A convex optimization approach to robust iterative learning control for linear systems with time-varying parametric uncertainties

In this paper, we present a new robust iterative learning control (ILC) design for a class of linear systems in the presence of time-varying parametric uncertainties and additive input/output disturbances. The system model is described by the Markov matrix as an affine function of parametric uncertainties. The robust ILC design is formulated as a min–max problem using a quadratic performance criterion subject to constraints of the control input update. Then, we propose a novel methodology to find a suboptimal solution of the min–max optimization problem. First, we derive an upper bound of the worst-case performance. As a result, the min–max problem is relaxed to become a minimization problem in the form of a quadratic program. Next, the robust ILC design is cast into a convex optimization over linear matrix inequalities (LMIs) which can be easily solved using off-the-shelf optimization solvers. The convergences of the control input and the error are proved. Finally, the robust ILC algorithm is applied to a physical model of a flexible link. The simulation results reveal the effectiveness of the proposed algorithm.     

Robustness analysis for linear dynamical systems with linearlycorrelated parametric uncertainties

The authors propose an approach for robust pole location analysis of linear dynamical systems with parametric uncertainties. Linear control systems with characteristic polynomials whose coefficients are affine in a vector of uncertain physical parameters are considered. A design region in complex plane for system pole placement and a nominal parameter vector generating a characteristic polynomial with roots in that region are given. The proposed method allows the computation of maximal domains bounded by linear inequalities and centered at the nominal point in system parameter space, preserving system poles in the given region. The solution of this problem is shown to also solve the problem of testing robot location of a given polytope of polynomials in parameter space. It is proved that for stability problems for continuous-time systems with independent perturbations on polynomial coefficients, this method generates the four extreme Kharitonov polynomials     

基于观测器的参数不确定非线性系统的模糊鲁棒控制

对一类非线性系统进行模糊建模及其模糊观测器设计，研究了在系统的状态不可测且存在参数不确定的模糊鲁捧控制问题，以线性矩阵不等式的形式给出了模糊控制系统具有李雅普诺夫意义下稳定的充分条件，最后把所提出的方法应用到倒立摆系统进行仿真，仿真结果验证了该控制方法的有效性。     

基于观测器的参数不确定非线性系统的模糊鲁棒控制

对一类非线性系统进行模糊建模及其模糊观测器设计, 研究了在系统的状态不可测且存在参数不确定的模糊鲁棒控制问题, 以线性矩阵不等式的形式给出了模糊控制系统具有李雅普诺夫意义下稳定的充分条件, 最后把所提出的方法应用到倒立摆系统进行仿真, 仿真结果验证了该控制方法的有效性.     

基于观测器的非线性不确定离散系统的鲁棒模糊控制

研究了参数不确定及状态变量难以获取的非线性系统的鲁棒模糊控制问题.采用离散模糊T-S模型对离散非线性系统进行建模并建立了模糊观测器.用矩阵不等式的形式推导出了在Lyapunov意义下鲁棒镇定的充分条件.利用线性矩阵不等式(LMI)导出了模糊反馈增益和模糊观测器增益存在的充分条件.     

Adaptive robust fault-tolerant control for linear MIMO systems with unmatched uncertainties

In this paper, two novel fault-tolerant control design approaches are proposed for linear MIMO systems with actuator additive faults, multiplicative faults and unmatched uncertainties. For time-varying multiplicative and additive faults, new adaptive laws and additive compensation functions are proposed. A set of conditions is developed such that the unmatched uncertainties are compensated by actuators in control. On the other hand, for unmatched uncertainties with their projection in unmatched space being not zero, based on a (vector) relative degree condition, additive functions are designed to compensate for the uncertainties from output channels in the presence of actuator faults. The developed fault-tolerant control schemes are applied to two aircraft systems to demonstrate the efficiency of the proposed approaches.     

