Robust stabilization of uncertain systems with unknown input delay

This paper is concerned with the robust controller design for uncertain input-delayed systems. The time delay is assumed to be an unknown constant. A controller with delay feedback for the robust stabilization of the system is proposed. The stability criterion of the closed-loop system is derived in terms of linear matrix inequalities (LMIs). Examples show that in many cases our method can give less conservative results than those by the existing methods. Moreover, for the same cases, our controllers have lower feedback gains than the existing ones.     

Adaptive non-predictor control of lower triangular uncertain nonlinear systems with an unknown time-varying delay in the input

In this paper, we consider a control problem for a class of uncertain nonlinear systems in which there exists an unknown time-varying delay in the input and lower triangular nonlinearities. Usually, in the existing results, input delays have been coupled with feedforward (or upper triangular) nonlinearities; in other words, the combination of lower triangular nonlinearities and input delay has been rare. Motivated by the existing controller for input-delayed chain of integrators with nonlinearity, we show that the control of input-delayed nonlinear systems with two particular types of lower triangular nonlinearities can be done. As a control solution, we propose a newly designed feedback controller whose main features are its dynamic gain and non-predictor approach. Three examples are given for illustration.     

Controller synthesis for uncertain fuzzy systems with integrating multiple time-varying delays

This article mainly investigates the controller synthesis for uncertain fuzzy systems with integrating multiple time-varying delays, which can describe a much larger class of nonlinear systems or uncertain time-delay systems. First, a sufficient stability condition for the unforced Takagi–Sugeno (T-S) fuzzy models with multiple time-varying delays and uncertainties are derived. By involving the parallel distributed compensator (PDC), some design conditions for the resulting closed-loop fuzzy systems are further presented. These proposed conditions are all expressed in terms of linear matrix inequalities (LMIs), and we can readily perform the PDC synthesis from current LMI solvers. Numerical examples are given to demonstrate the validity and superiority of the proposed approach.     

基于LMI 的不确定随机系统输出反馈保性能控制

针对一类不确定连续随机系统,研究了具有输出反馈控制器的保性能控制．首先,对于范数有界 的不确定随机系统,得到了具有输出反馈控制器的闭环系统的二次型性能指标的上界一般形式．其次,应用 线性矩阵不等式技术,研究了其闭环系统的二次稳定和二次保性能稳定;并且依据线性矩阵不等式优化方法, 得到了使闭环系统渐近稳定的最优输出反馈保性能控制器．最后,给出仿真算例,验证本文方法的可行性和 有效性．     

非线性动态突变系统的多模型自适应执行器故障补偿设计

本文针对因多重不确定执行器故障而引起系统动态突变的非线性系统,设计了一种基于多模型切换的自适应执行器故障补偿控制策略,以提高系统应对动态突变的能力,同时实现不确定执行器故障的快速精确补偿.针对执行器故障模式的不确定性问题,采用基于多模型的参数估计方法,设计了自适应控制器组;基于最优性能指标函数,提出了一种控制切换机制,...     

Robust sliding mode control of uncertain nonlinear systems

A dynamic sliding mode controller design method is proposed for multiple input-output systems with additive uncertainties. A previous result on the stability of triangular systems is generalised to the case of uniform ultimate boundedness of controlled triangular systems. This is used to prove the stability of the overall closed-loop system. The uncertain system with appropriately chosen sliding mode control is shown to be ultimately bounded if the zero dynamics of the nominal system are uniformly asymptotically (exponentially) stable. The design method is demonstrated with two examples.     

Passivity and passification for stochastic systems with Markovian switching and generally uncertain transition rates

The paper deals with the problems of passivity and passification for stochastic systems with Markovian switching and generally uncertain transition rates. The considered systems are more general, which cover uncertain transition rates and partly known transition rates as two special cases. By employing the multiple Lyapunov function and some free-weighting matrices, a state feedback controller is constructed such that the resulted closed-loop system is stochastically passive. Some sufficient conditions for the solution to the problem are derived in the form of linear matrix inequalities (LMIs). Finally, a numerical example is given to demonstrate the validity of the main results.

