Adaptive fault‐tolerant decentralized tracking control of switched stochastic uncertain nonlinear systems with time‐varying delay

Abstract

In this article, an adaptive neural fault-tolerant decentralized tracking control problem is investigated for switched stochastic large-scale uncertain nonlinear systems, in which time-varying delay and unknown control coefficient are under consideration. By incorporating the quadratic Lyapunov function and Lyapunov Krasovskii function into the backstepping approach, an adaptive neural fault-tolerant decentralized control strategy is proposed, which ensures that signals in the closed-loop system are stable in probability and the tracking error converges to a small neighborhood of the origin under arbitrary switching. At last, to verify the presented strategy is feasible, a simulation example is given.

Bipartite containment control of nonlinear multi‐agent systems with unknown inputs and state constraints

“…Thus, state constraint (10) is totally equivalent to that of (15). Therefore, in what follows, we plan to design a distributed controller for dynamic system (12) to realize the output containment control satisfying the constraint (15).…”

“…This motivate us to consider observer based control for for uncertain systems 12 or fault tolerant problems. [13][14][15] As a result, we found the following related works as references. On signed digraphs, Zhu et al 16 investigate the bipartite containment problem in singular MASs using observers.…”

Neural network‐based output‐feedback adaptive control for a class of uncertain strict feedback fractional‐order nonlinear systems subject to input saturation

“…• Contrary to the literature 4,11,19,[21][22][23]27,29,[32][33][34]43,[45][46][47][48][49] of adaptive control of fractional order nonlinear systems where the practical issue of input saturation was not treated, in the proposed method, the saturation nonlinearity is considered in the design phase to adhere with control signal limits and avoid any unexpected alteration.…”

“…As the system order increases, there is a drastic growth in the complexity of the control law that leads to an issue known as the "explosion of complexity". [19][20][21][22][23] To address this issue, graph theory combined with NNs was proposed in Reference 24. Alternatively, the well-known dynamic surface control (DSC), introduced in Reference 25, incorporates at each back-stepping phase, a first-order filter to estimate the virtual control input.…”

“…• The issue of complexity explosion arising in the literature on adaptive fractional-order systems [14][15][16][17][18][19][20][21][22][23][24]43 is completely eliminated in the proposed approach by resorting to a new non-backstepping-based transformational technique for fractional order systems.…”