Generalized Sector Condition Research Articles

A Switching Memory-Based Event-Trigger Scheme for Synchronization of Lur'e Systems With Actuator Saturation: A Hybrid Lyapunov Method.

This article is concerned with the event-triggered synchronization of Lur'e systems subject to actuator saturation. Aiming at reducing control costs, a switching-memory-based event-trigger (SMBET) scheme, which allows a switching between the sleeping interval and the memory-based event-trigger (MBET) interval, is first presented. In consideration of the characteristics of SMBET, a piecewise-defined but continuous looped-functional is newly constructed, under which the requirement of positive definiteness and symmetry on some Lyapunov matrices is dropped within the sleeping interval. Then, a hybrid Lyapunov method (HLM), which bridges the gap between the continuous-time Lyapunov theory (CTLT) and the discrete-time Lyapunov theory (DTLT), is used to make the local stability analysis of the closed-loop system. Meanwhile, using a combination of inequality estimation techniques and the generalized sector condition, two sufficient local synchronization criteria and a codesign algorithm for the controller gain and triggering matrix are developed. Furthermore, two optimization strategies are, respectively, put forward to enlarge the estimated domain of attraction (DoA) and the allowable upper bound of sleeping intervals on the premise of ensuring local synchronization. Finally, a three-neuron neural network and the classical Chua's circuit are used to carry out some comparison analyses and to display the advantages of the designed SMBET strategy and the constructed HLM, respectively. Also, an application to image encryption is provided to substantiate the feasibility of the obtained local synchronization results.

Stability and stabilization for the hydraulic automatic gauge control system of cold rolling mill with time delay and saturation

This paper studies the stability and stabilization of hydraulic automatic gauge control (HAGC) systems with time-varying delay and actuator saturation. First, a mathematical model of HAGC systems is established considering the measurement delay and saturation factors. With the help of state transformation, the measurement delay is transformed into input delay and the generalized sector condition is adopted to deal with the saturation problem in HAGC systems. Then, a new augmented L–K functional is constructed to contain more delay information to reduce the conservativeness of the stability criteria. Furthermore, by combining the proposed L–K functional with some advanced inequalities, the stability conditions and controller are derived with the aid of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed control algorithm is verified by simulation results.

Stabilization of polytopic discrete-time varying systems with rate and magnitude saturating actuators and bounded disturbances

This study tackles the critical challenge of designing parameter-dependent controllers for the wide class of discrete-time polytopic systems under rate and magnitude saturating actuators. Such a class finds widespread use in diverse applications spanning from medicine to industrial engineering. Our central contribution lies in developing novel convex parameter-dependent state feedback controller synthesis conditions that ensure regional and input-to-state stability, effectively mitigating the adverse effects of rate and magnitude-saturating actuators. Our approach considers the ℓ2/ℓ∞ gain between disturbance input and controlled output, offering performance specifications and retaining validity for specific initial conditions and amplitude-limited input disturbances. Moreover, our methodology is highly adaptable and suitable for a broad spectrum of systems, including LPV/quasi-LPV and T–S fuzzy systems. We leverage the position-type feedback model with speed limitation (PMSL) and the generalized sector condition to derive our controller synthesis method, resulting in a parallel-distributed-compensation strategy under standard assumptions, ensuring practicality and applicability to diverse system requirements. To highlight the effectiveness of our approach, we present numerical examples for comparative evaluation concerning the existing literature. Furthermore, we validate our methodology through real-time experiments conducted on a nonlinear coupled tank system, providing concrete evidence of its efficacy and feasibility for real-world implementation.

Intermittent Sampled-Data Control for Local Stabilization of Neural Networks Subject to Actuator Saturation: A Work-Interval-Dependent Functional Approach.

