Dynamic Output Feedback Controller Research Articles

A general dynamic output feedback control for rectangular nonlinear discrete-time descriptor Markov jump systems

This paper studies the dynamic output feedback (DOF) control problem (CP) for rectangular discrete-time descriptor Markov jump systems (RDDMJSs) with Lipschitz nonlinear terms. There is no restriction on the relationship between the number of system equations and the dimensions of states. First, according to designing general DOF controllers, the resulted closed-loop systems are converted into square DMJSs (SDMJSs). Then, a novel sufficient condition is proposed in terms of linear matrix inequality (LMI) based on the stochastic Lyapunov theory, S-procedure and with free matrices, which guarantees the stochastic admissibility and the existence and uniqueness of solution of the closed-loop systems. Furthermore, by utilising the matrix decoupling technique (MDT) and introducing relaxation matrices, the controller design algorithm is given, and the general DOF controllers with free dimensions are designed. Last, two numerical examples and a practical application are provided to demonstrate the validity and superiority of the proposed methods.

Adaptive event-triggered dynamic output feedback control for networked autonomous vehicles affected by signal quantization and actuator failures

In this paper, an event-triggered sliding-mode output feedback control (SMOFC) strategy with adaptive fault-tolerance is proposed to achieve path tracking for networked autonomous vehicles, considering the challenges posed by network communication and electric steering systems. Initially, signal quantization, external disturbances, and actuator faults are incorporated into the vehicle model. This incorporation enhances the designed controller’s robustness against a broader and more demanding range of driving scenarios. Subsequently, in situations where only output feedback is available, a dynamic output compensator is designed to reconstruct the unmeasurable vehicle state. Utilizing the reconstructed vehicle state, an event-triggered strategy is devised to alleviate the network burden and determine the minimum time between triggering events to prevent Zeno behavior. Furthermore, an adaptive mechanism is employed to estimate the actuator fault boundaries. The performance of the designed controller is evaluated through simulation instances.

Negative-imaginary systems theory-based output feedback control for satellite rendezvous

This article presents the development of a dynamic output feedback controller designed for a benchmark model of a satellite rendezvous system that has both uncertainties and external perturbations. The investigated method renders the controller-synthesised closed-loop rendezvous system into an α-strictly negative-imaginary system. The demonstration of robust stability for the satellite rendezvous system in the presence of uncertainties is achieved by employing the DC loop gain condition associated with negative-imaginary systems theory. Moreover, the closed-loop system, synthesised with negative-imaginary characteristics, demonstrates noteworthy time-domain performance. The simulation results of the article show the effectiveness of the output feedback control method in satellite rendezvous.

Robust model predictive control for polyhedral uncertain systems under relay and redundancy protocol

In networked systems, signal fading and packet loss occur due to limited bandwidth during signal transmission. To solve these problems, amplify-and-forward (AF) relay and redundant channels are considerd in the traditional robust model predictive control (RMPC) problem, and a novel design method for dynamic output feedback controller is propsoed in this paper. In addition to the min-max control method, the mathematical expectation is introduced to deal with the uncertainty of the system model and the randomness of the protocol parameters, sufficient conditions are established to guarantee the feasibility of the designed MPC scheme that ensures the robust stability of the closed-loop system. In terms of the solution to an auxiliary optimisation problem, an easy-to-implement MPC algorithm is proposed to obtain the desired sub-optimal control sequence as well as the upper bound of the quadratic cost function. Finally, a simulation example is shown to prove the effectiveness of the proposed RMPC strategy.

Composite Anti-Disturbance Control for Nonlinear Hidden Markov Jump Systems Under Replay Attacks: A Dynamic Output-Feedback Method.

This article is dedicated to researching the problem of composite anti-disturbance control for nonlinear hidden Markov jump systems, described by the interval type-2 Takagi-Sugeno fuzzy method, under replay attacks in the continuous-time domain. Based on dynamic output feedback control and disturbance observer, a fuzzy composite controller, following the core idea of nonparallel distribution compensation, is designed to compensate for the impact of multiple disturbances. For replay attacks, a multisensor scheme with the detection mechanism is introduced, enabling the studied systems to remain stable even under attacks. Afterward, with the aid of the Lyapunov stability theory, sufficient conditions for ensuring the stability of the resulting systems are deduced, and then the gains of the desired controller and disturbance observer are obtained. Finally, the rationality and effectiveness of the established method are demonstrated through simulation, as well as its superiority over the traditional Hinfty control method.

