Robust Stabilization Problem Research Articles

Robust stabilisation of uncertain nonlinear systems with matched and unmatched uncertainties

This paper considers the problem of robust stabilisation of uncertain nonlinear systems with both matched and unmatched uncertainties. A new robust controller is proposed to guarantee practical or asymptotic stability under non-vanishing or vanishing unmatched uncertainties. First, the system uncertainties are decomposed optimally into the matched and unmatched portions with an objective of the minimum norm for the unmatched part. Next, instead of a robust control design based on only the matched part of uncertainties commonly used in the previous works, a robust controller is synthesised based on both matched and mismatched portions of the uncertainties. It is shown that in uncertain systems whose state cannot simultaneously stay in a so-called null set and diverge to infinity, the proposed controller guarantees stability no matter how large the input-unrelated unmatched uncertainties are. Numerical examples illustrate that the proposed controller is more robust against uncertainties, and offers improved damping and stabilisation features.

Robust control design of uncertain nonlinear systems: a self-compensating and self-tuning approach

ABSTRACT The problem of robust stabilisation is considered for a class of uncertain nonlinear systems with linear control term. It is not required that the unforced nominal (nonlinear) system has to be stable and/or has to be known, which means that its Lyapunov function need not be known and/or found for designing a stabilising control scheme to compensate the effect of uncertainty on the systems like some traditional control design approaches. For such a class of uncertain nonlinear systems, a design approach, called a self-compensating and self-tuning one, is presented whereby some robust state feedback control schemes can be easily synthesised. The proposed design approach can result in a linear state feedback control scheme with a time-varying control gain for such a class of uncertain nonlinear systems, which implies the simplicity of the design approach and control results. In addition, the system uncertainty is also not required to have to satisfy the matching conditions.

An optimization‐based method for robust stabilization of linear delay systems

AbstractThis paper investigates the robust stabilization problem of linear delay systems with parametric uncertainty. First, by means of the argument principle, a delay‐dependent sufficient condition is derived for designing a feedback controller, with which the closed‐loop system can achieve robust stability. Then, based on the fundamental matrix of the linear delay systems, a constrained optimization problem is formulated for solving the feedback gain matrices. The effectiveness of the proposed method is verified by some simulation results.

On robustification of digital event-based controllers for control-affine nonlinear systems

In this paper, the robust digital stabilization problem of nonlinear systems is investigated. In particular, a methodology for the design of robust quantized sampled-data stabilizers updated via an event-triggered mechanism is provided for time-varying control-affine nonlinear systems affected by actuation disturbances and measurement noises. The notion of time-varying steepest descent feedback (TSDF), continuous or not, and the Input-to-State Stability (ISS) redesign methodology are used for the development of the proposed robust event-based digital controller. Under the assumption that the actuation disturbances and measurement noises are bounded with a-priori known bounds and that the amplitude of the measurement noises satisfies a certain condition related to the new added robustification term, the following result is proved: there exist a suitably fast sampling and an accurate quantization of the input/output channels such that the digital implementation of robustified TSDF controllers, updated through a proposed event-triggered mechanism, ensures semi-global practical stability of the related closed-loop system regardless of the above uncertainties. In the methodology here proposed, time-varying sampling periods and the non-uniform quantization of the input/output channels are allowed. Moreover, the theory here developed includes the analysis of the intersampling system behaviour. Possible discontinuities in the function describing the TSDF at hand are also managed. The provided results are validated through a numerical example.

Some new results about the stability radius of infinite-dimensional systems perturbed stochastically and deterministically

This paper presents two significant contributions: First, we examine linear infinite-dimensional systems perturbed in deterministic and stochastic ways. The stability radius method is used to solve the robust stability. Bounds on the perturbations are obtained, guaranteeing that the troubled system is stable. The outcomes are determined via a Lyapunov equation. Secondly, we study the robust stabilisation problem. We investigate the maximisation of the stability radius when the input operator is unbounded in the general case. Also, we establish the conditions under which suboptimal controllers exist. An infinite-dimensional Riccati equation describes the supreme achievable stability radius.

