State-dependent Impulsive Systems Research Articles

A state-dependent impulsive system with ratio-dependent action threshold for investigating SIR model

<abstract><p>In general, there is an imperative to amalgamate timely interventions and comprehensive measures for the efficacious control of infectious diseases. The deployment of such measures is intricately tied to the system's state and its transmission rate, presenting formidable challenges for stability and bifurcation analyses. In our pursuit of devising qualitative techniques for infectious disease analysis, we introduced a model that incorporates state-dependent transmission interventions. Through the introduction of state-dependent control, characterized by a non-linear action threshold contingent upon the combination of susceptible population density and its rate of change, we employ analytical methods to scrutinize various facets of the model. This encompasses addressing the existence, stability, and bifurcation phenomena concerning disease-free periodic solutions (DFPS). The analysis of the established Poincaré map leads us to the conclusion that DFPS indeed exists and maintains stability under specific conditions. Significantly, we have formulated a distinctive single-parameter family of discrete mappings, leveraging the bifurcation theorems of discrete maps to dissect the transcritical bifurcations around DFPS with respect to parameters such as $ ET $ and $ \eta_{1} $. Under particular conditions, these phenomena may give rise to effects like backward bifurcation and bistability. Through the analytical methodologies developed in this study, our objective is to unveil a more comprehensive understanding of infectious disease models and their potential relevance across diverse domains.</p></abstract>

Optimal control of a nonlinear state-dependent impulsive system in fed-batch process

Optimal control technique is crucial to improve the yield of microbial fermentation production. In this paper, we propose a nonlinear control system with state-dependent impulses, where the impulsive volume of feeding glycerol and the critical concentration of glycerol for occurring impulse are the control variables, to formulate 1,3-propanediol (1,3-PD) fed-batch production process. We also discuss a quantity of important properties for this control system. Then, we analyze the sensitivity of system state with respect to the kinetic parameters. We further propose a constrained optimal control model governed by the control system with state-dependent impulses. The existence of the optimal impulsive controls is established. For solving this problem, we utilize an exact penalty method to transform the problem into an optimization problem with only box constraints. Moreover, an improved differential evolution method is developed to seek the optimal impulsive strategy. Finally, numerical simulation results demonstrate that, by using the optimal impulsive strategies, final 1,3-PD concentration is considerably increased under the nominal parameter values and disturbances of kinetic parameters have significant effects on the optimal final 1,3-PD yield.

Stability analysis of state-dependent impulsive systems via a new two-sided looped functional

In this paper, the asymptotic stability of state-dependent impulsive systems is addressed by virtue of looped-functional approach. Firstly, based on B-equivalence method, a fixed-time impulsive comparison system is derived, which is B-equivalent with the original state-dependent impulsive system. Then the asymptotic stability criteria of state-dependent impulsive system are obtained by employing a new two-sided looped functional to analyze the comparison system with fixed-time impulses. The theoretical results are applied to Takagi-Sugeno (T-S) fuzzy impulsive control. The effectiveness of the proposed results is verified by two numerical examples.

Nonlinear state-dependent impulsive system and its parameter identification in microbial fed-batch culture

In fed-batch culture of glycerol to 1,3-propanediol by Klebsiella pneumoniae, glycerol and alkali are fed in batches into the bioreactor to provide sufficient nutrition and maintain a suitable environment for cells growth. In this paper, taking the feeding process as a state-dependent impulses process, a nonlinear state-dependent impulsive system is proposed to formulate the fed-batch process. Some important properties of the solution to the system are discussed, i.e., the existence, uniqueness and regularity of solution to the system and continuous dependence of the solution on initial value and parameters. Regarding the errors between the experimental results and calculated values as the performance index, a parameter identification model is presented. The identifiability of the parameter identification model is also proved. Finally, an improved particle swarm optimization (PSO) algorithm is constructed to seek the optimal parameters. Numerical results show that the nonlinear state-dependent impulsive system can be used to describe the fed-batch culture reasonably .

Nonlinear state-dependent impulsive system in fed-batch culture and its optimal control

In fed-batch culture, feeding substrates is to provide sufficient nutrition and reduce inhibitions simultaneously for cells growth. Hence, when and how much to feed substrates are important during the process. In this paper, a nonlinear impulsive controlls system, in which the volume of feeding is taken as the control function, is proposed to formulate the fed-batch fermentation process.In the system, both impulsive moments and jumps size of state are state-dependent. Some important properties of the system are investigated. To maximize the concentration of target product at the terminal time, an optimal control model involving the nonlinear state-dependent impulsive controlled system is presented.The optimal control problem is subject to the continuous state inequality constraint and the control constraint. The existence of optimal control is also obtained. In order to derive the optimality conditions, the optimal control model is transcribed into an equivalent one by treating the constraints. Finally, the optimality conditions of the optimal control model are obtained via calculus of variations.

Dynamical Behaviors for a Predator-Prey System with State-Dependent Impulsive Effects

With some theory about continuous and impulsive dynamical system, an impulsive model based on a special predator-prey system is considered. We assume that the impulsive effects occur when the density of the prey reaches a given value. For such a state-dependent impulsive system, the existence, uniqueness and orbital asymptotic stability of an order-1 periodic solution are discussed. Further, the existence of an order-2 periodic solution is also obtained, and persistence of the system is investigated.

The existence of viable trajectories in state-dependent impulsive systems

Suitable topological tools for studying the existence of viable and periodic viable trajectories in state-dependent impulsive differential equations and inclusions are provided. Some results based on the Ważewski retract method are applied. The techniques presented in the paper are illustrated with several examples.

Existence and stability of periodic solution of a Lotka–Volterra predator–prey model with state dependent impulsive effects

According to biological and chemical control strategy for pest, we investigate the dynamic behavior of a Lotka–Volterra predator–prey state-dependent impulsive system by releasing natural enemies and spraying pesticide at different thresholds. By using Poincaré map and the properties of the Lambert W function, we prove that the sufficient conditions for the existence and stability of semi-trivial solution and positive periodic solution. Numerical simulations are carried out to illustrate the feasibility of our main results.