     

Delta算子切换系统的鲁棒滤波器研究

研究了一类参数不确定线性Delta算子切换系统的鲁棒H∞滤波器设计问题。提出利用多Lyapunov函数和平均驻留时间方法,以线性矩阵不等式的形式给出了参数不确定Delta算子滤波误差切换系统指数稳定性条件,并进行了肌性能分析,从而进一步给出Delta算子切换系统鲁棒肌滤波器存在的充分条件和设计方法。所设计的滤波器不但保证系统参数不确定时闭环系统指数稳定,而且满足所期望的H∞性能指标。仿真结果证明了设计方法的有效性和可行性。     

Adaptive stabilizing state feedback controllers of uncertaindynamical systems with multiple time delays

The problem of robust stabilization for a class of uncertain dynamical systems with multiple delayed state perturbations is considered. In this paper, it is assumed that each perturbation is bounded by a linear function of delayed state with unknown gains, and an adaptation law is proposed to estimate these unknown gains. Moreover, by making use of the updated values of these unknown bounds we propose a memoryless state feedback controller for such a class of uncertain time-delay systems. Based on Lyapunov stability theory and Lyapunov-Krasovskii functional, it is shown that the closed-loop dynamical system resulting from the proposed adaptive robust control schemes is globally stable in the sense of uniform ultimate boundedness. Finally, a numerical example is given to demonstrate the validity of the results     

On stability delay bounds of simple input-delayed linear and non-linear systems: Computational results

This paper deals with the problem of delay size stability analysis of single input-delayed linear and nonlinear systems. Conventional reduction, reduction linked by sliding mode, and linear memoryless control approaches are used for simple input-delayed systems to obtain the stability conditions. Several first order examples are investigated systematically to demonstrate the capabilities and limitations of the advanced stability analysis techniques including Lyapunov-Krasovskii functionals, Newton-Leibniz formula, and a newly addressed Lagrange mean value theorem. Numerical comparative results show the usefulness and effectiveness of the advanced delay size analysis techniques proposed in this paper.     

具有结构不确定性的线性反馈控制系统的鲁棒稳定性

本文研究了具有结构不确定性(Structured Uncertainty)因素的反馈控制系统的鲁棒稳 定性问题,对于一个普通的补偿器,给出了闭环系统鲁棒稳定的充要条件,当补偿器满足某些 假设条件时,得出了闭环系统鲁棒稳定的有限检验的充分必要条件.     

Adaptive neural control for pure-feedback nonlinear time-delay systems with unknown dead-zone: a Lyapunov-Razumikhin method

This paper addresses the problem of adaptive neural control for a class of uncertain pure-feedback nonlinear systems with multiple unknown state time-varying delays and unknown dead-zone. Based on a novel combination of the Razumikhin functional method, the backstepping technique and the neural network parameterization, an adaptive neural control scheme is developed for such systems. All closed-loop signals are shown to be semiglobally uniformly ultimately bounded, and the tracking error remains in a small neighborhood of the origin. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control schemes.     

Memoryless State Feedback Controller Design for Time Delay Systems With Matched Uncertain Nonlinearities

The robust control problem for a class of uncertain time-delay systems is investigated. The systems include multiple time delays and uncertain nonlinear functions. To our best knowledge, no controller design method for the systems is reported in the literature except for sliding mode control (SMC). However, the sliding mode controller must use the delayed state of the system, so that the precise time delays have to be known, and also a large memory is needed for controller implementation. To overcome the shortcomings, we employ the backstepping method to design a memoryless state feedback controller. By constructing a novel Lyapunov-Krasovskii functional, we show that the resulting closed-loop system is asymptotically stable. Simulations are done to verify the effectiveness of the proposed method.     

不确定条件下控制分配问题的鲁棒优化方法

针对具有冗余执行机构的过驱动系统, 在考虑控制效率不确定性的条件下, 提出了一种基于鲁棒优化理论的控制分配算法. 研究了原始不确定鲁棒优化模型的建立和基于椭球不确定集的鲁棒对等式的转化问题, 并推广到可由锥二次不等式表示的不确定集的情况. 讨论了鲁棒优化控制分配算法的求解方法及其计算复杂度. 最后, 针对多操纵面飞机的最优控制分配问题与传统算法进行了仿真比较, 结果表明鲁棒优化算法能有效降低控制效率不确定性的影响, 使分配结果更为合理, 从而具有更好的鲁棒性, 同时能有效提高操纵面故障情况下闭环系统的控制重构能力, 很好地改善了飞控系统的性能.     