Robust asymptotic stability analysis for fractional-order systems with commensurate time delays: The 1 < β ≤ 2 case

The robust asymptotic stability problem for fractional-order linear systems with commensurate time delays (FOSCDs) and structured perturbations is investigated in this manuscript. Based on the properties of Kronecker products and μ-analysis, the necessary and sufficient conditions are given to guarantee the asymptotic stability of FOSCDs. Then, the necessary and sufficient conditions for the robust asymptotic stability of FOSCDs with structured perturbations are investigated. To reduce the computing complexity and deal with the problems of systems with larger dimensions, a sufficient condition on the robust asymptotic stability of FOSCDs with structured perturbations is given based on the properties of Kronecker products and 2-norm transformations. Finally, several examples are illustrated to test the effectiveness of the proposed results.

Robust set stability of large-scale Boolean networks with disturbance via network aggregation

This paper explores the robust set stability problem of large-scale Boolean networks (BNs) with disturbances by resorting to the network aggregation method. Firstly, the network graph of large-scale BNs is partitioned into several small subnetworks, which converts the robust set stability of large-scale BNs into the (robust) set stability of subnetworks under arbitrary switching signal. Secondly, by perceiving the input nodes from other subnetworks as a switching signal, several new criteria are proposed for the robust set stability of each subnetwork with disturbance inputs under arbitrary switching signal. Finally, by combining the (robust) set stability of all subnetworks, the robust set stability of large-scale BNs with disturbance inputs is discussed. Moreover, as an application, the robust partial stability of large-scale BNs is considered.

Robust stability and stabilization of continuous‐discrete fractional‐order 2D Fornasini–Marchesini second model with interval uncertainties

AbstractThis paper investigates the robust stability and stabilization problems of continuous‐discrete fractional‐order two‐dimensional Fornasini–Marchesini second model with interval uncertainties. Firstly, for the nominal model with fractional‐order , the unified LMI‐based stability conditions are presented by general description of stable root‐clustering sets. Secondly, these stability conditions are transformed to be more tractable for stabilization, and the LMI/BMI‐based stabilization conditions are established via state feedback controllers. Meanwhile, one algorithm is proposed to solve the BMI‐based conditions. Thirdly, facing interval uncertainties in this model, the LMI‐based robust stability conditions and LMI/BMI‐based robust stabilization conditions are established. Lastly, two examples are given to show the validity of our robust stability and stabilization results.

Event‐triggered cooperative robust output regulation of minimum‐phase linear uncertain multi‐agent systems

AbstractIn this article, we investigate the event‐triggered cooperative robust output regulation problem of a class of minimum‐phase linear uncertain multi‐agent systems. In particular, we first propose a dynamic event‐triggered mechanism and an event‐triggered distributed output feedback control law. Then, by the internal model, the event‐triggered cooperative robust output regulation problem is converted into the event‐triggered cooperative robust stabilization problem of an augmented system composed of the distributed internal model and the original multi‐agent system. Next, we show that the event‐triggered cooperative robust stabilization problem can be solved by the proposed event‐triggered distributed output feedback control law together with a dynamic event‐triggered mechanism, and thus the event‐triggered cooperative robust output regulation problem is solved exactly in the sense that the tracking error of each subsystem converges to zero asymptotically while preventing the Zeno behavior from happening. Finally, we provide an example to illustrate the proposed control approach.

Robust fuzzy adaptive stabilization for uncertain nonlinear systems with quantized input and output constraints

In this paper, we study the problem of robust fuzzy adaptive output feedback stabilization for a class of nonlinear systems with quantized input and output constraints. The system under consideration has these characteristics: unknown state mismatch uncertainties and unknown disturbances, and unknown measurement noises. By employing the output filtering transformation, the fuzzy logic system (FLS) approximator, the backstepping, and the high gain observer technique, a non-fragile robust fuzzy adaptive observer and a hyperbolic tangent adaptive controller are presented to guarantee that the closed-loop system is ultimately uniformly bounded and the output is constricted in a prescribed performance curve. The effectiveness of the scheme is verified by numerical simulations.

Stochastic stability robustness and H 2 performance robustness of continuous-time Markovian jump linear systems with uncertain transition rates via μ analysis

This paper considers the stability robustness and H 2 performance robustness of continuous-time Markovian jump linear systems with uncertain transition rates. Based on the Kronecker product, the robustness problems are transformed into problems of judging whether a class of uncertain matrices can maintain nonsingularity. For the robust stability problem, the method for computing the robust upper and lower bounds of transition rates is given first and then the necessary and sufficient condition for the investigated system to maintain robust stochastic stability is given when considering interval uncertainty. For the robust H 2 performance problem, the robustness bounds and sufficient and necessary conditions guaranteeing the robust H 2 performance are similarly given. The robustness bounds for analysing the tolerance of continuous-time Markovian jump linear systems to parameter uncertainties can be conveniently computed by utilising the proposed results. Numerical examples illustrate that the results are less conservative than existing results.