This article is concerned with the local stabilization of neural networks (NNs) under intermittent sampled-data control (ISC) subject to actuator saturation. The issue is presented for two reasons: 1) the control input and the network bandwidth are always limited in practical engineering applications and 2) the existing analysis methods cannot handle the effect of the saturation nonlinearity and the ISC simultaneously. To overcome these difficulties, a work-interval-dependent Lyapunov functional is developed for the resulting closed-loop system, which is piecewise-defined, time-dependent, and also continuous. The main advantage of the proposed functional is that the information over the work interval is utilized. Based on the developed Lyapunov functional, the constraints on the basin of attraction (BoA) and the Lyapunov matrices are dropped. Then, using the generalized sector condition and the Lyapunov stability theory, two sufficient criteria for local exponential stability of the closed-loop system are developed. Moreover, two optimization strategies are put forward with the aim of enlarging the BoA and minimizing the actuator cost. Finally, two numerical examples are provided to exemplify the feasibility and reliability of the derived theoretical results.

Data-driven control of input saturated systems: a LMI-based approach

This paper addresses three complex control challenges related to input-saturated systems from a data-driven perspective. Unlike the traditional two-stage process involving system identification and model-based control, the proposed approach eliminates the need for an explicit model description. The method combines data-based closed-loop representations, Lyapunov theory, instrumental variables, and a generalized sector condition to formulate data-driven linear matrix inequalities (LMIs). These LMIs are applied to maximize the origin’s basin of attraction, minimize the closed-loop reachable set with bounded disturbances, and introduce a new data-driven ℓ2-gain minimization problem. Demonstrations on benchmark examples highlight the advantages and limitations of the proposed approach compared to an explicit identification of the system, emphasizing notable benefits in handling nonlinear dynamics.

Stability analysis of nonlinear fuzzy hybrid control systems subject to saturation and delays via step‐function method

AbstractWithin the framework of the step‐function method, the stability of a nonlinear fuzzy hybrid control system that incorporates both an impulsive controller and a continuous state feedback controller is investigated. Both the two controllers are assumed to be subject to both actuator saturation and time‐varying delays, which has been given scant attention, if any, in the existing studies. A new assumption is introduced in this article, thereby enabling the use of generalized sector conditions to tackle the double saturation, and the conservatism inherent in stability results is remarkably reduced owing to the improved step‐function approach employed. The stability theorem proposed in this article removes constraints imposed on the time delays of both controllers, which can be also applied to wider scopes of systems, encompassing hybrid control systems with both stabilizing and instabilizing impulses, systems with varying impulsive gain, and systems with Zeno behavior. Numerical simulations of stabilization for different systems by delayed saturated hybrid control have been conducted, which demonstrate the validity of the proposed theorems.

Bipartite Consensus of Heterogeneous Multi-Agents Under Input Saturation Over Signed Graphs

This brief addresses the problem of bipartite consensus for linear multi-agent systems (MASs) with heterogeneous dynamics susceptible to input saturation over a signed graph under antagonistic interactions. Prior to extending the findings to directed signed graphs, a theoretical examination of the bipartite consensus for undirected signed graphs is conducted. Input saturation is addressed by using a generalized sector condition. With the aid of the Lyapunov theory, it has been shown that for the MASs with heterogeneous dynamics stability and bipartite consensus can be accomplished. To the best of our knowledge, a bipartite consensus control approach for heterogeneous MASs with input saturation nonlinearity, connected via directed signed graphs, has been considered for the first time. The validity of the given results is demonstrated by a numerical example.

Discontinuous Event-Triggered Control for Local Stabilization of Memristive Neural Networks With Actuator Saturation: Discrete- and Continuous-Time Lyapunov Methods.