Dynamic output feedback model predictive control for polytopic uncertain systems under decode and forward cooperative relay protocol

This paper addresses the robust model predictive control (RMPC) problem for a class of polytopic uncertain systems under the decode and forward cooperative relay protocol (DFCP). In order to combat signal fading from sensors to controllers and improve communication reliability, spatial diversity is achieved through cooperative terminal relay signals. At each transmission instant, the terminal only selects a better signal for transmission and a switched system is constructed. The aim of this paper is to design a set of desired dynamic output feedback controllers in the framework of RMPC such that the switched system with the underlying DFCP is exponentially stable. By taking the influence of the randomness of DFCP derived from a three nodes model composed of DF relay, a new objective function based on the mathematical expectation of the traditional quadratic function of MPC is established. Then, the orthogonal complement technique is applied to handle the inherent couplings of variables to formulate a solvable optimisation problem. Moreover, the sufficient conditions are provided to guarantee the recursive feasibility of the MPC strategy and the stability of the established closed-loop system in terms of the average dwell time (ADT) method. Finally, three experiments are given to illustrate the effectiveness of the proposed method.

Sampled-Data H∞ Dynamic Output-Feedback Control for NCSs With Successive Packet Losses and Stochastic Sampling.

The problem of sampled-data H∞ dynamic output-feedback control for networked control systems with successive packet losses (SPLs) and stochastic sampling is investigated in this article. The aim of using sampled-data control techniques is to alleviate network congestion. SPLs that occur in the sensor-to-controller (S-C) and controller-to-actuator (C-A) channels are modeled using a packet loss model. Additionally, it is assumed that stochastic sampling follows a Bernoulli distribution. A model is established to capture the stochastic characteristics of both the SPL model and stochastic sampling. This model is crucial as it allows us to determine the probability distribution of the sampling interval between successive update instants, which is essential for stability analysis. An exponential mean-square stability condition for the constructed equivalent discrete-time stochastic system, which also guarantees the prescribed H∞ performance, is established by incorporating probability theory. The desired controller is designed using a step-by-step synthesis approach, which may offer lower design conservatism compared to some existing methods. Finally, our designed approach using a networked F-404 engine system model is validated and its merits relative to existing results are discussed. The proposed method is finally validated by employing a networked model of the F-404 engine system. Furthermore, the advantages of our method are presented in comparison to previous results.

Output-feedback controllers with guaranteed ℒ2-gain for continuous-time Lur'e systems using noncausal Zames–Falb multipliers

This paper focuses on the problem of dynamic output feedback control for continuous-time Lur'e systems with slope-bounded nonlinearities, particularly addressing the closed-loop L 2 gain. The synthesis framework is derived using integral quadratic constraints. The following contributions are highlighted: (i) assessment of stability and L 2 gain through causal, anticausal, and noncausal Zames–Falb multipliers; (ii) technical enhancements to improve efficiency and to reduce the conservativeness of two different classes of multipliers regarding the L 1 norm evaluation; (iii) the synthesis conditions are presented in terms of an iterative procedure based on linear matrix inequalities, allowing arbitrary order for both the controller and the multipliers. The proposed achievements are validated through numerical examples, demonstrating the efficacy and flexibility of the approach compared to existing methods in the literature.

Policy gradient methods for designing dynamic output feedback controllers

This paper proposes model-based and model-free policy gradient methods (PGMs) for designing dynamic output feedback controllers for discrete-time partially observable deterministic systems without noise. To fulfill this objective, we first show that any dynamic output feedback controller design is equivalent to a state-feedback controller design for a newly introduced system whose internal state is a finite-length input–output history (IOH). Next, based on this equivalence, we propose a model-based PGM and show its global linear convergence by proving that the Polyak–Łojasiewicz inequality holds for a reachability-based lossless projection of the IOH dynamics. Moreover, we propose a model-free implementation of the PGM with a sample complexity analysis. Finally, the effectiveness of the model-based and model-free PGMs is investigated through numerical simulations.

