Asian Journal of Control最新文献

This paper focuses on the problem of multi-agent resource allocation in the context of directed balanced network attacks and event-triggered communications. Considering the potential communication link failures due to external attacks, this paper proposes a continuous-time distributed resource allocation algorithm to effectively address these challenges. Additionally, an event-triggered communication mechanism is implemented, which intelligently determines the timing of information exchanges to enhance system responsiveness while significantly reducing communication resource consumption. Through extensive theoretical analysis, the algorithm is proven to effectively avoid Zeno behaviors and to converge exponentially to the optimal solution. Finally, some simulation experiments further validate the accuracy of the theoretical analysis and the practical effectiveness of the algorithm.

The paper deals with $��\varsigma �$-tempered fractional derivatives, along with their stability properties. Firstly, we obtain the derivative inequalities, which are essential in applying the theorems derived in this work. Then, by using Lyapunov function, we obtain the stability results of such systems. Furthermore, an observer design is given as an application to validate the proposed theory. A numerical example is presented to show the effectiveness of our results.

This study explores an improved intermediate estimator-based fault estimation method for Lipschitz nonlinear systems. The proposed intermediate estimator offers notable advantages, including the elimination of the need for a matching condition, the ability to accommodate unbounded faults, and the removal of the necessity to identify the fault derivative bound. The primary focus is on improving the performance of the fault estimator by reducing overshoot, minimizing steady-state error, and accelerating the convergence rate. To achieve these improvements, a novel dynamic system with a PID structure is introduced into the intermediate estimator design. This design incorporates three adjustable parameters: proportional, integral, and derivative coefficients. Fine-tuning these parameters allows for optimized performance in both transient and steady-state conditions. Numerical simulations demonstrate that the improved intermediate estimator outperforms the nominal intermediate estimator. Theoretical analysis further reveals that the nominal intermediate estimator can be considered a subset of the proposed estimator. Utilizing Lyapunov stability theory and the linear matrix inequality (LMI) method, it is proven that the error system's states are uniformly ultimately bounded. Comparisons with the nominal intermediate estimator highlight the proposed method's superior capabilities and benefits.

This paper studies a formation control problem with distance constraints for nonlinear agents with uncertainties. Controlling an edge is assigned to only one of its incident agents. Directed graph theory is used to model the desired formation topology. The method is distributed, applicable to uncertain nonlinear agents, and is based on robust-optimal control. The proposed control scheme is based on integral sliding mode control (ISMC) combined with the state-dependent Riccati equation (SDRE) method. The method minimizes a weighted cost function that includes the formation and control input costs for a given mission while compensating for the effect of uncertainties. A rigorous Lyapunov stability analysis proved the local asymptotic convergence of the agents to the desired distances. We use the concept of mathematical induction to show that the formation of all agents is stable. Detailed simulation results are included to verify the proposed control scheme.

This paper investigates the adaptive variable-step predictive (AVSP) control of networked control systems (NCSs) against denial-of-service (DoS) attacks. An adaptive variable-step prediction approach based on cumulative error is formulated to ensure the security of the system against DoS attacks, under which the prediction step varies adaptively in each DoS attacks period. The underlying system is described as a switching system and is categorized into three operation modes based on the presence or absence of DoS attacks and the prediction step size. With piecewise Lyapunov function, sufficient conditions for the design of DoS-period-based mode-dependent controller is established, and the effectiveness is verified by an example.

This paper considers the bipartite consensus (BC) of second-order delayed multi-agent systems under signed graphs via aperiodically intermittent control (AIC). Firstly, to break the bottleneck of limited state information from the leader, a novel distributed observer is introduced based on the output information. Secondly, a new aperiodically intermittent controller is designed to achieve the consensus goal and reduce the control cost. By employing inequality techniques and Lyapunov stability theory, some sufficient conditions for ensuring BC of second-order multi-agent systems is ultimately obtained. Finally, the effectiveness of the theoretical analysis is demonstrated through a numerical example.

This paper focuses on the design of $��{�H�}_{�\infty �}�$ filtering for two-dimensional (2-D) continuous-discrete Takagi–Sugeno (T–S) fuzzy systems. The frequency of disturbance input is assumed to be known and to reside in a finite frequency (FF) domain. The objective is to provide a new design sufficient condition via linear matrix inequalities (LMIs) formulation, ensuring both the stability of the filtering error system and $��{�H�}_{�\infty �}�$ performance level in specific FF domain. Finally, an illustrative example is provided to demonstrate the applicability and effectiveness of the proposed method.

This paper investigates the reachable set estimation problem for networked T-S fuzzy switched systems by utilizing the integral-based event-triggering scheme. Different from the existing results, the proposed controller design method firstly integrates the integral-based event-trigger mechanism for T-S fuzzy switched systems, which not only reduces the transmission of communication data but also ensures that the state trajectories can be driven to the reachable set. Then, the event-trigger parameters are derived and the controller gains are obtained. Finally, the superiority and effectiveness of the derived results are verified through a simulation example.

Network topology is one of crucial components in multi-agent systems, and it reflects the information interaction between agents. In many practical multi-agent systems, for example, wireless sensor networks, the interactions between agents can be characterized by a state-dependent graph, in which the weights vary with the relative agent states. How to achieve the finite-time consensus under the state-dependent graph is worth in-depth research and especially integrates/reforms the relevant techniques. This paper addresses the finite-time consensus for uncertain nonlinear multi-agent systems under a state-dependent graph. Typically, the systems allow severe uncertainties in control coefficients and nonlinearities, which, together with the state-dependent graph, renders the protocol design of finite-time consensus more difficult. To this end, a fully distributed protocol with dynamic high gain is designed. Notably, in the protocol, only one dynamic high gain, rather than multiple ones in related existing results, is sufficient to deal with the uncertainties and the unavailable global graph information. Especially, a condition which relies on the specified distance and the system initial states is presented to guarantee the connectivity of the graph. It turns out that by the protocol and condition, the finite-time consensus is achieved. Simulation results are given to illustrate the validity of the proposed method.

This paper introduces a novel Jacobian-based frequency-sweeping approach for constructing a stability map on a delay plane for linear time-invariant (LTI) systems with two delays. It is demonstrated that by imposing a zero Jacobian condition on the Rekasius-transformed polynomial equations defining the stability crossing curves (SCCs), the set of stability crossing frequencies (SCFs) can be determined exactly and exhaustively. Compared to existing frameworks that use a discrimination criterion to identify the upper bound of SCFs, our proposed framework offers the following three merits: (i) it establishes a direct link between the zero Jacobian criterion and the end points of the SCF intervals; (ii) it reveals the invariance property of the curve-wise crossing direction for each SCC; (iii) it provides a simple Jacobian calculation to determine the root crossing directions relative to the imaginary axis. These merits significantly enhance the cluster treatment of the characteristic root (CTCR) paradigm for investigating stability robustness against delay uncertainties. A computational procedure is provided for the implementation of the proposed framework. Additionally, the role of Jacobian in constructing stability crossing curves is demonstrated through two examples.