不确定离散广义系统的D稳定鲁棒控制

研究了具有圆盘区域极点约束的一类不确定离散广义系统的鲁棒控制问题.首先,研 究了控制输入项不含扰动的不确定离散广义系统,提出了广义二次D镇定的概念,基于矩阵不 等式和广义Riccati方程,给出了一种广义二次D镇定器的设计方法,所得到的结论能够实现研 究目标;然后,讨论了控制输入项含有扰动的不确定离散广义系统,在一定的假设条件下,给出 了期望状态反馈增益阵的存在条件及其解析表达式.最后,用数值示例说明所给方法的有效性 及可行性.     

不确定非线性系统的鲁棒耗散性与保性能控制

考虑了不确定仿射非线性系统的鲁棒耗散性与保性能控制问题,不确定性范数有界,不满足匹配条件.基于HJI不等式,设计了状态反馈控制器.当扰动存在时,控制器能使系统达到耗散,当扰动为零时,所设计的控制器使系统对于给定的性能函数具有上界,最后研究了不确定线性系统的保性能与耗散性控制情形.     

Flocking of networked mechanical systems on directed topologies: a new perspective

In this paper, we investigate the flocking problem for multiple uncertain mechanical systems interacting on directed topologies. We propose an integral-sliding adaptive control to realise the objective of flocking, which gives rise to a cascade closed-loop system, and also propose a new notion – iBIBO (integral-bounded-input bounded-output) stability to characterise a new input–output property of a special class of dynamical systems, which is then used for the stability analysis of the closed-loop system. With the proposed iBIBO analysis tool and Lyapunov-like approach, we show that the proposed adaptive controller ensures the position and velocity consensus of the mechanical systems if and only if the damping is greater than certain lower bound for a given stiffness, and that the velocities of the mechanical systems converge to the weighted average of their initial values and the positions of the mechanical systems converge to the initial-states-dependent ramp trajectory. The performance of the proposed adaptive control scheme is shown by numerical simulation results.     

Closed-loop identification of systems with uncertain time delays using ARX-OBF structure

Closed-loop identification of systems with known time delays can be effectively carried out with simple model structures like Autoregressive with Exogenous Input (ARX) and Autoregressive Moving Average with Exogenous Input (ARMAX). However, when the system contains large uncertain time delay, such structures may lead to inaccurate models with significant bias if the time delay estimate used in the identification is less accurate. On the other hand, conventional orthonormal basis filter (OBF) model structures are very effective in capturing the dynamics of systems with uncertain time delays. However, they are not effective for closed-loop identification. In this paper, an ARX-OBF model structure which is obtained by modifying the ARX structure is shown to be effective in handling closed-loop identification of systems with uncertain time delays. In addition, the paper shows that this advantage of ARX-OBF models over simple ARX model is considerable in multi-step ahead predictions.     

A fuzzy adaptive variable-structure control scheme for uncertain chaotic MIMO systems with sector nonlinearities and dead-zones

In this paper, a fuzzy adaptive variable-structure controller is investigated for a class of uncertain multi-input multi-output (MIMO) chaotic systems with both sector nonlinearities and dead-zones. A suitable adaptive fuzzy system is used to reasonably approximate the uncertain functions. A Lyapunov approach is employed to derive the parameter adaptation laws and prove the boundedness of all signals of the closed-loop system as well as the exponential convergence of the closed-loop errors to an adjustable region. The proposed controller can be applied to the systems with or without sector nonlinearities and/or dead-zones in the input. The effectiveness of the proposed fuzzy adaptive controller is illustrated throughout simulation results.     

不确定非线性时滞系统的非脆弱保成本控制

研究了一类具有状态时滞的不确定非线性系统的非脆弱保成本控制问题。通过利用Lyapunov稳定性理论和线性矩阵不等式方法,设计非脆弱保成本控制律,使得闭环系统渐近稳定,并且系统的性能指标不超过某个确定的上界。通过求解一个具有线性矩阵不等式约束的凸优化问题来设计最优非脆弱保成本控制器,以使得闭环不确定系统的性能指标最小化。仿真结果验证了该控制算法的有效性。