Adaptive tracking control of stochastic switched nonlinear systems with unknown dead‐zone output

Abstract

In this article, the problem of adaptive output feedback control is carried out for stochastic switched nonlinear systems with dead-zone output and asymmetric tracking constraints. A type of smooth approximate model is proposed, which unfastens the nondifferentiable phenomena of dead-zone output.The Nussbaum-type function is utilized to develop the control design of the unknown dead-zone output. Subsequently, an improved first-order filter is cooperated into the barrier Lyapunov function analysis, which avoids the repeated derivative problem of virtual control inputs in the backstepping design procedure and completes the control design successfully. The proposed constructive control algorithm can achieve the control goal well. Finally, a numerical example with comparison results is given to further verify the validity of the new control tactic.

Adaptive fuzzy event-triggered fault-tolerant control of switched nonlinear systems with actuator failures under state-dependent switchings

“…From ( 1), (5), we have ṡ1 = ẋ1 − ẏ𝑑 = 𝑔 1,𝑘 (𝑡)𝑥 2 + Δ 1,𝑘 (𝑡) + 𝑓 1,𝑘 (𝑥 1 ) − ẏ𝑑 . Substituting ṡ1 into (7), and based on Assumption 2, we have…”

Output tracking of stochastic high‐order nonlinear systems perturbed by second‐order moment process

“…Recently, tracking control is also a hot research topic [12][13][14][15][16][17][18][19][20][21][22][23][24]. For stochastic systems, Ji and Xi [16] study the adaptive stabilization and tracking problems of output feedback canonical systems driven by wiener noise of unknown covariance; Wu et al [17] focus on the adaptive tracking control for a class of stochastic nonlinear systems with stationary Markovian switching; Li and Zhang [18] discuss the distributed tracking problem for multiagent systems (MASs) where the subsystem of each agent is driven by nonlinear drift and diffusion terms; Xie and Duan [19] consider output tracking of stochastic high-order nonlinear systems.…”

“…For stochastic systems, Ji and Xi [16] study the adaptive stabilization and tracking problems of output feedback canonical systems driven by wiener noise of unknown covariance; Wu et al [17] focus on the adaptive tracking control for a class of stochastic nonlinear systems with stationary Markovian switching; Li and Zhang [18] discuss the distributed tracking problem for multiagent systems (MASs) where the subsystem of each agent is driven by nonlinear drift and diffusion terms; Xie and Duan [19] consider output tracking of stochastic high-order nonlinear systems. Li and Wu [20] introduce a II-operator and use Dynkin formula to solve the output tracking problem for stochastic high-order nonlinear systems with Markovian switching; Li et al [21] solve the output-feedback tracking problem for stochastic high-order nonlinear systems; Li et al [22] design distributed controllers to solve the cooperative control problems for multiple stochastic nonlinear systems under directed network topology; Wu et al [23] study the quantized adaptive finite-time bipartite tracking control problem for stochastic pure-feedback nonlinear MASs with sensor faults; Liu and Ma [24] investigate the adaptive tracking control of stochastic switched nonlinear systems.…”

Hybrid neural network control of uncertain switched nonlinear systems with bounded disturbance

“…One way is to suppose that a common virtual control function occurs and is accessible 43 in which inequality restrictions are posed on common virtual functions. In References 44 and 45, the authors suggested an effective approach of establishing common virtual control functions for the examined uncertain switched nonlinear systems, that solved a class of switched nonlinear systems with uncertainty. The adaptive stabilization for a category of switched nonlinear systems in non‐strict feedback form is examined in References 42 and 46.…”