robust fuzzy control and evolutionary fuzzy identification of singularly perturbed nonlinear systems with parameter uncertainty

This paper presents an H _∞ robust fuzzy control strategy which stabilizes singularly perturbed (SP) nonlinear systems with bounded uncertainties and guarantees disturbance attenuation bounds for all admissible uncertainties. The modified Takagi–Sugeno (T–S) fuzzy linear models are used to describe the SP nonlinear systems. By the proposed fuzzy control strategy, the number and type of membership functions in the fuzzy control rules are not necessarily the same as those in the fuzzy models. A sufficient condition for the existence of the H _∞ robust fuzzy controllers is then presented in terms of a novel linear matrix inequalities (LMIs) form which takes full consideration of modeling error and uncertainties in system parameters. This condition provides extra design parameters with more flexibility in control gain selection. Furthermore, we propose a compound search strategy composed of island genetic algorithms concatenated with the simplex method to identify the uncertain SP nonlinear systems for the fuzzy control design, and to solve the LMI problem. Finally, design example of the proposed H _∞ robust fuzzy controller for an uncertain SP nonlinear system is presented.     

基于自适应模糊滑模控制的机器人轨迹跟踪算法

针对控制参数的不确定性以及存在未知外部扰动情况下移动机器人的轨迹跟踪问题,提出一种基于光滑非线性饱和函数的自适应模糊滑模轨迹跟踪控制算法。通过建立不确定非线性移动机器人运动控制模型,利用自适应模糊逻辑系统构建自适应模糊滑模控制器。为了增强轨迹跟踪控制算法对随机不确定外部扰动适应能力的同时削弱滑模控制算法中的输入抖振现象,利用有界输入有界输出(BIBO)稳定的方法,通过带有自适应调节算法的模糊系统对滑模控制律中非线性函数项进行自适应逼近,并设计了模糊系统中可调参数的自适应控制律,保证了控制系统的稳定与收敛。实验结果表明,所设计的控制器对系统参数不确定性和外界扰动均具有较强的轨迹跟踪性能和鲁棒性。与传统的滑模控制算法相比,该算法不仅能有效减小输入抖振而且轨迹跟踪控制精度提高了18.89%。     

Robust adaptive control of nonlinearly parameterized systems with unmodeled dynamics

Many physical systems such as biochemical processes and machines with friction are of nonlinearly parameterized systems with uncertainties. How to control such systems effectively is one of the most challenging problems. This paper presents a robust adaptive controller for a significant class of nonlinearly parameterized systems. The controller can be used in cases where there exist parameter and nonlinear uncertainties, unmodeled dynamics and unknown bounded disturbances. The design of the controller is based on the control Lyapunov function method. A dynamic signal is introduced and adaptive nonlinear damping terms are used to restrain the effects of unmodeled dynamics, nonlinear uncertainties and unknown bounded disturbances. The backstepping procedure is employed to overcome the complexity in the design. With the proposed method, the estimation of the unknown parameters of the system is not required and there is only one adaptive parameter no matter how high the order of the system is and how many unknown parameters there are. It is proved theoretically that the proposed robust adaptive control scheme guarantees the stability of nonlinearly parameterized system. Furthermore, all the states approach the equilibrium in arbitrary precision by choosing some design constants appropriately. Simulation results illustrate the effectiveness of the proposed robust adaptive controller. __________ Translated from Journal of Sichuan University (Engineering Science Edition), 2005, 37(5): 148–153 (in Chinese)