Asian Journal of Control最新文献

In this paper, output-feedback containment control problem of unmanned aerial vehicle (UAV) swarm with input saturation is studied under distributed denial of service (DoS) attacks. Any edge in the communication network may be attacked independently. The considered distributed DoS attack may occur at any time, and there is no limit to the number of DoS attacks, which is more in line with the actual attack scenario. The leader UAVs are noncooperative, which are embedded with unknown input. Firstly, to estimate the state signals, distributed observers are designed. Then, a general form of distributed DoS attack model is established. To deal with distributed DoS attacks, compensators are constructed for each follower UAV to estimate its neighbor signals when DoS attacks occur. The compensator calibration mechanism is introduced to calibrate the estimated values once the communication is restored. In this way, the flexible switching between the estimated values and the real values is realized to improve the ability to respond to DoS attacks. Then, an auxiliary system is designed to cope with the possible input saturation phenomenon. Finally, a novel variable-gain distributed containment control law is proposed, based on a quadratic term of the adaptive parameter, which shortens the convergence time and reduces the steady-state error. It is proved that the proposed scheme ensures that all the state errors, including containment error, observation error, adaptive parameter, and auxiliary variable, are uniformly ultimately bounded, and the effectiveness and superiority are verified by simulation experiments and comparative analyses.

Swelling (also called expansive) soils are characterized by a swell in the soil's volume when subjected to moisture. The clay minerals in soil naturally attract and absorb water. When water is introduced to swelling soils, the water molecules are pulled into the gaps between the soil plates. As more water is absorbed, the plates are forced further apart, leading to an increase in soil pore pressure and consequently swelling soils significantly leading to geotechnical and structural challenges. In this paper, we consider a fractional swelling soil system damped by only a viscoelastic term. It turns out that investigating this problem the same way as done for the integer case is not possible. This is mainly due to the nonlinear character of the fractional derivative (in addition to the viscoelastic term), the difficulty caused by singular kernels, and the weak damping implied by the viscoelasticity. We prove that the system is Mittag–Leffler stable when the relaxation function itself is decaying in a Mittag–Leffler fashion. Our result is obtained using the multiplier method and some properties in fractional calculus. In addition, we present a numerical example to prove the validity of the theoretical stability results for this system.

This paper presents a rigorous analytical framework for investigating the Mittag–Leffler synchronization (MLSY) properties in fractional-order reaction–diffusion systems (FO-RDs). By incorporating a linear control strategy within a drive-response configuration, we derive sufficient conditions under which the system states converge to their equilibrium point (EP). The analysis employs fractional calculus specifically Caputo fractional derivatives (CFDs) and Mittag–Leffler function estimates—in conjunction with Lyapunov function (LF) techniques to establish Mittag–Leffler stability (MLS) and synchronization despite the systems' inherent nonlinearities and spatial heterogeneity. The theoretical results are substantiated by numerical simulations on a glycolysis RD model, demonstrating rapid convergence and robust performance of the proposed control scheme. These findings underscore the potential applicability of the developed approach in diverse areas such as secure communications, biological system modeling, and complex network synchronization.

This paper explores an optimal control problem of weakly coupled abstract hyperbolic systems with missing initial data. Hyperbolic systems, known for their wave-like phenomena and complexity, become even more challenging with weak coupling between subsystems. The study introduces no-regret and low-regret control strategies to handle missing information and achieve optimal performance. By deriving the Euler–Lagrange optimality system, it characterizes these control approaches in the context of weak coupling. Additionally, the paper establishes the existence and uniqueness of a no-regret and low-regret control, emphasizing the influence of uncertain coupling parameters. These findings are optimal control strategies for abstract weakly coupled hyperbolic systems under uncertainty. Finally, as highlighted in our conclusion, future research could explore integrating memory effects through fractional derivatives to improve the modeling of viscoelasticity, diffusion with memory, and wave damping.

This paper presents an Adaptive MIMO Sliding Mode Control (AMSMC) strategy for coordinating Active Front Steering (AFS) and Direct Yaw Control (DYC) systems to enhance vehicle stability and handling under uncertain conditions. Traditional Single Input Single Output (SISO) models fail to capture the complex interactions and nonlinearities inherent in vehicle dynamics, leading to suboptimal performance. The proposed method addresses these limitations by utilizing a Multiple Input Multiple Output (MIMO) framework, which accurately models the nonlinear interactions between AFS and DYC systems. Additionally, the method introduces a dynamic coefficient in the sliding mode control, enabling real-time adaptation to unknown uncertainties and enhancing robustness. The slip angle is estimated by an observer and a first-order delay is introduced into the lateral forces modeling to improve the accuracy of vehicle dynamics representation. The stability of the closed-loop system is further validated using the Lyapunov method. The performance of the proposed controller is evaluated considering the coefficient of road tire friction and parametric uncertainties in vehicle parameters, such as total mass, moment of inertia, and tire stiffness. The efficacy of this method has been rigorously confirmed through MATLAB simulations using a nonlinear 8-DOF vehicle model, which includes parameter uncertainties to ensure the control strategy's resilience to varying road conditions. The simulation results demonstrate significant improvements in the vehicle's stability and handling performance across a variety of driving maneuvers.

The Takagi–Sugeno observer is based on fuzzy logic, which allows for a higher degree of interpretability compared to purely mathematical or computational models. The rules and their membership functions can be understood and modified by human operators, providing a degree of transparency that is valuable in practical applications. For a specific class of Bilinear Systems (BS), we examine the observer design problem under small disturbances in this work. Under some appropriate conditions, we prove that the resulting error system is globally exponentially stable to a small compact set. An application to the case of fractional order with a numerical example is also proposed to strengthen the validity of the main result.

This paper investigates the problem of practical stabilization for a class of tempered fractional-order nonlinear fuzzy systems. By incorporating tempered fractional derivatives into the control design and employing Lyapunov-based analysis, we derive sufficient conditions to ensure practical Mittag–Leffler stability (PMLS) of the closed-loop system. The proposed approach leverages a fuzzy control framework to handle system uncertainties while ensuring robust performance. An illustrative example is provided to demonstrate the effectiveness of the stabilization strategy. These results contribute to the ongoing research on fractional-order system control and highlight potential applications in observer-based control and fault-tolerant systems.