Adaptive dynamic optimal control for triggered networked switched systems under dual‐ended denial‐of‐service attacks

This study centers on the issue of finite‐time event‐triggered bumpless transfer (BT) control of switched systems. The aim is to suppress the undesirable control jumps at both switching and triggering time, and guarantee the finite‐time stability of switched systems. First, the property of BT is described from its original intention. Then, by co‐design of an improved switching function, an event‐triggered strategy combined with a series of controllers to achieve this objective. Also, the Zeno behavior is excluded. Further, a criterion to guarantee the BT property and the finite‐time stability under event‐triggered mechanism is established. Finally, a turbofan engine control system is taken as an example to testify the validity of the presented control scheme.

Section: Introductionmentioning

confidence: 99%

Finite‐time event‐triggered bumpless transfer control for switched systems

Wang

Zhao

et al. 2022

“…Networked switched systems (NSSs) not only consist of a series of subsystems and a logic strategy, but also are combined with network transmission. It should be pointed out that network‐induced imperfections may destabilize the NSSs, since NSSs depend on the network to transmit information of switching signal and system state 25‐31 . Several approaches for stability analysis of NSSs subject to network‐induced imperfections have been well developed.…”

Section: Introductionmentioning

confidence: 99%

Stability of networked switched systems in the presence of denial‐of‐service attacks

Zuo

Wang

et al. 2022

This article is concerned with the stability issue of networked switched systems which consist of only unstable subsystems subject to Denial of Service (DoS) attacks. The stability analysis of networked switched systems in the presence of DoS attacks under state‐dependent switching is first presented. It is shown that the derived restrictions which differ from those in the existing work are imposed on DoS attack model. Specifically, the proposed conditions to characterize the duration and frequency of DoS attacks are state‐dependent and mode‐dependent. As a result, the ratio of total duration of DoS attack to the operating time of switched systems is higher than the previous literature. Furthermore, our result is extended to the stability of networked switched affine systems in the presence of DoS attacks. In the end, two simulation examples are given to demonstrate the effectiveness of our work.

“…4 The main task of the optimal control problem is to choose a control input such that a given objective function is minimized or maximized for a given dynamical system. 5,6 The classical optimal control theory is based on the Pontryagin's maximum principle or the dynamic programming method. 7,8 The Pontryagin's maximum principle presents a necessary condition for optimality.…”

Section: Introductionmentioning

confidence: 99%

“…During the past two decades, optimal control of nonlinear systems have been attracting many researchers from various fields in science and engineering 4 . The main task of the optimal control problem is to choose a control input such that a given objective function is minimized or maximized for a given dynamical system 5,6 . The classical optimal control theory is based on the Pontryagin's maximum principle or the dynamic programming method 7,8 .…”

Section: Introductionmentioning

confidence: 99%

Optimal control of nonlinear systems with integer‐valued control inputs and stochastic constraints

Zhang

Cheng

2022

Practical industrial process is usually a dynamic process including uncertainty. Stochastic constraints can be used for industrial process modeling, when system sate and/or control input constraints cannot be strictly satisfied. Thus, optimal control of nonlinear systems with stochastic constraints can be available to address practical industrial process problems with integer‐valued control inputs. In general, obtaining an analytical solution of this optimal control problem is very difficult due to the discrete nature of the control inputs and the complexity of stochastic constraints. To obtain a numerical solution, this problem is formulated as a finite dimensional static constrained optimization problem. First, the integer‐valued control input is relaxed into a continuous‐valued control input by imposing a penalty term on the objective function. Convergence results show that the relaxed solution obtained is an integer solution as long as the penalty parameter is sufficiently large. In addition, it should be noted that no any constraint is introduced in the novel relaxation technique, which can effectively avoid introducing any extra extreme point for the original optimal control problem. Next, a novel smooth approximation function is used to construct a subset of feasible region for this optimal control problem. It is proved that the smooth approximation can converge uniformly to the stochastic constraints as the adjusting parameter reduces. Following that, a numerical computation method is proposed for solving the original optimal control problem. Finally, in order to illustrate the effectiveness of the proposed method, an electric vehicle energy management problem is extended by considering some stochastic constraints. The numerical results show that the proposed method is less conservative compared with the existing typical approaches and can obtain a stable and robust performance when considering the initial condition small perturbations.