Event-triggered dynamic output-feedback control for LPV systems

This paper addresses the co-design of event-triggered dynamic output-feedback (DOF) control for discrete-time linear parameter-varying (LPV) systems. Two independent event-triggering schemes are introduced to determine when to transmit data from the sensor to the controller and from the controller to the actuator channels. Enhanced conditions employing linear matrix inequalities (LMIs) are derived to establish constructive criteria for simultaneously designing the gain-scheduled DOF controller and the triggering mechanisms, ensuring the asymptotic stability of the closed-loop LPV system's origin. Additionally, a convex optimisation problem is proposed to enlarge the inter-event sampling on the independent channels of sensor-to-controller and controller-to-actuator. Numerical examples are provided to illustrate the effectiveness of the proposed method.

Two channels event‐triggered robust H‐infinity control of Luire industrial cyber physical systems under data injection attacks

AbstractBy fully taking the effects of data injection attacks, nonlinear disturbances and limited communication resources, the stability of Lurie industrial cyber physical systems with the time‐varying delays is investigated. The two channels event‐triggered dynamic robust control (ERHIC) strategy is proposed for achieving the stability of systems. On one hand, a dynamic output feedback controller is designed to ensure the stable operation of the system under attacks. On other hand, the measurement channel and the control channel (two channels) event‐triggered mechanisms are designed to improve the utilization rate of system resources. The simulation results with the size of capacitor voltage and inductor current under data injection attacks as the object verity the correctness and the effectiveness of the proposed two channels event‐triggered robust H‐infinity control method and the feasibility of the designed dynamic output feedback controller are verified by the simulation results.

Event‐triggered dynamic output feedback control for switched linear neutral systems under time‐varying delays and frequent asynchronism

Event‐triggered dynamic output feedback control for switched linear neutral systems under time‐varying delays and frequent asynchronism

Event‐triggered adaptive output feedback control of unmanned aerial vehicles under hybrid attacks

AbstractThis study addresses the adaptive dynamic output feedback (DOF) control for unmanned aerial vehicle systems subjected to hybrid attacks. These attacks are delineated by two Bernoulli variables, signifying denial‐of‐service (DoS) and deception attacks, respectively. In an effort to enhance energy efficiency and reduce communication costs in the presence of network delays, the study introduces an innovative probability event‐triggering mechanism (PETM). Subsequently, it crafts a DOF controller that operates based on the available measurement outputs. By harnessing Lyapunov stability theory, the study identifies sufficient conditions that guarantee the stability of the system's augmented dynamics. Finally, the efficacy and applicability of the proposed method are underscored through a case study on an unmanned aerial vehicle.

Dynamic output feedback control strategy for a satellite orbital model within negative-imaginary systems theory framework

This article presents the synthesis of a dynamic output feedback controller for a satellite orbital system confronted with uncertainties. The investigated method transforms the closed-loop system, synthesized by the controller, into an α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha $$\\end{document}-strictly negative-imaginary system. It utilizes the DC-loop gain condition associated with negative-imaginary systems theory to demonstrate robust stability of the satellite orbital system in the presence of uncertainties. Furthermore, the synthesized negative-imaginary closed-loop system exhibits notable time-domain performance. The numerical simulation outcomes presented in this article validate the investigated synthesis method.

Dynamic Output Feedback of Second-Order Systems: An Observer-Based Controller with Linear Matrix Inequality Design

This paper presents an observer-based dynamic output-feedback controller design procedure using linear matrix inequality (LMI) optimization for second-order systems with uncertainty and persistent perturbation in the states. Using linear-quadratic criteria, cost functions are minimized in a two-stage procedure to compute optimal state-feedback gains, and observer gains are coupled into a dynamic output-feedback optimal controller. The LMI set used in the two stages is matrix inversion free, a key issue for polytope formulation when uncertainty is present. The approach is tested in a mobile inverted pendulum robotic platform, and the effectiveness is verified in this underactuated and undesensed case.

