多模型分层切换车速控制

针对汽车纵向动力学建模存在较大不确定性的问题,设计了一种多模型分层切换车速控制系统。在不同汽车参数和工况下,辨识得到节气门开度到车速的传递函数,并建立不确定模型集合对其进行描述基础上,应用鲁棒控制理论对监督器和鲁棒控制器集合进行设计,实现了多模型分层切换车速控制。实验结果表明,与自适应控制器相比,设计的控制器对参数变化具有更快的调节能力,实现了更加快速准确的控制。     

运输机低空重装空投增益自适应滑模控制

本文针对带有不确定性且不确定性边界未知的低空重装备空投过程控制问题,提出了基于增益自适应全局滑模的飞行控制方法.该方法采用反馈线性化技术对重装空投过程模型进行线性化,解决了空投模型的强非线性问题,在此基础上,设计了切换增益自适应全局滑模控制器,保证了系统在响应全程的鲁棒性,克服了滑模到达阶段系统初始误差对切换增益自适应过程的影响.提出了一种改进的增益自适应方法,解决了滑动阶段的切换增益过度自适应问题.基于Lyapunov理论证明了控制器的稳定性和鲁棒性.仿真验证了控制方法的控制性能和优越性.     

四旋翼飞行器的轨迹跟踪抗干扰控制

针对四旋翼飞行器轨迹跟踪问题中系统存在模型不确定和易受到外界扰动的情况,提出了基于切换函数的扩张状态观测器设计方法来对系统中的扰动进行估计,并将估计值与滑模控制器的设计相结合,实现了对系统中非匹配不确定性和匹配不确定性的抑制且实现了系统跟踪误差的一致最终有界.首先,根据变量间的耦合关系将飞行器系统模型分解为两个子系统模型,设计扩张状态观测器对子系统中的非匹配不确定性进行估计,并将估计值作为变量加入到切换函数的设计中;进而基于切换函数设计扩张状态观测器以估计经切换函数重构系统中的扰动,并在控制器中对扰动进行补偿.最后通过李雅普诺夫理论证明了控制系统的稳定性.通过仿真验证了本文提出的方法能够有效实现飞行器轨迹跟踪控制且能够抑止传统滑模控制的抖振现象.     

显式抑制测量误差的改进滑模控制

反馈控制系统中模型不确定性和测量误差的同时出现, 给高精度控制器的设计带来挑战. 经典滑模控制能抵抗一定程度的模型不确定性和输入干扰, 但引入的高增益使得其性能对测量噪声极为敏感, 也容易引起系统强烈抖振. 为此, 本文针对一种典型的角度和角速率测量分别包含高频和低频测量误差条件, 提出了一种改进的基于趋近律的角度跟踪控制方案. 本方案采用低通滤波器来应对高频测量噪声, 同时采用一种新颖的基于模型的测量误差估计器, 来补偿低频测量漂移. 采用Quanser Aero平台进行两自由度角轨迹跟踪控制仿真和实验验证, 并与自抗扰控制等几种典型鲁棒控制方案进行了全面对比, 证实了本文方案性能上的优越性和调参的便捷性.     

含有输入时滞的不确定T-S模糊系统的滑模控制

研究同时包含输入时滞和状态时滞的不确定T-S模糊系统的滑模控制问题,其中非线性不确定项是未知的,并且不满足匹配条件.针对被控对象的T-S模糊模型,设计一种基于积分型切换面的滑模控制器,并利用线性矩阵不等式技术和李亚普诺夫稳定性理论,给出滑模动态渐近稳定的充分条件,设计滑模控制律使系统状态保持在切换面上.仿真结果表明,该方法能有效消除非线性不确定性和输入时滞给系统带来的影响.     