In this article, the local stabilization problem is investigated for a class of memristive neural networks (MNNs) with communication bandwidth constraints and actuator saturation. To overcome these challenges, a discontinuous event-trigger (DET) scheme, consisting of the rest interval and work interval, is proposed to cut down the triggering times and save the limited communication resources. Then, a novel relaxed piecewise functional is constructed for closed-loop MNNs. The main advantage of the designed functional consists in that it is positive definite only in the work intervals and the sampling instants but not necessarily inside the rest intervals. With the aid of extended reciprocally convex combination lemma, generalized sector condition, and some inequality techniques, two local stabilization criteria are established on the basis of both the discrete- and continuous-time Lyapunov methods. The proposed analysis technique fully takes advantage of the looped-functional and the event-trigger mechanism. Moreover, two optimization schemes are, respectively, established to design the control gain and enlarge the estimates of the admissible initial conditions (AICs) and the upper bound of rest intervals. Finally, some comparison results are given to validate the superiority of the proposed method.

Data-Driven Stabilization of Input-Saturated Systems

We provide a data-driven stabilization approach for input-saturated systems with formal Lyapunov guarantees. Through a generalized sector condition, we propose a convex design algorithm based on linear matrix inequalities for obtaining a regionally stabilizing data-driven static state-feedback gain. Regional, rather than global, properties allow us to address non-exponentially stable plants, thereby making our design broad in terms of applicability. Moreover, we discuss consistency issues and introduce practical tools to deal with measurement noise. Numerical simulations show the effectiveness of our approach and its sensitivity to the features of the dataset.

Local Output Feedback Stabilization of a Reaction–Diffusion Equation With Saturated Actuation

This article is concerned with the output feedback stabilization of a reaction–diffusion equation by means of bounded control inputs in the presence of saturations. Using a finite-dimensional controller composed of an observer coupled with a finite-dimensional state-feedback, we derive a set of conditions ensuring the stability of the closed-loop plant while estimating the associated domain of attraction in the presence of saturations. This set of conditions is shown to be always feasible for an order of the observer selected large enough. The stability analysis relies on Lyapunov functionals along with a generalized sector condition classically used to study the stability of linear finite-dimensional plants in the presence of saturations.

A Direct Parameter-Error Codesign Approach of Discrete-Time Saturated LPV Systems

Considering a discrete-time linear parameter-varying systems with input constraints, this article deals with the codesign of a parameter-dependent state-feedback controller and a new parameter-dependent event-triggering mechanism. Two independent event-triggering policies are introduced at the sensor node to economize the limited network resources. They indicate whether the current state or the current scheduling parameters should be transmitted to the controller or not. In this sense, the controller scheduling parameters can differ from those of the system, yielding a certain degree of robustness concerning parameter deviations. Sufficient conditions, given in terms of linear matrix inequalities, ensure the regional asymptotic stability of the closed loop. To formulated them, we use the Lyapunov theory along with the generalized sector condition. Moreover, we formulate a convex optimization procedure indirectly reducing the transmission activity over the network. The proposed methodology effectiveness is attested through numerical examples and comparisons with related works from the literature.

Synthesis of accelerated gradient algorithms for optimization and saddle point problems using Lyapunov functions and LMIs

This paper considers the problem of designing accelerated gradient-based algorithms for optimization and saddle-point problems. The class of objective functions is defined by a generalized sector condition. This class of functions contains strongly convex functions with Lipschitz gradients but also non-convex functions, which allows not only to address optimization problems but also saddle-point problems. The proposed design procedure relies on a suitable class of Lyapunov functions and, for a fixed convergence rate, is a convex semi-definite program in all but one scalar parameter. The proposed synthesis allows the design of algorithms that reach the performance of state-of-the-art accelerated gradient methods and beyond.

Design of Saturating State Feedback With Sign-Indefinite Quadratic Forms

In this article, we propose a novel class of piecewise smooth Lyapunov functions leading to linear-matrix-inequality-based stability/performance analysis and control design for linear systems with saturating inputs. We provide conditions for global properties, and also conditions for local properties and guaranteed estimates of the basin of attraction. The backbone of our result consists in using quadratic forms with constant matrices that are not necessarily sign definite, thereby providing additional degrees of freedom. Using generalized sector conditions involving the dead-zone nonlinearity and its derivative, we formulate convex optimization conditions to verify their positivity in the region of interest. Several numerical examples with connections to existing results illustrate the potential behind our novel construction.

