Impulsive Dynamical Systems Research Articles

Fixed/predefined-time stability and designing of terminal sliding mode control of impulsive dynamical systems

The contribution of the present work is two-fold. Firstly, some results on the predefined and fixed-time stability of non-linear impulsive systems are derived. Impulse-dependent sufficient conditions are derived for predefined-time estimation of settling-time under the influence of stabilising impulses. In contrast, a fixed-time estimate of the settling-time is obtained for destabilising impulses. Secondly, terminal sliding mode (TSM) control is designed in the presence of hybrid (continuous and impulsive) matched disturbances for n-dimensional systems. It shows that the trajectories can reach the sliding surfaces in fixed-time and thus will stay on it after that under the influence of the proposed TSM. Thus, the system states will converge to the origin in a fixed-time. Finally, three examples, which also consist of the stability of Cohen-Grossberg BAM neural networks, are provided to justify the proposed results numerically.

A novel finite-time stability criteria and controller design for nonlinear impulsive systems

The issue of a novel finite-time stability and stabilization design for a class of nonlinear impulsive systems is discussed in this paper. In previous finite-time control designs for impulsive systems, the convergence rate of these control strategies is even less rapid than the exponential convergence rate when the initial state is distant from the origin. To overcome this problem, two sufficient conditions for the novel finite-time stability of impulsive systems are presented, in which the stabilizing impulses and the destabilizing impulses are considered, respectively. Meanwhile, the upper bound of the settling-time is evaluated. In addition, combining Lyapunov functions theory with impulsive control, we design a controller for impulsive dynamical systems to satisfy the novel finite-time stability. Finally, two simulation examples are given, in which the first example demonstrates the superiority of the proposed finite-time stability criterion for nonlinear impulsive systems by comparing it with traditional finite-time stability, and the second example verifies the effectiveness of the presented controller.

Fixed‐time stability of nonlinear impulsive systems: Sufficient criteria and necessary condition

AbstractThis article explores the criteria for fixed‐time stability (FxTS) within nonlinear impulsive dynamical systems, encompassing both stabilizing and destabilizing impulses. Initially, employing the Lyapunov method, the article delineates a criterion for FxTS, particularly when impulsive sequences are delineated by an average impulsive interval. Following this, the article innovatively applies two integral inequalities to introduce an optimized criterion for uniform impulsive sequences, evidencing its lesser conservativeness relative to the initial criterion. Moreover, this article derives a necessary condition for dynamical systems subjected to destabilizing impulses. Intriguingly, the investigation reveals the existence of a minimal threshold for the maximum impulsive interval, below which the system cannot achieve FxTS. This result elucidates why existing literature uniformly imposes a specific condition on the impulsive interval for destabilizing impulses. Finally, the efficacy of the proposed theory is underscored through numerical examples.

ADP-Based Event-Triggered Constrained Optimal Control on Spatiotemporal Process: Application to Temperature Field in Roller Kiln.

The precise control of the spatiotemporal process in a roller kiln is crucial in the production of Ni-Co-Mn layered cathode material of lithium-ion batteries. Since the product is extremely sensitive to temperature distribution, temperature field control is of great significance. In this article, an event-triggered optimal control (ETOC) method with input constraints for the temperature field is proposed, which takes up an important position in reducing the communication and computation costs. A nonquadratic cost function is adopted to describe the system performance with input constraints. First, we present the problem description of the temperature field event-triggered control, where this field is described by a partial differential equation (PDE). Then, the event-triggered condition is designed according to the information of system states and control inputs. On this basis, a framework of the event-triggered adaptive dynamic programming (ETADP) method that is based on the model reduction technology is proposed for the PDE system. A critic network is used to approach the optimal performance index by a neural network (NN) together with that an actor network is used to optimize the control strategy. Furthermore, an upper bound of the performance index and a lower bound of interexecution times, as well as the stabilities of the impulsive dynamic system and the closed-loop PDE system, are also proved. Simulation verification demonstrates the effectiveness of the proposed method.

Attracting sets of impulse-perturbed heat equation in the space of continuous functions

The paper deals with the impulsive infinite-dimensional problem generated by solutions of the thermal conductivity equation under the condition of impulse ”pumping” of heat. Moments of impulses are not fixed and are determined by the amount of total heat in the system. It is proved that such a problem generates impulsive dynamical system in the space of continuous functions and its ω-limits sets are investigated.