不确定性机器人的鲁棒控制

本文研究不确定性刚性机器人的鲁棒控制问题，提出了一种新的鲁棒控制方案，控制器由两部分组成：第一部分为基于标称模型设计的计算力矩控制器；第二部分为基于Ｌｙａｐｕｎｏｖ方法设计的鲁棒补偿控制器，其作用是消除不确定性对跟踪性能的影响。本文证明了闭环系统的全局收敛性，仿真结果表明本方法对于存在外扰和模型不确定性的机器人系统是十分有效的。     

磁耦合谐振无线电能传输系统的输出鲁棒控制

磁耦合谐振无线电能传输系统的负载和谐振参数会因为受到外界环境的影响而发生变化, 系统工作频率发生随机漂移, 导致模型参数存在不确定性. 针对参数不确定下的输出鲁棒控制问题, 本文基于H_∞控制理论, 应用Matlab鲁棒控制工具箱设计H_∞控制器, 并基于结构奇异值法分析了闭环系统的鲁棒稳定性与鲁棒性能. 结果表明, 在H_∞控制器的作用下, 实现了闭环摄动系统的输出鲁棒控制, 并为此类高阶非线性不确定闭环系统提供了一种通用的控制器设计方法.     

多电机驱动系统的保性能鲁棒Funnel控制

本文针对含参数不确定性的多电机驱动系统,提出一种基于最优保性能鲁棒的Funnel控制方法实现系统的规定跟踪性能.该控制方法通过构造Funnel函数对误差系统进行变换,并设计自适应反步控制器保证变换后系统的稳定性即可使跟踪误差的瞬态和稳态响应均被限制在给定的Funnel边界内.然而由于系统中存在的参数不确定性会影响系统的规定控制性能,本文在Funnel控制基础上又设计了最优保性能鲁棒控制器.它是通过将参数不确定性系统的保性能鲁棒控制问题转化为标称系统的最优控制问题,并求解新的黎卡提方程而得到的.因此所设计的控制器不但消除了参数不确定性对系统的影响并且能够使系统的性能指标达到一确定的上界.最后,对四电机驱动系统进行了仿真和实验验证,说明所提出控制方法的有效性.     

高超声速飞行器非线性鲁棒控制律设计

高超声速飞行器具有模型非线性程度高、耦合程度强、参数不确定性大、抗干扰能力弱等特点,其自主控制具有较大的挑战.论文提出了一种基于鲁棒补偿技术和反馈线性化方法的非线性鲁棒控制方法.文中首先采用反馈线性化的方法对纵向模型进行输入输出线性化,实现速度和高度通道的解耦和非线性模型的线性化.针对得到的线性模型,设计包括标称控制器和鲁棒补偿器的线性控制器.基于极点配置原理,设计标称控制器使标称线性系统具有期望的输入输出特性,利用鲁棒补偿器来抑制参数不确定性和外界扰动对于闭环控制系统的影响.基于小增益定理,证明了闭环控制系统的鲁棒稳定性和鲁棒跟踪性能.相比于非线性回路成形控制方法,仿真结果表明了所设计非线性鲁棒控制算法的有效性和优越性.     

不确定LTI-SISO系统的低通滤波时滞观测器控制

合理利用时滞可能获得意想不到的性能.研究表明,系统的不确定性以及受到的外部 干扰可以利用时滞观测器来进行观测,从而实现系统的鲁棒控制.本文提出了一种低通滤波时 滞观测器.避免了常规时滞观测器控制中出现的控制信号颤振,得到了一种结构新颖的控制器. 仿真结果表明时滞观测器控制系统可以很好地抑制系统的不确定性以及受到的外部干扰,是一 种性能优良的鲁棒控制方法.     

基于鲁棒控制理论的多模型分层切换控制

A new hierarchical switching control system of multiple models based on robust control theory is designed for some plant with large uncertainties. The model set and controller set are designed by robust control theory and the characteristics of robust control system are taken into account. A new kind of switching index function by estimating uncertainty is designed. Furthermore,stability of the closed system is analyzed by the small gain theorem in the sense of exponentially weighted L2 norm. And simulation is done on a plant with both parameter uncertainty and unmodeled dynamics. Both theoretical analysis and simulation results show that this new hierarchical switching control system can control the plant with large uncertainties effectively and has good performance of tracking and stability.     