Finite‐time robust simultaneous stabilization control for two nonlinear singular time‐delay systems

AbstractIn this paper, the finite‐time simultaneous stabilization problem of two nonlinear singular time‐delay Hamiltonian systems is investigated. Firstly, the two general nonlinear singular time‐delay Hamiltonian systems are transformed into their Hamiltonian differential‐algebraic forms by equivalent transformation, respectively, they are then converted to two strictly dissipative Hamiltonian forms via the state feedback method, and two strictly dissipative Hamiltonian systems are extended into a Hamiltonian one. Based on which, a suitable Hamiltonian function is constructed to analyze the finite‐time simultaneous stability and finite‐time robust simultaneous stabilization problem. Finally, an illustrative example is given to show the effectiveness of the results obtained. It should be pointed out that since there does not exist a finite‐time stability criterion on the nonlinear singular delay system, we adopt a new double compound asymptotic method.

Robust and Exponential Stabilization of a Cart–Pendulum System via Geometric PID Control

This paper addresses the robust stabilization problem of a cart–pole system. The controlled dynamics of this interconnected system are deduced by following the analytic framework of Lagrangian mechanics, and the residual terms are formulated as a bias depending on the angle and angular velocity. A geometric definition of Proportional–Integral–Derivative (PID) control algorithm is proposed, and a Lyapunov function is explicitly constructed through two stages of variable change. Local exponential stability of the stable equilibrium is proved, and a criterion for parameter tuning is provided by ensuring an exponential decrease in the Lyapunov function. Enlarging the control parameters to infinity allows for the extension of attraction region almost to the half circle. The effectiveness of geometric PID controller and the local exponential stability of the resulting close system are verified by simulating a numerical example.

Adaptive optimal ℓ∞‐induced robust stabilization of minimum phase SISO plant under bounded disturbance and coprime factor perturbations

AbstractThis paper addresses the problem of optimal robust stabilization of a discrete‐time minimum‐phase plant in the framework of robust control theory in the setup and under poor a priori information. Coefficients of the transfer function of the plant nominal model with stable zeros are unknown and belong to a known bounded polyhedron in the space of coefficients. The gains of coprime factor perturbations of the plant and the upper bound of external disturbance are also unknown. The problem under consideration is to design adaptive controller that minimizes, with the prescribed accuracy, the worst‐case asymptotic upper bound of the output. Solution of the problem is based on set‐membership estimation of unknown parameters and treating the control criterion as the identification criterion. A hard nonconvex problem of on‐line computation of optimal estimates is reduced, under additional nonrestrictive assumption, to a linear‐fractional programming via a nonlinear transformation of estimated parameters. Despite the non‐identifiability of the unknown parameters, the proposed adaptive controller guarantees, with the prescribed accuracy, the same optimal asymptotic upper bound of the output of adaptive system as the optimal controller for the plant with known parameters. In addition to the optimality of adaptive control, the proposed solution provides on‐line verification/validation of current estimates and a priori assumptions.

Consensus control of multi-agent systems with delays

&lt;p&gt;This paper concerns the consensus problem of linear time-invariant multi-agent systems (MASs) with multiple state delays and communicate delays. Consensus control is widely applied in spacecraft formation, sensor networks, robotic manipulators, autonomous vehicles, and others. By introducing a linear transformation, the consensus problem of the delayed MAS under an undirected network was converted into a robust asymptotic stability problem associated with the eigenvalues of the normalized Laplacian matrix of the network. By means of the argument principle and optimization technologies, a numerical controller design method was presented for the delayed MAS to reach consensus. The effectiveness of the proposed approach was illustrated by some numerical examples. The proposed approach may be applied to multi-agent systems with distributed delays.&lt;/p&gt;

On the robustification of digital event-based stabilizers for nonlinear time-delay systems

