一类不确定离散时间系统的最优鲁棒控制

本文针对一类含有不确定因素的离散单输入系统,采用李雅普诺夫第二种方法设计了一种鲁棒控制器.这个控制器是系统状态的线性函数,并且被证明当矩阵Q给定时,它是最优的.文末给出了仿真例子.     

一类非线性互联大系统的分散镇定

本文研究一类非线性互联大系统的局部分散状态反馈镇定问题。文中将非线性系统的几何方法和分析方法有机地结合起来，用于研究这类非线性互联大系统的分散镇定问题的可解性，并且得到了较弱的充分条件，最后用一个例子对本文的主要结果做进一步的说明。     

一类不确定离散时间系统的鲁棒控制

本文针对一类离散时间不确定多输入系统,采用李雅普诺夫第二方法设计了一种鲁棒的线性状态反馈控制器.分析了控制系统的稳定性,并得出系统稳定的充分条件.最后给出仿真例子.     

不确定非线性切换系统鲁棒容错H∞控制与仿真

为了克服外部扰动与执行器失效对切换系统的不良影响,使系统具有可靠性和抗干扰性,针对一类不确定非线性切换系统,研究了鲁棒容错H∞控制器设计与切换问题.假设系统中存在外部扰动,并且所有的矩阵同时带有未知、时变和范数有界的不确定性.当有执行器失效,并使得每个子系统均不能镇定的情况下,利用线性矩阵不等式技术和多李亚普诺夫函数法设计γ次优鲁棒H∞反馈容错控制器和切换策略,保证切换系统能全局二次稳定并且满足日∞性能指标,对得到的γ次优鲁棒H∞容错控制器进行优化,通过变量替换法获得了γ最优鲁棒H∞容错控制器.仿真结果表明,在执行器正常工作和一些执行器发生失效时,容错控制器和切换策略是有效的.     

非线性系统有限时间控制研究综述

近30年来,有限时间控制因其具有收敛速度快、抗扰性强、控制精度高等优点,引起了学者们的研究兴趣.据作者所知,目前鲜有文献系统地总结有限时间控制的相关研究内容.因此,本文致力于较为系统且完整地给出非线性系统有限时间控制方法的研究进展.主要内容包括如下几方面:研究意义;有限时间的定义,判据及设定时间表达式;有限时间设计方法的研究现状以及未来工作.     

非线性系统的分区域线性化控制及其在水轮机调节系统中的应用

本文初步解决了非线性系统的分区域线性化控制律的连续性和系统的稳定性问题,简要介绍了一个应用例子.     

一类非线性不确定系统的高阶积分自适应滑模控制

为有效改善传统积分滑模在一类非线性不确定系统的应用中存在的抖振问题,结合有限时间收敛理论、高阶积分滑模理论和自适应控制理论,提出了一种高阶积分自适应滑模控制方法;该方法通过选取有限时间收敛反馈量和设计高阶积分滑模面,不仅确保了系统状态误差在有限时间内的收敛性,而且还保证了系统具备对不确定性干扰的抑制能力;同时,当系统的不确定项的边界范围无法预先确定时,采用自适应方法对滑模控制的趋近速率进行估计;仿真结果表明所提方法能够有效抑制非线性不确定系统的抖动,并具有较高的控制精度.     

一类非线性切换时延系统的鲁棒稳定性

本文通过利用平均驻留时间方法,研究一类具有不确定性非线性切换时延系统的指数稳定性问题。给出非切换系统的候选李雅普诺夫函数的衰减估计分析,然后以线性矩阵不等式的形式给出使系统保持指数稳定及鲁棒指数稳定的充分条件,同时也给出了系统状态指数衰减的具体的估计形式。     

一类具有未知幂次的高阶不确定非线性系统的自适应控制

研究了一类具有未知幂次的高阶不确定非线性系统的自适应跟踪控制问题. 在无需系统函数先验知识的条件下, 采用积分反推技术和障碍李雅普诺夫函数, 提出了一种新颖的自适应跟踪控制算法. 该控制算法的显著特点是所设计的自适应控制器均与系统幂次无关, 并且能够保证闭环系统的所有信号皆有界. 仿真算例验证了该控制算法的有效性.     