A more reliable robust stability indicator for linear systemssubject to parametric uncertainties

Many of the currently proposed techniques to perform frequency-domain stability analysis against real parametric variations fail because “discontinuities” of the real stability margin prevent straightforward frequency gridding techniques from behaving properly. In this paper, we present a new robustness indicator which readily bypasses this issue. The new indicator seems to work considerably better than the existing ones     

Distributed robust control of linear multi-agent systems with parameter uncertainties

This article considers the distributed robust control problems of uncertain linear multi-agent systems with undirected communication topologies. It is assumed that the agents have identical nominal dynamics while subject to different norm-bounded parameter uncertainties, leading to weakly heterogeneous multi-agent systems. Distributed controllers are designed for both continuous- and discrete-time multi-agent systems, based on the relative states of neighbouring agents and a subset of absolute states of the agents. It is shown for both the continuous- and discrete-time cases that the distributed robust control problems under such controllers in the sense of quadratic stability are equivalent to the H _∞ control problems of a set of decoupled linear systems having the same dimensions as a single agent. A two-step algorithm is presented to construct the distributed controller for the continuous-time case, which does not involve any conservatism and meanwhile decouples the feedback gain design from the communication topology. Furthermore, a sufficient existence condition in terms of linear matrix inequalities is derived for the distributed discrete-time controller. Finally, the distributed robust H _∞ control problems of uncertain linear multi-agent systems subject to external disturbances are discussed.     

Robust iterative learning control for linear systems with multiple time-invariant parametric uncertainties

This article presents a novel robust iterative learning control algorithm (ILC) for linear systems in the presence of multiple time-invariant parametric uncertainties.The robust design problem is formulated as a min–max problem with a quadratic performance criterion subject to constraints of the iterative control input update. Then, we propose a new methodology to find a sub-optimal solution of the min–max problem. By finding an upper bound of the worst-case performance, the min–max problem is relaxed to be a minimisation problem. Applying Lagrangian duality to this minimisation problem leads to a dual problem which can be reformulated as a convex optimisation problem over linear matrix inequalities (LMIs). An LMI-based ILC algorithm is given afterward and the convergence of the control input as well as the system error are proved. Finally, we apply the proposed ILC to a generic example and a distillation column. The numerical results reveal the effectiveness of the LMI-based algorithm.     

Comparisons among robust stability criteria for linear systems with affine parameter uncertainties

This paper is concerned with the problem of comparisons among robust stability criteria for a class of uncertain linear systems, where the system state matrices considered are affinely dependent on the uncertain parameters. At first, a robust stability criterion for the class of systems to be affinely quadratically stable (AQS) is derived based on the vertex separator approach, where affine parameter-dependent Lyapunov functions are exploited to prove stability. Then comparison results between the robust stability criterion and the existing tests for AQS are given in terms of degree of conservatism. A numerical example is given to illustrate the results.     

Design of robust output-feedback repetitive controller for class of linear systems with uncertainties

Repetitive control, which adds a human-like learning capability to a control system, is widely used in many fields. This paper deals with the problem of designing a robust repetitive-control system based on output feedback for a class of plants with time-varying structured uncertainties. A continuous-discrete two-dimensional hybrid model is established that accurately describes the features of repetitive control so as to enable independent adjustment of the control and learning actions. A sufficient conditi...     

New robust stability bounds of linear discrete-time systems with time-varying uncertainties

This paper presents new uncertain parameter variation bounds for linear discrete-time systems to preserve asymptotic stability. The Lyapunov method is utilized to treat both structured and unstructured uncertainties, and the results are optimized with respect to a parameter in the inequality used. When applied to examples considered by previous authors, our results give less conservative bounds.     

不确定时滞系统的时滞依赖鲁棒非脆弱H∞控制

基于线性矩阵不等式(LMI)方法,研究了不确定时滞线性系统的鲁棒非脆弱H∞状态反馈控制器的设计问题,以一个LMI形式给出了控制器存在的充分条件,而且该LMI是与时滞相关的.同时,经过全等变换、变量变换和Schur补引理,该LMI的所有参数都是线性的,这样参数无需预取就可以利用LMI Toolbox获得解.实例表明了上述设计方法的有效性.     

