Switched Control of HyTAQs: A Framework of Stochastic Hybrid Fuzzy Systems With Variable Dimensions.

This article is concerned with the switched control of hybrid terrestrial and aerial quadrotors (HyTAQs) via stochastic hybrid fuzzy system methodology, in which the terrestrial and aerial mode switching is subject to a Markov process with lower-bounded sojourn time. For the first time, the bimodal nonlinear attitude dynamics of HyTAQs is analyzed and modeled based on the Takagi-Sugeno (T-S) fuzzy model, and switched fuzzy controllers are developed to stabilize the hybrid fuzzy system. The characteristic of state dimension switching caused by ground contact is modeled via the singular system presentation with mode-dependent singularity matrices, based on which numerically testable criteria of stability and stabilization in the stochastic sense are derived. Compared with the previous control approaches based on Markov jump systems, the proposed one is able to describe the deterministic dwelling duration in practice and integrate multiple subsystems with algebraic equations of different dimensions, while achieving lower conservatism. Illustrative examples are provided to demonstrate the effectiveness and potential of the designed variable-dimension fuzzy controllers.

Resilient Output Containment Control of Heterogeneous Multiagent Systems Against Composite Attacks: A Digital Twin Approach.

This article delves into the distributed resilient output containment control of heterogeneous multiagent systems against composite attacks, including Denial-of-Service (DoS) attacks, false-data injection (FDI) attacks, camouflage attacks, and actuation attacks. Inspired by digital twin technology, a twin layer (TL) with higher security and privacy is employed to decouple the above problem into two tasks: 1) defense protocols against DoS attacks on TL and 2) defense protocols against actuation attacks on the cyber-physical layer (CPL). Initially, considering modeling errors of leader dynamics, distributed observers are introduced to reconstruct the leader dynamics for each follower on TL under DoS attacks. Subsequently, distributed estimators are utilized to estimate follower states based on the reconstructed leader dynamics on the TL. Then, decentralized solvers are designed to calculate the output regulator equations on CPL by using the reconstructed leader dynamics. Simultaneously, decentralized adaptive attack-resilient control schemes are proposed to resist unbounded actuation attacks on the CPL. Furthermore, the aforementioned control protocols are applied to demonstrate that the followers can achieve uniformly ultimately bounded (UUB) convergence, with the upper bound of the UUB convergence being explicitly determined. Finally, we present a simulation example and an experiment to show the effectiveness of the proposed control scheme.

Adaptive Bipartite Tracking Control of Nonlinear Multiagent Systems With Input Quantization.

This article studies the bipartite tracking control problem of distributed nonlinear multiagent systems with input quantization, external disturbances, and actuator faults. We use the radial basis function (RBF) neural networks (NNs) to model unknown nonlinearities. Due to the fact that the upper bounds of disturbances and the number of actuator faults are unknown, an intermediate control law is designed based on a backstepping strategy, where a compensation term is introduced to eliminate external disturbances and actuator faults. Meanwhile, a novel smooth function is incorporated into the real distributed controller to reduce the effect of quantization on the virtual controller. The proposed distributed controller not only realizes the bipartite tracking control but also ensures that all signals are bounded in the closed-loop systems and the outputs of all followers converge to a neighborhood of the leader output. Finally, simulation results demonstrate the effectiveness of the proposed control algorithm.

Reliable filtering with strict dissipativity for T-S fuzzy time-delay systems.

In this paper, the problem of reliable filter design with strict dissipativity has been investigated for a class of discrete-time T-S fuzzy time-delay systems. Our attention is focused on the design of a reliable filter to ensure a strictly dissipative performance for the filtering error system. Based on the reciprocally convex approach, firstly, a sufficient condition of reliable dissipativity analysis is proposed for T-S fuzzy systems with time-varying delays and sensor failures. Then, a reliable filter with strict dissipativity is designed by solving a convex optimization problem, which can be efficiently solved by standard numerical algorithms. Finally, numerical examples are provided to illustrate the effectiveness of the developed techniques.