Asian Journal of Control最新文献

This paper investigates the control problem of systems with asymmetric saturation by the formulated saturation degree-dependent event-triggered mechanism. The subregion partition method is adopted to represent the asymmetric saturation as the symmetric saturation in each subregion. In order to further reduce the triggering number when the system is saturated and save the communication resources of the system, this paper establishes the saturation degree-dependent adaptive event-triggered condition. Then, the subregion-related control law under the presented event-triggered scheme is designed, and the asymptotic stabilization of the underlying system is realized. Moreover, an optimization algorithm is proposed to estimate the maximal domain of attraction. Finally, simulation examples are used to validate the theoretical results.

This paper mainly studies the design of asynchronous controllers for positive singular semi-Markov jump systems with $��{�L�}_{�1�}�$ performance under the dynamic-memory event-triggered. The positive singular semi-Markov jump system model is established for the first time. And the dynamic-memory event-triggered transmission protocol is used to reduce network transmission pressure. Then, a unified cyber-attack framework that includes DoS attacks and spoofing attacks is established. A simple hidden Markovian model (HMM) model is used to describe the asynchronous phenomena between the controller and the system. Considering the situation where all data cannot be accurately obtained in reality, a simple HMM is set as a partially unknown conditional probability matrix. Based on stochastic Lyapunov functional, the stochastically admissible conditions for the closed-loop systems are obtained. Finally, a numerical example is given to verify the effectiveness of the proposed method.

The Fractional Complex Order Plant model, which has lately gained popularity in applied physics and control systems, is the main subject of this study. The major contribution of this study to the literature is the discussion of the physical phenomena of complex plant models and how they affect the stability and robustness of the systems. Because the Fractional Complex Order Plant model is the most general mathematical form, other plant models covering the Integer Order Plant and the Fractional Order Plant can be easily created with this benefit. The proposed approach using the classical Proportional Integral controller which is recalled as the Integer-Order PI controller in this paper gives the calculation equations of the physical alterations of plants having integer, fractional, and complex orders. Along with the visuals and with the aid of simulations, the consequences of the parameters on the system are described. Additionally, the advantages and disadvantages of the proposed controller designs for each of the three plant species are discussed.

For continuous-time complex-valued neural networks, this paper addresses the state-feedback stabilization issue via dynamic event-triggered protocol. Aiming at random parameters' switching, semi-Markov jump model surpasses the Markov jump model in terms of its generality, enabling us to effectively capture the occurrence of random abrupt alterations in both the structure and parameters of complex-valued neural networks. To optimize packet transmission, a new dynamic event-based protocol is introduced to judge whether the previous signal transmission continues. The design of this protocol takes into full consideration the imaginary part characteristics of the system, while also integrating the system modes and dynamic variables. Utilizing an appropriate Lyapunov functional that contains auxiliary internal dynamical variables, the desired stability is proposed. Eventually, the effectiveness of theoretical findings is ultimately validated through two numerical simulations.

In this article, the issue of adaptive predefined-time control for high-order switched systems is researched. Neural networks (NNs) are introduced to approximate the uncertain nonlinear functions. In particular, a novel predefined-time convergence filter is proposed to refrain from the problem of repeated differentiation of virtual controllers. On the basis of the backstepping recursion technique and the common Lyapunov function (CLF) approach, a neural adaptive predefined-time dynamic surface control (DSC) scheme is proposed that can demonstrate all the signals in closed-loop systems are bounded and the tracking error can converge to a small area near zero within predefined time. The simulation results illustrate the effectiveness of the proposed control scheme.

In this article, the problem of bipartite time-varying formation (BTVF) tracking for multi-agent systems (MASs) under signed digraphs is investigated, in which the inputs of leaders are unknown and bounded. A novel kind of adaptive nonsmooth BTVF tracking protocol for MASs is proposed that did not utilize eigenvalue of Laplacian matrix. Based on the state observer, the problem that the system states are not measurable is solved. In addition, in order to avoid undesirable chattering caused by leaders' nonzero inputs, continuous protocols are proposed. And in this case, the error is uniformly ultimately bounded. Lyapunov method reflects the convergence analysis of the submitted protocols. At last, the desired theoretical results are achieved on a multirobot system.

This paper studies the cooperative output regulation problem for heterogeneous multi-agent systems (MASs) subject to false data injection (FDI) attacks, which means the malicious cyber-attackers may inject false data into the communication topology randomly. To ensure that each follower agent can track the leader agent accurately, we construct both an observer and a control law for each follower agent. Since the FDI attacks may exist in the communication network, a filter with an adaptive compensator, which can estimate attack signals dynamically, is equipped for each observer, such that the filter can neutralize attacks when malicious attackers launch attacks. Therefore, the cooperative output regulation can be achieved under the control law based on the observer no matter whether there exist attacks or not. Finally, a numerical example is provided for validating the theoretical results.

This paper mainly addresses the bipartite time-varying formation tracking (BTVFT) problem for networked Euler–Lagrange systems (NELSs) with external disturbances and parametric uncertainties, considering a directed signed communication network that encompasses both cooperative and competitive interactions. A novel nonsingular sliding mode control (SMC) method serves as the foundation for a predefined-time hierarchical control algorithm (PTHCA), introduced to tackle the BTVFT challenge for NELSs in a predefined time. This approach enables the settling time to be predetermined as a control parameter. Moreover, sufficient conditions for establishing the predefined-time stability of closed-loop systems are provided based on the Lyapunov argument. Simulations are conducted to demonstrate the effectiveness of the main findings.

In this paper, the tracking control problem is investigated for a class of discrete-time multidelayed systems under the accumulation-based event-triggered protocol. The considered phenomena of multidelays, which are extremely common in the real world, include the time-varying delays and the constant delays. The accumulation-based event-triggered protocol is deployed in the communication from sensors to the remote tracking controller in order to alleviate the communication burden. By utilizing the Lyapunov–Krasovskii functional and matrix inequality technology, sufficient conditions are presented to guarantee the exponential stability of the tracking error and the $��{�\ell �}_{�2�}�-�{�\ell �}_{�\infty �}�$ performance, and the controller gain is subsequently designed. Finally, a simulation example is conducted to verify the validity of the developed tracking control scheme.