Local Stabilization for Multiple Input-Delay Systems Subject to Saturating Actuators: The Continuous-Time Case

In this article, the local stabilization problem is dealt with for a class of continuous-time multiple input-delay systems subject to saturating actuators. Using the generalized sector conditions and the piecewise Lyapunov–Krasovskii functional, and carrying out rigorous mathematical deduction, a sufficient condition is established under which the closed-loop dynamics is exponentially stable for admissible initial conditions. Subsequently, the explicit characterization of controller gains is obtained in terms of the solvability of linear matrix inequalities. The special cases concerning the constant and single delays are also discussed. Moreover, optimization problems are proposed to maximize the estimate of the domain of attraction. Finally, two examples are given to show the effectiveness and advantages of the obtained results.

Regional T-S Model-based Attitude Tracking Control of a Quadrotor with Input Saturation and External Disturbances

This paper presents a model reference attitude tracking controller design for a quadrotor unmanned aerial vehicle subject to saturated actuators and external disturbances. The dynamical nonlinear model of the quadrotor's attitude is represented by an uncertain-like Takagi-Sugeno model, with exact matching on a compact subset of the state space. The generalized sector condition is employed to deal with the saturated inputs of the quadrotor. LMI conditions are derived for the design of the proposed tracking controller from a quadratic Lyapunov function, together with a performance index used to minimize the L2-norm transfer between the disturbances and the state tracking errors. Because of the input saturation and the validity domain of the Takagi-Sugeno model, the obtained results only hold regionally and an optimization procedure to estimate the closed-loop tracking domain of attraction is proposed. Simulation results are provided to illustrate the effectiveness of the proposed design methodology.

Robust Fault Detection for Uncertain Delayed Systems With Measurement Outliers Under Stochastic Communication Protocol

In this paper, the robust fault detection (RFD) problem is studied for uncertain networked systems with time delay and measurement outliers under limited communication condition, where the time delay is presumed to occur randomly and the occurrence probability is considered to be uncertain. Specifically, in order to reduce the communication burden, the stochastic communication protocol (SCP) is introduced to adjust the transmission of measurement signals. Moreover, a fault detection filter (FDF) with saturation constraints is constructed to achieve the purpose of properly eliminating possible measurement outliers. Subsequently, a generalized sector condition is utilized to derive the stability criteria of the system on the basis of appropriate Lyapunov functional. In addition, a traditional FDF is also designed to compare with the saturation-constrained FDF. It is shown that the FDF with saturation constraints can properly avoid the influence of outliers on the detection effect. Finally, two simulations are presented to show the superiority and the practicality of the developed saturation-constrained fault detection (FD) filtering algorithm.

Observer-Based Control of LPV Systems with Input Delay and Saturation and Matched Disturbances via a Generalized Sector Condition

This paper examines the control design for parameter-dependent input-delay linear parameter-varying (LPV) systems with saturation constraints and matched input disturbances. A gain-scheduled dynamic output feedback controller, coupled with a disturbance observer to cancel out input disturbance effects, was augmented with an anti-windup compensator to locally stabilize the input-delay LPV system under saturation, model uncertainty, and exogenous disturbances. Sufficient delay-dependent conditions to asymptotically stabilize the closed-loop system were derived using Lyapunov-Krasovskii functionals and a modified generalized sector condition to address the input saturation nonlinearity. The level of disturbance rejection was characterized via the closed-loop inducedL2-norm of the closed-loop system in the form of linear matrix inequality (LMI) constraints. The results are examined in the context of the mean arterial pressure (MAP) control in the clinical resuscitation of critical hypotensive patients. The MAP variation response to the injection of vasopressor drugs was modeled as an LPV system with a varying input delay and was susceptible to model uncertainty and input/output disturbances. A Bayesian filtering method known as the cubature Kalman filter (CKF) was used to estimate the instantaneous values of the parameters. The varying delay was estimated via a multiple-model approach. The proposed input-delay LPV control was validated in closed-loop simulations to demonstrate its merits and capabilities in the presence of drug administration constraints.