Adaptive sensorless robust control of AC drives based on sliding mode control theory

This paper focuses in the design of a new adaptive sensorless robust control to improve the trajectory tracking performance of induction motors. The proposed design employs the so‐called vector (or field oriented) control theory for the induction motor drives, being the designed control law based on an integral sliding‐mode algorithm that overcomes the system uncertainties. This sliding‐mode control law incorporates an adaptive switching gain in order to avoid the need of calculating an upper limit for the system uncertainties. The proposed design also includes a new method in order to estimate the rotor speed. In this method, the rotor speed estimation error is presented as a first‐order simple function based on the difference between the real stator currents and the estimated stator currents. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. The simulated results show, on the one hand that the proposed controller with the proposed rotor speed estimator provides high‐performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external load disturbances. Finally, experimental results show the performance of the proposed control scheme. Copyright © 2006 John Wiley & Sons, Ltd.     

NCS系统中二自由度内模控制器的优化设计

针对网络化控制系统中网络时滞与对象模型不确定性,提出了一种二自由度内模控制器的优化设计方法。该控制器能够实现设定值跟踪与扰动抑制过程解耦,同时在对象模型失配情况下,系统具有较强的鲁棒稳定性。对于控制器的参数采用了混沌算法进行优化,以直线伺服系统为对象的仿真实验证实了此方法的可行性。     

An H∞ suboptimal robust control approach for systems with uncertainties and data dropouts

This paper studies the design of control systems subject to plant uncertainties and data losses in the channel connecting the plant sensor with the controller. The controller design has two main objectives. The first one is to robustify the control law against plant uncertainties. The other one is to achieve good performance by minimising the variance of the error signal. Data losses are modelled as an independent and identically distributed sequence of Bernoulli random variables. For analysis and design, this random variable is replaced by an additive noise plus gain channel model. To cope with structural uncertainties in the model of the plant, an H_∞ control technique is employed. The controller is synthesised in order to make the closed-loop system robust against structural uncertainties of the nominal model, while achieving optimal performance of the system in the presence of dropouts.     

A nonparametric approach to design robust controllers for uncertain systems: Application to an air flow heating system

This paper presents an approach to design robust fixed structure controllers for uncertain systems using a finite set of measurements in the frequency domain. In traditional control system design, usually, based on measurements, a model of the plant, which is only an approximation of the physical system, is first built, and then control approaches are used to design a controller based on the identified model. Errors associated with the identification process as well as the inevitable uncertainties associated with plant parameter variations, external disturbances, measurement noise, etc. are expected to all contribute to the degradation of the performance of such a scheme. In this paper, we propose a nonparametric method that uses frequency-domain data to directly design a robust controller, for a class of uncertainties, without the need for model identification. The proposed technique, which is based on interval analysis, allows us to take into account the plant uncertainties during the controller synthesis itself. The technique relies on computing the controller parameters for which the set of all possible frequency responses of the closed-loop system are included in the envelope of a desired frequency response. Such an inclusion problem can be solved using interval techniques. The main advantages of the proposed approach are: (1) the control design does not require any mathematical model, (2) the controller is robust with respect to plant uncertainties, and (3) the controller structure can be chosen a priori, which allows us to select low-order controllers. To illustrate the proposed method and demonstrate its efficacy, an application to an air flow heating system is presented.     

Robust distributed model predictive control of linear systems with structured time-varying uncertainties

In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min–max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.     

不确定系统鲁棒自适应离散变结构控制

研究不确定系统的离散变结构控制设计问题.对离散趋近律方法进行分析, 提出一种基于鲁棒趋近律的自适应切换增益算法,能根据不确定因素对系统影响的强弱自动调整增益大小. 给出了闭环系统的鲁棒稳定性证明,并对其准滑模运动进行分析.理论分析与仿真研究结果均表明, 所提方法能有效减弱抖振,较好地改善离散变结构控制器的性能, 并解除了传统上确界方法要求不确定因素上确界可知的限制.