New predefined-time stability results of impulsive systems with time-varying impulse strength and its application to synchronization of delayed BAM neural networks

In this paper, the predefined-time synchronization of BAM neural networks with hybrid impulsive effects and time-varying delays is explored. First, based on the improved Lyapunov function method, two novel predefined-time stability lemmas of impulsive dynamical systems are given, in which the derivative of Lyapunov function can be negative definite or indefinite. Second, different from previous studies on constant impulse strength, we consider the impulse strength as a time-varying function, which can take different values at different moments and allow for the coexistence of both stabilizing and destabilizing impulses simultaneously. Then, two novel controllers are designed, and some sufficient conditions are derived to ensure predefined-time synchronization of the established system. Finally, the effectiveness of the obtained criteria is verified by a numerical simulation. The results show that the synchronized time can be adjusted according to actual needs and does not depend on the initial values and parameters of the system.

Model-based neuroadaptive event-triggered tracking consensus control for nonlinear multiagent systems with input delay

In this article, a neuroadaptive event-triggered control methodology is proposed to tackle the leader-following tracking consensus issue of uncertain nonlinear multiagent systems (MASs) with input delay and external disturbances. The proposed approach incorporates radial bias function neural networks (RBF NNs) and the integral compensation technique, effectively addressing the issues of nonlinear uncertainty and input delay, respectively. For the sake of reducing the transmission of information, we adopt the strategy that the neural network (NN) weight update law is only changed at the event-triggered instant, and a novel adaptive model and related controller are constructed. Simultaneously, this paper establishes an impulsive dynamic system to analyze the stability of the closed-loop system by extending the Lyapunov theorem to continuous and reset dynamics. Sufficient conditions for achieving leader-following tracking consensus are derived without the Zeno behavior. Finally, a numerical example is presented to illustrate the validity of the proposed method.

ω-Limit Sets of Impulsive Semigroups for Hyperbolic Equations

In this paper, we investigate the qualitative behavior of an evolutionary problem consisting of a hyperbolic dissipative equation whose trajectories undergo instantaneous impulsive discontinuities at the moments when the energy functional reaches a certain threshold value. The novelty of the current study is that we consider the case in which the entire infinite-dimensional phase vector undergoes an impulsive disturbance. This substantially broadens the existing results, which admit discontinuities for only a finite subset of phase coordinates. Under fairly general conditions on the system parameters, we prove that such a problem generates an impulsive dynamical system in the natural phase space, and its trajectories have nonempty compact ω-limit sets.

Novel adaptive synchronization in finite-time and fixed-time for impulsive complex networks with semi-Markovian switching

This paper intensively studied the finite-time (FNT) and fixed-time (FXT) synchronization issues for complex networks (CNs) with semi-Markovian switching and impulsive effect. The impulses are assumed to be independent of the semi-Markovian switching. Firstly, a unified FNT and FXT stability criterion of impulsive dynamical system with time-varying delays is extended by comparison principle. Secondly, two novel hybrid control schemes, which are composed of adaptive gain and switching state-feedback are proposed. Thirdly, by employing Kronecker product, Lyapunov-Krasovskii functional and inequality technique, FNT and FXT synchronization criteria for impulsive CNs with semi-Markovian switching are presented in a set of low-dimensional linear matrix inequalities, and the settling times are computed respectively. Finally, simulations are given to verify the proposed adaptive FNT and FXT synchronization criteria.

Lyapunov-based stability of time-triggered impulsive logical dynamic networks

In this paper, we consider the stability of impulsive logical dynamic systems (ILDNs) from two aspects: impulsive disturbance and impulsive control. The existing results on the stability of ILDNs only consider the stability of ILDNs under a given impulsive instant sequence (IIS), which has some limitations and motivates us to consider the stability of ILDNs under any IIS. By constructing a merged ILDN, under the assumption that the non-impulsive process and impulsive process are all globally stable, a necessary and sufficient condition on the stability of ILDNs under any IIS is proposed at first. Unfortunately, the obtained result is too restrictive, and in practice, it is not common that a stable LDN is still stable under any IIS. The fact is that for any stable LDN, there exist some IISs such that its stability is destroyed, and these IISs are called impulsive disturbances; for any unstable LDN, there exist some IISs such that the stability can be achieved, and these IISs are called impulsive control. To investigate the stability of ILDNs, the concept of average impulsive interval is first introduced to ILDNs, and several sufficient conditions are proposed to ensure the stability of LDNs under the time-triggered IISs with the property of average impulsive interval. Moreover, the obtained results are applied to the set stability of ILDNs.