Aperiodic sampled-data MPC strategy for LPV systems

This paper addresses the design of a sampled-data model predictive control (MPC) strategy for linear parameter-varying (LPV) systems. A continuous-time prediction model, which takes into account that the samples are not necessarily periodic and that plant parameters vary continuously with time, is considered. Moreover, it is explicitly assumed that the value of the parameters used to compute the optimal control sequence is measured only at the sampling instants. The MPC approach proposed by Kothare et al. [1], where the basic idea consists in solving an infinite horizon guaranteed cost control problem at each sampling time using linear matrix inequalities (LMI) based formulations, is adopted. In this context, conditions for computing a sampled-data stabilizing LPV control law that provides a guaranteed cost for a quadratic performance criterion under input saturation are derived. These conditions are obtained from a parameter-dependent looped-functional and a parameter-dependent generalized sector condition. A strategy that consists in solving convex optimization problems in a receding horizon policy is therefore proposed. It is shown that the proposed strategy guarantees the feasibility of the optimization problem at each step and leads to the asymptotic stability of the origin. The conservatism reduction provided by the proposed results, with respect to similar ones in the literature, is illustrated through numerical examples.

Controller design for output constrained thyristor controlled series capacitor (TCSC) of time-delayed power system

Abstract Thyristor Controlled Series Capacitor (TCSC) is employed as actuator in an interconnected power system using Supplementary Damping Controller (SDC) to enhance the power transfer capabilities between areas as well as damp out the Inter-Area Low-Frequency (IALF) oscillations by varying the impedance of transmission lines. The time-varying delays in the feedback loop and asymmetric saturation limits at the output of TCSC may reduce the performance of the designed controller and lead to closed-loop instability if these are not considered in the process of controller design. Usually, a Minimum Absolute Saturation Bound technique (MASB) is used to convert asymmetric saturation limits into symmetric one. However, such consideration provides an apparent conservative and degrades the performance of the control system. To reduce the conservative in the control design process, a Normalized Saturation Bound (NSB) technique is used in this paper to convert asymmetric saturation limits of TCSC of time-delayed power system. The L-K functional and generalized sector conditions are utilized in the proposed controller design process to compensate the effect of time-varying delay and converted symmetric saturation limits. Sufficient conditions required for controller design are formulated in LMI form. 2-area 4-machine power model is used to verify the performance of the designed controller. From the simulation results, it is observed that the designed controller is giving superior performance in the present of time-varying delays and asymmetric saturation as compared to the designed controller using MASB technique.

Analysis and experimental application of a dead‐time compensator for input saturated processes with output time‐varying delays

Dead-time compensators (DTCs) are a family of classical controllers derived from the Smith Predictor (SP). Their main characteristic is that they explicitly employ the model of the open-loop process to feedback a predicted value of the non-delayed system, thus obtaining \textit{compensation} of the delay. Such a perfect compensation is not achievable in the case of time-varying delays. In this paper, we address stability analysis of a DTC structure in this situation, in addition to considering saturating actuators and disturbances of limited energy. Specific challenges related to the DTC closed loop are taken into account in the developed theoretical conditions, which are expressed in terms of linear matrix inequalities (LMIs) by using an adequate Lyapunov-Krasovskii functional (LKF) and generalized sector conditions. Furthermore, a new approach for the definition of the set of initial conditions in an augmented space in conjunction with the LKF is presented. Besides theoretical innovations, practical discussion about the relation between the tuning of DTC controllers and robustness for this class of systems is presented through numerical examples. An experimental application on a neonatal incubator prototype is carried out to emphasize the effectiveness of the results.