不确定线性多时变时滞系统的时滞相关鲁棒控制

提出一种积分不等式新方法，讨论不确定线性多时变时滞系统的鲁棒稳定性以及鲁棒稳定化问题，首先利用Park不等式建立了基于二次型项的积分不等式，利用这一不等式获得了系统基于LMI的时滞相关、时滞导数相关鲁棒稳定条件；然后利用这一条件给出了时滞状态反馈控制器的一种新的设计方法，数值例子说明了所得结论具有较小的保守性。     

不确定时滞系统的时滞依赖鲁棒非脆弱H∞控制

基于线性矩阵不等式(LMI)方法, 研究了不确定时滞线性系统的鲁棒非脆弱H_∞状态反馈控制器的设计问题, 以一个LMI形式给出了控制器存在的充分条件, 而且该LMI是与时滞相关的. 同时, 经过全等变换、变量变换和Schur补引理, 该LMI的所有参数都是线性的, 这样参数无需预取就可以利用LMI Toolbox获得解. 实例表明了上述设计方法的有效性.     

Problem of tracking in linear systems with parametric uncertainties under unstable zero dynamics

Proposed was a solution to the problem of tracking in linear SISO systems with unstable zero dynamics in the conditions of parametric uncertainty of the models of plant and reference generator under incomplete information about the state vectors. The approach developed employs the methods of the sliding mode theory in the problems of real-time feedback design, observation, and parameter identification.     

Non-monotonic robust H2 fuzzy observer-based control for discrete time nonlinear systems with parametric uncertainties

A non-monotonic Lyapunov function (NMLF) is deployed to design a robust H₂ fuzzy observer-based control problem for discrete-time nonlinear systems in the presence of parametric uncertainties. The uncertain nonlinear system is presented as a Takagi and Sugeno (T–S) fuzzy model with norm-bounded uncertainties. The states of the fuzzy system are estimated by a fuzzy observer and the control design is established based on a parallel distributed compensation scheme. In order to derive a sufficient condition to establish the global asymptotic stability of the proposed closed-loop fuzzy system, an NMLF is adopted and an upper bound on the quadratic cost function is provided. The existence of a robust H₂ fuzzy observer-based controller is expressed as a sufficient condition in the form of linear matrix inequalities (LMIs) and a sub-optimal fuzzy observer-based controller in the sense of cost bound minimization is obtained by utilising the aforementioned LMI optimisation techniques. Finally, the effectiveness of the proposed scheme is shown through an example.     

New results on robust stability for differential-difference systems with affine linear parametric uncertainty

This article presents sufficient conditions to verify the robust stability property of convex combinations for quasipolynomials that represent the characteristic equation of differential-difference dynamics systems. It considers affine linear parametric uncertainty structure in the coefficients of quasipolynomials and also, interval uncertainty in the time delay. First of all, a transformation of the delay's operator is performed in order to get a two variable polynomial; after this, to obtain the robust stability property, a result based on the Hurwitz matrix is applied.     

基于线性矩阵不等式的参数不确定性关联模糊大系统的分散鲁棒镇定

讨论了参数不确定性关联模糊大系统的分散鲁棒镇定问题,所考虑的参数不确定性满足范数有界条件.基于李雅普诺夫稳定性理论及大系统分散控制理论,采用分散化PDC(parallel distributed compensation)控制器,给出了保证该关联模糊大系统闭环渐近稳定的LMI形式的充分条件,通过MATLAB软件中的LMI工具箱可求解出这些LMI中的控制器参数.仿真例子说明了所提方法的有效性.     

Design of robust PD-type control laws for robotic manipulators with parametric uncertainties

In this article, design of a simple robust control law that achieves desired positions and orientations for robotic manipulators with parametric uncertainties is studied. A discontinuous control law is proposed, which consists of a high-gain linear proportional plus derivative (PD) term and additional terms that compensate for the effect of gravitation. The stability of the robotic system under the proposed control law is proved by LaSalle's stability theorem. Furthermore, by the theory of singularly perturbed systems, it is shown that if the proportional and derivative gain matrices are diagonal with large positive elements then the system is decoupled into a set of first-order linear systems. Simulation results are presented to illustrate the application of the proposed control law to a two-link robotic manipulator.