Adaptive RBF Neural Network Tracking Control of Stochastic Nonlinear Systems with Actuators and State Constraints

• Published in: Mathematics (Basel) Vol. 12; no. 9; p. 1378
• Main Authors: Zhang, Jianhua, Li, Yinguang
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.05.2024
• Subjects: actuator constraint; Actuators; adaptive; Analysis; Control systems; Control systems design; Controllers; Design; full-state constraints; Hyperbolic functions; Inequality; Liapunov functions; Neural networks; NN fixed time control; Nonlinear control; Nonlinear systems; Randomness; stochastic nonlinear systems; Stochastic systems; Tracking control

This paper investigates the adaptive neural network (NN) tracking control problem for stochastic nonlinear systems with multiple actuator constraints and full-state constraints. The issue of system full-state constraints is tackled by a generalized barrier Lyapunov function (GBLF), and the output co...