一类时变系统中补偿器的功能和设计

PID控制器由于其结构简单和参数整定容易,具有良好的控制功能,被广泛应用在工程上的线性确定性系统中.但是,在非线性系统和不确定性系统中, PID控制器由于其固定的控制参数和结构限制,很难克服系统中内外干扰的影响,控制器鲁棒性能较差.本文按照被控对象中的标称模型设计常规PID控制器优化参数,对非线性系统中多个线性化模型和不确定性系统中的不同工作点模型,设计了一类补偿器,使得整个闭环系统具有与标称模型下相同的控制品质.工程应用例子论证了本文提出的补偿器能提高不确定与非线性系统的控制品质和鲁棒性能.     

一类非线性时变系统的鲁棒输出跟踪控制

研究一类具有非匹配不确定性的非线性时变系统的鲁棒状态反馈输出跟踪控制器设计问题。通过引入非线性时变系统的相对阶将系统输入输出线性化,然后设计出一种基于标称系统和不确定性上界的连接型鲁棒输出跟踪控制器,利用该方案设计的控制器可保证整个闭环系统是一致有界稳定的,且闭环输出可以渐近跟踪期望的轨迹。     

基于光流的四旋翼直升机鲁棒自主着陆控制

针对小型四旋翼无人机自主着陆问题,提出了一种基于光流的高度估计方法和基于信号补偿的高度鲁棒控制器设计方法.首先从通用光流运动模型出发,采用奇异值分解方法求解无人机线速度和深度的比值,通过对垂直速度和高度比值积分获得高度数据.其次,将考虑地效影响和其它不确定性的高度通道非线性模型分解为标称线性模型和等效扰动两部分,并设计基于信号补偿的高度鲁棒控制器,该控制器由标称控制器和鲁棒补偿器组成,其中标称控制器使得标称闭环系统达到期望的高度跟踪特性,鲁棒补偿器用于抑制等效扰动的影响.最后从理论上证明了该控制器可以保证高度跟踪误差在有限时间内收敛至指定的原点邻域内.四旋翼无人机自主着陆的实验结果验证了所提出的基于光流的高度估计和鲁棒控制方法的有效性.     

参数不确定机器人分散鲁棒跟踪控制

提出了一种新的参数不确定机器人分散控制器设计方法．首先将关节子系统的动力学模型分解为人工标称模型和非线性时变不确定模型两部分；然后分别设计相应的标称控制器和鲁棒补偿器．标称控制器使得标称闭环系统具有理想的跟踪性能；鲁棒补偿器可以抑制参数不确定和关节间非线性耦合等因素的影响，实现鲁棒跟踪．所设计的控制器只需要局部关节的位置反馈，具有易于实现和可在线调整的优点．仿真结果说明了该方法的有效性．     

机器人鲁棒控制器参数演化设计

论文将讨论具有控制输入幅值限制的机器人轨迹跟踪控制问题。将利用基于信号补偿的鲁棒控制方法设计机器人的子关节系统控制器。该控制器由标称控制器和鲁棒补偿器组成。标称控制器对于一标称受控对象实现所希望的轨迹跟踪特性,鲁棒补偿器则用于减小实际受控对象和标称受控对象之间的差异对跟踪特性的影响。当输入存在饱和约束的情况下,对鲁棒补偿器进行了修改,并且基于演化寻优的方法求取鲁棒补偿器参数。     

基于反馈线性化系统的非线性鲁棒控制μ方法

对于可状态反馈线性化的一类仿射非线性系统，本文提出一种非线性鲁棒控制的μ方法。首先给出非线性鲁棒控制问题，然后利用状态反馈线性化方法，把非线性系统线性化，并利用μ综合方法，对线性化系统进行鲁棒控制器的设计，最后通过回代构成非线性鲁棒控制系统。     

具有输入齿隙的一类非线性不确定系统自适应鲁棒控制

针对一类具有未知输入齿隙、参数不确定以及未建模动态和干扰的非线性系统,设计了自适应鲁棒控制器.将齿隙非线性模型等价表示为具有有界建模误差的全局线性化模型,在此基础上设计了包含自适应模型补偿、反馈稳定和鲁棒反馈3部分的自适应鲁棒控制器,并给出了系统动态跟踪误差和稳态误差指标.理论分析证明,闭环控制系统信号有界且跟踪误差在任意期望的精度范围内,仿真研究验证了所提出方法的有效性.     