In this paper, the robust stabilization problem by means of quantized sampled-data event-based (QSE) controllers is investigated for nonlinear systems affected by state delays and unknown disturbances. In particular, a methodology for the design of robust QSE stabilizers is provided for control-affine nonlinear systems affected by unknown actuation disturbances and unknown measurement errors. Firstly, the notion of Steepest Descent Feedback (SDF), continuous or not, is suitably revised in order to deal with the robustification of event-based controllers. Then, Input-to-State Stability (ISS) redesign methodologies are used to provide the robustification term which is added to the SDF at hand in order to arbitrarily attenuate the effects of unknown external disturbances affecting the considered control scheme. A spline approximation approach is used in order to cope with the problem of the possible non-availability in the buffer of suitable past values of the system state required for the correct application of the proposed robust QSE controller. It is proved that there exist a suitably fast sampling and an accurate quantization of the input/output channels such that: the robust QSE implementation of SDFs, continuous or not, ensures the semi-global practical stability of the related closed-loop system, regardless of the above disturbances, provided that the observation errors affects marginally the new added control term. The stabilization in the sample-and-hold sense theory is used as a tool to prove the results. The provided results include the case of non-uniform quantization of the input/output channels and the case of aperiodic sampling. Applications are presented in order to validate the results.

Robust Stabilization of Time-Varying Nonlinear Systems With Time-Varying Delays: A Fully Actuated System Approach.

A general time-varying nonlinear uncertain system with time-varying delays is proposed, which is composed of two subsystems: one is an uncertain fully actuated subsystem representing the controllable part in the system, the other is an isolated globally uniformly asymptotically (GUA) stable autonomous subsystem which represents the uncontrollable part in the system. Both the single-order fully actuated system (FAS) and the multiorder FAS representations of the controllable subsystem are introduced. The problem of robust stabilization of such a compound system with full-state feedback can be converted into an input-to-state GUA stabilization problem of the fully actuated subsystem, which is solved for both types of single- and multiorder FASs with very general assumptions on the uncertain perturbed functions. Under certain conditions, the solution reduces to that for robust stabilization with partial-state feedback, and naturally reduce to that for robust stabilization of FASs. Two illustrative examples demonstrate both the effect and the application procedure of the proposed robust stabilization approach.

Cooperative robust output regulation for a class of nonlinear multi-agent systems over jointly connected switching networks

In this paper, we consider the cooperative robust output regulation problem for a class of nonlinear multi-agent systems over jointly connected switching networks. First, by attaching each subsystem with an input driven filter, we obtain an extended system. Second, by integrating the distributed observer approach and the distributed internal model approach, we convert the cooperative output regulation problem of the original system into a distributed robust stabilisation problem of an augmented error system which is also a multi-agent system. Finally, we solve the original problem by stabilising the augmented error system via a distributed output feedback control law.

Robust dynamic event‐triggered control of saturated nonlinear systems using reinforcement learning

AbstractWe develop a robust dynamic event‐triggered control (ETC) law for asymmetrically input‐saturated nonlinear systems having matched disturbances. Initially, by constructing a novel cost function for the associated nominal system, we transform the constrained robust stabilization problem into an unconstrained optimal control problem. Then, we propose a dynamic event‐triggering rule for improving the performance in reducing the computational burden. Based on such a dynamic triggering rule, we present the event‐triggered Hamilton‐Jacobi‐Bellman equation (ET‐HJBE). To solve the ET‐HJBE, we employ a critic approximator with its parameters being updated in the reinforcement learning framework. After that, we apply Lyapunov's direct method to prove uniform ultimate boundedness of the closed‐loop system and the critic approximator's parameter estimation error. Finally, we provide two nonlinear plants to validate the present dynamic ETC law.

Robust stabilization of LTI negative imaginary systems using the nearest negative imaginary controller

AbstractThis paper considers the problem of robust stabilization of linear time‐invariant systems with respect to unmodelled dynamics and structure uncertainties. To that end, a methodology to find the nearest negative imaginary system for a given non‐negative imaginary system is presented first. Then, this result is employed to construct a near optimal linear quadratic Gaussian controller achieving desired performance measures. The problem is formulated using port‐Hamiltonian method and the required conditions are defined in terms of linear matrix inequalities. The technique is presented using the fast gradient method to solve the problem systematically. The designed controller satisfies a negative imaginary property and guarantees a robust feedback loop. The effectiveness of the approach is demonstrated by a simulation on a numerical example.