基于加幂积分方法的制导控制一体化设计

针对高超声速飞行器纵向制导控制一体化设计问题展开研究.首先建立纵向制导与控制系统一体化设计模型;然后结合非线性干扰观测器与加幂积分方法设计制导与控制一体化算法,并借助相关基础理论证明级联系统是全局有限时间稳定的.所提出的方法可以使制导与控制系统协调配合,更充分地利用飞行器控制能力.通过与反步滑模制导控制一体化设计方法进行对比仿真,验证了该方法有效且更具优势,并通过模拟外扰及参数拉偏情况下的仿真验证了所提出方法亦具备较强的鲁棒性.     

Reduced-order control for a class of nonlinear similar interconnected systems with mismatched uncertainty

In this paper, a class of nonlinear interconnected systems with similar structure is considered. The interconnected system consists of matched and mismatched uncertainties. Based on constrained Lyapunov equations and by exploiting the structure of the interconnected system, a continuous output feedback reduced-order control scheme is presented to stabilize the system robustly. Our approach allows more general forms of known and uncertain interconnections than existing work. The effectiveness of the proposed reduced-order control scheme is illustrated through a numerical example.     

Robust output tracking of nonlinear systems with mismatched uncertainties

The problem of robust output tracking for a class of uncertain nonlinear systems which do not satisfy the conventional matching condition is considered. The main assumption on the uncertainty is that the triangularity condition is satisfied. Based on backstepping method and input/output linearization approach, we propose a class of non-adaptive state feedback controllers which can guarantee exponential stability of the tracking error for the uncertain nonlinear systems first. Next, adaptive control laws are developed so that no prior knowledge of the bounds on the uncertainties is required. By updating these upper bounds, we design a class of adaptive robust controllers. It is shown that under the proposed adaptive robust control the tracking error of the controlled system converges to zero as time approaches infinity.     

Robust adaptive output-feedback control for a class of nonlinear systems with general uncertainties

This paper investigates the robust adaptive output-feedback control for a class of nonlinear systems with general uncertainties and unknown parameters. First, a stable state observer is constructed and the system state is observed, and then the adaptive output-feedback controller is constructively designed for tracking the given reference signal. It is proven that the constructed controller is robust to the uncertainties of both the unknown parameters and the system states. These results show that the global stability of the resulting closed-loop systems has been guaranteed and the ε-tracking problem has been solved. Meanwhile, it is also proven that the tracking error tends to a ‘steady state’ at the negative exponential attenuating rate. Simulation examples show that the tracking effects of the designed adaptive control systems are good, and the control quantities used in the simulation examples are always within the range of the admissible control.     

Passive actuator fault tolerant control for a class of MIMO nonlinear systems with uncertainties

Fault tolerant control of affine class of multi-input multi-output (MIMO) nonlinear systems has not received considerable attention of researchers compared to other class of nonlinear systems. Therefore, this paper proposes an adaptive passive fault tolerant control method for actuator faults of affine class of MIMO nonlinear systems with uncertainties using sliding mode control . The actuator fault is represented by a multiplicative factor of the control signal which reflects the loss of actuator effectiveness. The design of the controller is based on the assumption that the maximum loss level of the actuator effectiveness is known. Furthermore, since the proposed controller is adaptive, it does not require any a-priori knowledge of the uncertainty bounds. The closed-loop stability conditions of the controller are derived based on Lyapunov theory. The effectiveness of the proposed controller is demonstrated considering two examples: a two degree of freedom helicopter and a two-link robot manipulator and has been found to be satisfactory.     