Dynamic output feedback based fault tolerant control for continuous-time switched affine systems via reduced-order observer

In this study, the issue on dynamic output feedback fault-tolerant controller design is addressed for a class of continuous-time switched affine systems in the presence of actuator faults. The existence of affine terms gives rise to the lack of a common equilibrium point and further makes it more difficult to propose the desired output-feedback-based fault-tolerant control scheme. Firstly, the actuator fault estimation is achieved through a reduced-order observer design approach. Then, a kind of dynamic output feedback controller is constructed to perform the fault tolerance goal by utilizing fault estimation information. Moreover, the mode-dependent average dwell time switching constraint is borrowed to avoid the chattering owing to the high-frequency switching. The sufficient conditions with less conservative are derived to guarantee the practical exponential stability of closed-loop system with a prescribed L∞ gain. Finally, both the effectiveness and validity of the designed fault-tolerant control strategy are illustrated via a case study of a buck-boost DC-DC converter.

Parallel event-triggered dynamic output feedback control for nonlinear networked systems with randomly occurring multiple communication delays

This paper investigates the issue of parallel event-triggered (PET) dynamic output feedback control for networked control systems (NCSs) built by the discrete-time T–S fuzzy model. Initially, a novel PET dynamic output feedback controller is designed. Based on saving network resources and enhancing transmission efficiency, the PET strategy makes full use of relative and absolute triggering condition information. And the dynamic output feedback control can not only address unmeasurable states but also provide a better response to the internal information of the system. The random multiple communication delays and the ℓth-order Rice fading model with different channel coefficients, meanwhile, are both applied in the system. It is closer to the actual situation. Subsequently, new sufficient conditions of membership function dependence are proposed via the staircase function approximation method combined with Lyapunov stability. It guarantees that the system is exponentially mean square stable (EMSS) with H∞ performance. Ultimately, the presented results are validated using two examples. In the future, we will explore the correlative research of T–S fuzzy Markov jump NCSs.

Dissipative imitation learning for discrete dynamic output feedback control with sparse data sets

AbstractImitation learning enables synthesis of controllers for systems with complex objectives and uncertain plant models. However, ensuring an imitation learned controller is stable requires copious amounts of data and/or a known plant model. In this paper, we explore an input–output (IO) stability approach to imitation learning, which achieves stability with sparse data sets while only requiring coarse knowledge of the energy characteristics of the plant. A constrained optimization problem is developed, in which the controller learns to mimic expert data while maintaining stabilizing energy characteristics induced by the plant. While the learning objective is nonconvex, iterative convex overbounding (ICO) and projected gradient descent (PGD) are explored as methods to learn the controller. In numerical examples, it is shown that with little knowledge of the plant model and a small data set, the dissipativity constrained learned controller achieves closed loop stability and successfully mimics the behavior of the expert controller, while other methods often fail to maintain stability and achieve good performance.

Dynamic output feedback control of uncertain nonlinear systems based on co-design adaptive event-triggered scheme

This paper presents a framework to design a robust dynamic output feedback (DOF) controller for a class of nonlinear systems, based on the adaptive event-triggered control (AETC) method. The considered system contains parametric uncertainty and to design the event-triggered mechanism (ETM) Finite-gain L2 stability criteria are used. In this paper, a robust adaptive event-triggered mechanism (AETM) is first designed using a pre-designed controller. Then, in a co-design approach, the AETM and the DOF controller are designed together to increase the closed-loop performance. Indeed, the matrices of the DOF controller and the sufficient conditions for the AETM are obtained simultaneously. These conditions are represented as linear matrix inequalities (LMIs) and lead to a significant increase in the update interval. Moreover, the proposed design method guarantees the stability of the closed-loop system in the presence of the proposed triggering event. Finally, to illustrate the performance of the controller three examples are simulated.

Asynchronous control of switched systems with time-delay based on mode-dependent average dwell time

Switched system is a kind of important hybrid system, which is usually composed of finite subsystems and an organization switching rule. In the study of switched system, it is usually default that the subsystem and the sub-controller are switched synchronously. However, in practice, the switching of sub-controller often lags behind the subsystem, resulting in asynchronous switching between subsystem and sub-controller, which affects the stability of the system. To solve this problem, this paper discusses the asynchronous control problem of a class of time-varying delay switched systems based on mode-dependent average dwell time (MDADT). Firstly, by constructing a dynamic output feedback controller and using piecewise Lyapunov function, the sufficient conditions for exponential stability and H∞ performance of the closed-loop switching system are obtained. At the same time, the design algorithm of dynamic output feedback controller is given. Finally, a simulation of a switched system with two subsystems under ADT switching signal and MDADT switching signal is given, and the effectiveness of the proposed method is verified by comparison.