Fixed-time stability of Cohen-Grossberg BAM neural networks with impulsive perturbations

This article concerns the problem of fixed-time stability (FXTS) of a Cohen-Grossberg bidirectional associative memory neural network (CGBAMNN) with destabilizing impulsive effects. A novel sufficient condition for the impulsive dynamical systems (IDSs) to be FXTS for destabilizing impulses is obtained. Different from the usual Lyapunov inequality for FXTS of IDSs, we have applied a new Lyapunov inequality to obtain the results under impulsive perturbations. Based on the average impulsive interval (AII) and the comparison principle, we have derived the results of this paper. Two types of continuous controllers: one with signum terms and another without signum terms, based on a new Lyapunov inequality, FXTS of CGBAMNN have been studied. The settling-time functions obtained in this article depend on the parameters of the impulsive sequences. Finally, two numerical examples, one is a cyber-physical system with deception attacks and another is a neural network, are given to validate the efficiency of our obtained theoretical results.

Impulsive Dirac system on time scales

UDC 517.9 We consider an impulsive Dirac system on Sturmian time scales. An existence theorem is given for this system. А maximal, minimal and self-adjoint operators generated by the impulsive dynamic Dirac system are constructed. We also construct the Green function for this problem. Finally, an eigenfunction expansion is obtained.

Event-Triggered Optimal Control for Temperature Field of Roller Kiln Based on Adaptive Dynamic Programming.

Temperature field control is crucial for the comprehensive performance of Ni-Co-Mn layered cathode material that is the most important part of lithium-ion batteries. Starting from the aspect of a class of distributed parameter systems described by highly dissipative partial differential equations (PDEs), an event-triggered optimal control (ETOC) method based on adaptive dynamic programming (ADP) for the roller kiln temperature field is proposed. First, we formulate the event-triggered control problem of the temperature field under the general framework of PDE systems. Then, an event-triggered condition is designed based on the stability of the closed-loop PDE system, which also guarantees the upper bound of the performance index. Subsequently, ADP technology is adopted to realize the ETOC, where the critic network is employed to approximate the optimal value function. Since the studied system can be regarded as an impulsive dynamic system with flow dynamics and jump dynamics simultaneously, the stability of the impulsive dynamic system combined with the ADP-based closed-loop PDE system is proved. Finally, simulation results on the temperature field verify the effectiveness of the proposed method.

On the solution of the Cayley impulsive dynamic control systems

On the solution of the Cayley impulsive dynamic control systems

Fixed-time synchronization of delayed memristive neural networks with impulsive effects via novel fixed-time stability theorem

In this study, the fixed-time synchronization (FXTS) of delayed memristive neural networks (MNNs) with hybrid impulsive effects is explored. To investigate the FXTS mechanism, we first propose a novel theorem about the fixed-time stability (FTS) of impulsive dynamical systems, where the coefficients are extended to functions and the derivatives of Lyapunov function (LF) are allowed to be indefinite. After that, we obtain some new sufficient conditions for achieving FXTS of the system within a settling-time using three different controllers. At last, to verify the correctness and effectiveness of our results, a numerical simulation was conducted. Significantly, the impulse strength studied in this paper can take different values at different points, so it can be regarded as a time-varying function, unlike those in previous studies (the impulse strength takes the same value at different points). Hence, the mechanisms in this article are of more practical applicability.

Intelligent control of convergence rate of impulsive dynamic systems affected by nonlinear disturbances under stabilizing impulses and its application in Chua’s circuit

This paper investigates the variable convergence rate stability and variable convergence rate stabilization of impulsive dynamic linear systems with stabilizing impulses affected by nonlinear disturbances. The eigenvalues (poles) of the system state are closely related to the convergence or divergence rate of the system. Sufficient conditions for the variable convergence rate stability are obtained by using the generalized pole placement idea and the method of system transformation. By designing a memoryless state feedback controller, sufficient conditions of variable convergence rate stabilization are obtained, ensuring the asymptotic stability of the target closed-loop system and accurately adjusting the system state’s convergence rate. An algorithm for adjusting the speed of system state convergence and its flow chart are designed by referring to the C programming language. Combined with the variable convergence rate stabilization method, the intelligent control of system state convergence speed is realized at the operation level. As a representative example of chaotic systems, Chua’s circuit affected by impulses verifies the effectiveness of the variable convergence rate stabilization method.