Robust learning control for a class of nonlinear systems with periodic and aperiodic uncertainties

This paper addresses the robust learning control problem for a class of nonlinear systems with structured periodic and unstructured aperiodic uncertainties. A recursive technique is proposed which extends the backstepping idea to the robust repetitive learning control systems. A learning evaluation function instead of a Lyapunov function is formulated as a guideline for derivation of the control strategy which guarantees the asymptotic stability of the tracking system. A design example is given.     

Adaptive multiple-surface sliding control for non-autonomous systems with mismatched uncertainties

In this paper, we propose a sliding mode-based controller for a class of single-input single-output nonlinear systems with mismatched uncertainties whose variation bounds are not given. The concept of multiple-surface sliding control is used to cope with the uncertainty mismatch problem, and the function approximation technique is introduced to transform the uncertainties into a finite combination of orthonormal basis functions. An adaptive controller can thus be designed using the Lyapunov approach to achieve output error convergence and boundedness of all signals. Simulation results of a benchmark problem have verified the performance and feasibility of the proposed control strategy.     

一类非匹配不确定非线性系统的鲁棒跟踪控制制

针对一类半严格反馈型不确定非线性系统,提出一种鲁棒反演滑模变结构控制方法.采用反演控制方法设计了使前n-1阶子系统稳定的虚拟控制律,抑制非匹配不确定性的影响;在第n步设计了一种连续可导的滑模变结构控制律,消除控制抖振,实现了对存在未知不确定性及扰动系统的鲁棒输出跟踪.通过Lyapunov定理证明了闭环系统所有信号最终有界.仿真结果验证了该方法的有效性.     

Observer based learning control for a class of nonlinear systems with time-varying parametric uncertainties

In this note, a new learning control approach, combined with state estimation, is developed to perform output tracking problems where the state information is not available. By virtue of the learning capability, the control mechanism is able to handle a class of rapid time-varying parametric uncertainties which are periodic and the only prior knowledge is the periodicity. Two classes of system nonlinearities are taken into account. The first class is the global Lipschitz continuous functions of the unknown state variables, and the second class is the local Lipschitz continuous functions of the accessible output variables. To facilitate the learning control design and property analysis, the Lyapunov-like energy function is employed, which allows the incorporation of any available system knowledge. Henceforth the new learning control approach widens the application scope comparing with the repetitive type learning control.     

Filtering adaptive neural network controller for multivariable nonlinear systems with mismatched uncertainties

This paper synthesizes a filtering adaptive neural network controller for multivariable nonlinear systems with mismatched uncertainties. The multivariable nonlinear systems under consideration have both matched and mismatched uncertainties, which satisfy the semiglobal Lipschitz condition. The nonlinear uncertainties are approximated by a Gaussian radial basis function (GRBF)‐based neural network incorporated with a piecewise constant adaptive law, where the adaptive law will generate adaptive parameters by solving the error dynamics between the real system and the state predictor with the neglection of unknowns. The combination of GRBF‐based neural network and piecewise constant adaptive law relaxes hardware limitations (CPU). A filtering control law is designed to handle the nonlinear uncertainties and deliver a good tracking performance with guaranteed robustness. The matched uncertainties are cancelled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. Since the virtual reference system defines the best performance that can be achieved by the closed‐loop system, the uniform performance bounds are derived for the states and control signals via comparison. To validate the theoretical findings, comparisons between the model reference adaptive control method and the proposed filtering adaptive neural network control architecture with the implementation of different sampling time are carried out.     

Finite‐time tracking control for a class of nonlinear systems with multiple mismatched disturbances

This article investigates the finite‐time output tracking problem for a class of nonlinear systems with multiple mismatched disturbances. To efficiently estimate the disturbances and their derivatives, a continuous finite‐time disturbance observer (CFTDO) design method is developed. Based on the modified adding a power integrator method and CFTDO technique, a composite tracking controller is constructed such that the system output can track the desired reference signal in finite time. Simulation results demonstrate the effectiveness of the proposed control approach.