Finite‐time adaptive tracking control for a class of nonstrict feedback nonlinear systems with full state constraints
Yudi Wang, Guangdeng Zong, Dong Yang, Kaibo Shi
Abstract
Abstract This article reports our investigation on the finite‐time tracking control problem for nonstrict feedback nonlinear systems subject to full state constraints. A finite‐time stability criterion is founded by employing the barrier Lyapunov function methodology. With the backstepping technique, an adaptive neural networks controller is proposed, which can pledge that the closed‐loop system signals bounded and the tracking error converges to a sufficiently modest area around the origin in finite‐time under full state constraints. Finally, an example of the electromechanical system is given to corroborate the validity of acquired methods.
Topics & Concepts
BacksteppingControl theory (sociology)Nonlinear systemTracking errorComputer scienceController (irrigation)Tracking (education)Bounded functionLyapunov functionState (computer science)Stability (learning theory)Control (management)Adaptive controlMathematicsAlgorithmArtificial intelligenceMachine learningPhysicsMathematical analysisPsychologyAgronomyBiologyQuantum mechanicsPedagogyAdaptive Control of Nonlinear SystemsAdaptive Dynamic Programming ControlIterative Learning Control Systems