基于状态变换的非线性鲁棒控制器设计

本文对具有特定结构的非线性系统,介绍了一种非线性变换使之线性化,并利用线性鲁棒 控制器的设计方法设计非线性鲁棒控制器,从而提高了闭环系统对参数变动的鲁棒性.文中 还通过一个CSTR反应器模型的仿真说明该方法的有效性.     

交直流并联输电系统的非线性鲁棒控制

针对含有常参数不确定性的交直流输电系统,使用自适应逆推方法设计了直流系统的非线性鲁棒控制器.基于该方法的设计,无需对原系统进行反馈线性化,并能保证闭环误差系统渐近稳定.设计过程表明逆推方法设计的控制器拥有更优越的性能.     

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.     

Robust attitude tracking control of small-scale unmanned helicopter

Robust attitude control problem for small-scale unmanned helicopters is investigated to improve attitude control performances of roll and pitch channels under both small and large amplitude manoeuvre flight conditions. The model of the roll or pitch angular dynamics is regarded as a nominal single-input single-output linear system with equivalent disturbances which contain nonlinear uncertainties, coupling-effects, parameter perturbations, and external disturbances. Based on the signal compensation method, a robust controller is designed with two parts: a proportional-derivative controller and a robust compensator. The designed controller is linear and time-invariant, so it can be easily realised. The robust properties of the closed-loop system are proven. According to the ADS-33E-PRF military rotorcraft standard, the controller can achieve top control performances. Experimental results demonstrate the effectiveness of the proposed control strategy.     

Robust backstepping output tracking control for SISO uncertain nonlinear systems with unknown virtual control coefficients

The output tracking controller design problem is dealt with for a class of nonlinear strict-feedback form systems in the presence of nonlinear uncertainties, external disturbance, unmodelled dynamics and unknown time-varying virtual control coefficients. A new method based on signal compensation is proposed to design a linear time-invariant robust controller, which consists of a nominal controller and a robust compensator. It is shown that the closed-loop control system with a controller designed by the proposed method has robust asymptotical practical tracking property for any bounded initial conditions and robust tracking transient property if all initial states are zero.     

Robust Control System Design for an Uncertain Nonlinear System Using Minimax LQG Design Method

A systematic approach to design a nonlinear controller using minimax linear quadratic Gaussian regulator (LQG) control is proposed for a class of multi‐input multi‐output nonlinear uncertain systems. In this approach, a robust feedback linearization method and a notion of uncertain diffeomorphism are used to obtain an uncertain linearized model for the corresponding uncertain nonlinear system. A robust minimax LQG controller is then proposed for reference command tracking and stabilization of the nonlinear system in the presence of uncertain parameters. The uncertainties are assumed to satisfy a certain integral quadratic constraint condition. In this method, conventional feedback linearization is used to cancel nominal nonlinear terms and the uncertain nonlinear terms are linearized in a robust way. To demonstrate the effectiveness of the proposed approach, a minimax LQG‐based robust controller is designed for a nonlinear uncertain model of an air‐breathing hypersonic flight vehicle (AHFV) with flexibility and input coupling. Here, the problem of constructing a guaranteed cost controller which minimizes a guaranteed cost bound has been considered and the tracking of velocity and altitude is achieved under inertial and aerodynamic uncertainties.     

Robust Output Feedback Consensus of High-order Multi-agent Systems with Nonlinear Uncertainties

In this paper, the output feedback consensus problem of high-order multi-agent systems with nonlinear uncertainties is researched by the robust control method. By the dimensional extension of the observation matrix, the consensus control problem is transformed into a stability problem. Then the robust controller is designed by combining the nominal controller and the robust compensator. The nominal controller can obtain desired nominal performance based on the output informations. The robust compensator, which relys on robust signal compensation technology, is order to suppress the nonlinear uncertainties. According to the proposed method, output consensus error can be guaranteed as small as desired. Finally, simulation results are given to illustrate the effectiveness of this control method.     

