Publications

This article addresses the hybrid model predictive control of chiller systems via collaborative neurodynamic optimization. A mixed-integer optimization problem is formulated for the model predictive control of chiller systems to minimize power consumption, subject to various constraints including thermodynamic and energy-conservation constraints. It is then decomposed into a global and a binary optimization subproblem. A collaborative neurodynamic optimization approach is proposed to solve the subproblems sequentially. The approach is based on multiple pairs of projection neural networks and discrete Hopfield networks, assisted with a metaheuristic rule. The effectiveness of the approach is demonstrated through experiments based on the parameters and specifications of a chiller system.

This article is concerned with the H∞ cluster formation control of a multiagent system (MAS) with stochastic sampling in network environments. First, based on a directed communication topology with acyclic partition, agents are separated into several clusters. The agents moving in the same cluster are expected to achieve a desired formation collaboratively, while the agents in different clusters have different formation patterns. Second, the external disturbance for each agent is taken into account. The associated H∞ cluster formation control, whose performance bound can be obtained by considering both formation information and cluster characteristics, is introduced to measure the disturbance attenuation ability. Third, by casting a stochastic sampled-data-based H∞ cluster formation problem into an H∞ control problem of a stochastic system, an H∞ cluster formation criterion is derived for the MAS with external disturbance. Finally, a lower-dimensional cluster formation criterion is obtained for the disturbance-free MAS. Cluster formation performance analysis testifies the effectiveness of the proposed design methods.

No abstract is provided for this article.

This paper is concerned with distributed Nash equilibrium seeking strategies under quantized communication. In the proposed seeking strategy, a projection operator is synthesized with a gradient search method to achieve the optimization of players' objective functions while restricting their actions within required non-empty, convex and compact domains. In addition, a leader-following consensus protocol, in which quantized information flows are utilized, is employed for information sharing among players. More specifically, logarithmic quantizers and uniform quantizers are investigated under both undirected and connected communication graphs and strongly connected digraphs, respectively. Through Lyapunov stability analysis, it is shown that players' actions can be steered to a neighborhood of the Nash equilibrium with logarithmic and uniform quantizers, and the quantified convergence error depends on the parameter of the quantizer for both undirected and directed cases. A numerical example is given to verify the theoretical results.

This paper is concerned with global asymptotic stability for a class of generalized neural networks with interval time-varying delays by constructing a new Lyapunov–Krasovskii functional which includes some integral terms in the form of ∫ t − h t ( h − t − s ) j x ̇ T ( s ) R j x ̇ ( s ) d s ( j = 1 , 2 , 3 ) . Some useful integral inequalities are established for the derivatives of those integral terms introduced in the Lyapunov–Krasovskii functional. A matrix-based quadratic convex approach is introduced to prove not only the negative definiteness of the derivative of the Lyapunov–Krasovskii functional, but also the positive definiteness of the Lyapunov–Krasovskii functional. Some novel stability criteria are formulated in two cases, respectively, where the time-varying delay is continuous uniformly bounded and where the time-varying delay is differentiable uniformly bounded with its time-derivative bounded by constant lower and upper bounds. These criteria are applicable to both static neural networks and local field neural networks. The effectiveness of the proposed method is demonstrated by two numerical examples.

This paper is concerned with active packet dropouts-based anti-disturbance performance optimization for a continuous-time networked control system (NCS) under consideration of time-varying network-induced delays. By proposing the active packet dropouts method, a new model for an NCS is established. Based on the established model, stabilizing controller design criteria are derived to optimize the anti-disturbance performance of the considered NCS. When transferring nonlinear matrix inequalities into linear matrix inequalities, a parameter searching algorithm and new bounding inequalities are proposed to introduce less conservatism. The mutually exclusive distribution characteristic of the interval time-varying delays is made full use to deal with integral inequalities for products of vectors. A numerical example is given to illustrate the effectiveness of the proposed active packet dropouts-based anti-disturbance performance optimization.

This paper investigates the problem of tracking control for a class of linear networked control systems (NCSs). A linear system with interval time-varying delay is employed to describe the NCSs in consideration of both network-induced delay and packet dropout. An LMI-based sufficient condition on the existence of a network-based controller which guarantees an H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> tracking performance is derived by a new discretized Lyapnov functional. Based on the stability condition and the particle swarm optimization technique, an algorithm is presented to design the tracking controller. Two examples show the effectiveness of the proposed methods.

Internet of things (IoT) devices make up 30% of all network-connected endpoints, introducing vulnerabilities and novel attacks that make many companies as primary targets for cybercriminals. To address this increasing threat surface, every organization deploying IoT devices needs to consider security risks to ensure those devices are secure and trusted. Among all the solutions for security risks, firmware security analysis is essential to fix software bugs, patch vulnerabilities, or add new security features to protect users of those vulnerable devices. However, firmware security analysis has never been an easy job due to the diversity of the execution environment and the close source of firmware. These two distinct features complicate the operations to unpack firmware samples for detailed analysis. They also make it difficult to create visual environments to emulate the running of device firmware. Although researchers have developed many novel methods to overcome various challenges in the past decade, critical barriers impede firmware security analysis in practice. Therefore, this survey is motivated to systematically review and analyze the research challenges and their solutions, considering both breadth and depth. Specifically, based on the analysis perspectives, various methods that perform security analysis on IoT devices are introduced and classified into four categories. The challenges in each category are discussed in detail, and potential solutions are proposed subsequently. We then discuss the flaws of these solutions and provide future directions for this research field. This survey can be utilized by a broad range of readers, including software developers, cyber security researchers, and software security engineers, to better understand firmware security analysis.

The stability problem of linear neutral systems with different delay arguments is investigated using the discretized Lyapunov functional (DFL) approach. Delay-dependent stability criteria are formulated in the form of a linear matrix inequality. The results in this paper contain some existing results as their special cases. Numerical examples are also given to indicate significant improvements over some existing results.

This paper is concerned with robust sliding mode H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> control using time-varying delayed states for an offshore steel jacket platforms subject to self-excited nonlinear wave force, external disturbance and parametric uncertainties. By intension-ally introducing a time-varying delay into the control channel, a delayed robust sliding mode H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> controller is designed to reduce the internal oscillations of the offshore platform. The positive effect of the introduced time-varying delay on robust sliding mode H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> control for the offshore platform is investigated. It is found through simulation results that the delayed robust sliding mode H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> controller is effective to attenuate the vibration of the offshore platform, and the control force required by the proposed controller is smaller than the one by robust sliding mode controller and robust sliding mode H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> controller.

Sampling and communication are both crucial for coordination in multi-agent systems (MASs), with sampling capturing raw data from the environment for contr