Existence, stability and controllability of piecewise impulsive dynamic systems on arbitrary time domain

The main objective of this article is to establish the existence of solutions, stability, and controllability results for piecewise nonlinear impulsive dynamic systems on an arbitrary time domain. Using the Banach fixed point theorem, we prove the existence of a unique solution while by applying Schauder’s fixed point theorem, we prove the existence of at least one solution. Further, we establish the controllability results by converting the controllability problem into a fixed point problem of an operator equation in some suitable function space. Mainly, we used the fixed point theorems, Gramian type matrices, functional analysis, and time scales theory to establish these results. Since the problem is formulated by using the theory of time scales, therefore, the obtained results are true for the continuous-time domain, discrete-time domain, as well as any combination of these two, which shows that the obtained results are non-trivial and generalize the existing ones. In the last, we have given a simulated example for two different time domains to verify the obtained analytical results.

Finite-time stabilization of state dependent impulsive dynamical linear systems

The problem of finite-time stabilizing control design for state-dependent impulsive dynamical linear systems (SD-IDLS) is tackled in this paper. Such systems are characterized by continuous-time, linear, possibly time-varying, dynamics coupled with discrete-time, linear, possibly time-varying, dynamics. The continuous-time part determines the system evolution in any time interval between two consecutive resetting events, while the discrete-time part governs its instantaneous state jump whenever the system trajectory intersects a resetting set, i.e. a region of the state space assumed to be time-independent. By making use of a quadratic control Lyapunov function, the finite-time stabilization of SD-IDLS through a static output feedback control design is specifically discussed in this paper. A sufficient and constructive result is provided based on the conical hulls of the resetting set subregions and on some cone copositivity properties of the chosen control Lyapunov function. Such a result is based on the solution of a feasibility problem that involves a set of coupled Difference/Differential Linear Matrix Inequalities (D/DLMI), which is shown to be less conservative and more numerically amenable with respect to other results available in the literature. An example illustrates the effectiveness of the proposed approach.

A new H∞ control method of impulsive dynamical linear systems: H∞ control criterion constrained by convergence rate

AbstractIn this article, a new control criterion of impulsive dynamic linear systems is proposed, that is, control criterion based on convergence rate. The conclusion can not only satisfy the target system control criterion, but also reveal the dynamic performance index, such as the convergence rate of its state, which can achieve the purpose of accurate control and have certain anti‐interference ability. According to the relationship between the eigenvalues (poles) and performances of systems, the conditions of interval stability and interval stabilization are obtained via the idea of generalized pole placement and equivalent systems. Then, combined with the classical control criterion, control criterion constrained by convergence rate is investigated. Referring to the programming language, system eigenvalues adjustment algorithm is designed. Through the cooperation between the algorithm and the above criteria, the target system has certain anti‐interference ability and its state convergence speed is precisely controlled. Finally, the advantages mentioned above are illustrated by two examples.

Stabilizing control design for state-dependent impulsive dynamical linear systems

The stabilizing control design problem for state-dependent impulsive dynamical linear systems (SD-IDLS) is tackled in this paper. This class of systems consists of a continuous-time, linear time-invariant system combined with discrete-time linear time-invariant dynamics in a prescribed region of the state space. The former regulates the evolution of the system between any two consecutive resetting events, while the latter governs the instantaneous state jumps occurring whenever the system trajectory intersects a resetting set, which is a portion of the state space assumed to be time-independent. Stabilization of SD-IDLS through a state feedback control design is specifically discussed in this paper, by making use of a candidate quadratic control Lyapunov function. By considering the conical hulls of the resetting set subregions and imposing some cone copositivity properties on the chosen control Lyapunov function, a sufficient and constructive condition for the global asymptotic stabilization of SD-IDLS is provided. Such a result, based on the solution of a feasibility problem that involves a set of Linear Matrix Inequalities (LMIs), is shown to be less conservative and more numerically amenable with respect to other results available in the literature. An example illustrates the effectiveness of the proposed approach.