Robust nonlinear control associating robust feedback linearization and H/sub /spl infin// control

In this note, a robust nonlinear controller for a nonlinear system subject to model uncertainties is proposed. Such a controller associates a "robust feedback linearization" with a robust linear H/sub /spl infin// controller. The robust feedback linearization exactly transforms the nonlinear system into a linear system equal to the linear approximation of the original nonlinear system around a nominal operating point. The robustness of the resulting overall nonlinear controller is proved by theoretical arguments and illustrated through an application example, the control of a magnetic bearing system.     

Robust Stable Fuzzy Control via Fuzzy Modeling and Feedback Linearization with Its Applications to Controlling Uncertain Single-link Flexible Joint Manipulators

In this paper, a robust stable fuzzy control design based on feedback linearization is presented. Takagi–Sugeno fuzzy model is used as representing the nonlinear plant model and uncertainty is assumed to be included in the model structure with known bounds. For this structured uncertainty, the closed system can be analyzed by applying the perturbation system stability analysis to the fuzzy feedback linearization systems and a sufficient condition is derived to guarantee the stability of the closed-loop system with bounded parameter uncertainties. Based on the developed analysis method, we can design a robust fuzzy controller by choosing the control parameters satisfying the robust stability condition.     

Uncertainty modeling and robust minimax LQR control of multivariable nonlinear systems with application to hypersonic flight

For a class of multi‐input and multi‐output nonlinear uncertainty systems, a novel approach to design a nonlinear controller using minimax linear quadratic regulator (LQR) control is proposed. The proposed method combines a feedback linearization method with the robust minimax LQR approach in the presence of time‐varying uncertain parameters. The uncertainties, which are assumed to satisfy a certain integral quadratic constraint condition, do not necessarily satisfy a generalized matching condition. The procedure consists of feedback linearization of the nominal model and linearization of the remaining nonlinear uncertain terms with respect to each individual uncertainty at a local operating point. This two‐stage linearization process, followed by a robust minimax LQR control design, provides a robustly stable closed loop system. To demonstrate the effectiveness of the proposed approach, an application study is provided for a flight control problem of an air‐breathing hypersonic flight vehicle (AHFV), where the outputs to be controlled are the longitudinal velocity and altitude, and the control variables are the throttle setting and elevator deflection. The proposed method is used to derive a linearized uncertainty model for the longitudinal motion dynamics of the AHFV first, and then a robust minimax LQR controller is designed, which is based on this uncertainty model. The controller is synthesized considering seven uncertain aerodynamic and inertial parameters. The stability and performance of the synthesized controller is evaluated numerically via single scenario simulations for particular cruise conditions as well as a Monte‐Carlo type simulation based on numerous cases. It is observed that the control scheme proposed in this paper performs better, especially from the aspect of robustness to large ranges of uncertainties, than some controller design schemes previously published in the literature. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Robust output containment control of multi-agent systems with unknown heterogeneous nonlinear uncertainties in directed networks

Output containment problem for high-order nonlinear time-invariant multi-agent systems in directed networks is investigated in this paper. The output is related with the observation matrix. The dimensions of observation matrix are extended so that it is non-singular. Then the containment problem is transformed into stability problem. The model of each agent is constructed by a nominal system combined with uncertainties. A robust controller, which includes a nominal controller and a robust compensator, is proposed to achieve output containment and restrain external uncertainties. The nominal controller is based on the output feedback and the nominal system constructed by the nominal controller contains desired containment properties. The robust compensator design is based on robust signal compensation technology for restraining the effects of external disturbances. A sufficient condition on the output containment is proposed and the containment errors can be made as small as desired with the expected convergence rate. Finally, numerical simulation is presented to demonstrate the effectiveness of the control method.