Adaptive output-feedback tracking control for a class of nonlinear systems with input saturation: a multi-dimensional Taylor network-based approach
Yu‐Qun Han
Abstract
For the nonlinear systems with input saturation constraint, a novel MTN-based output-feedback control strategy is developed via backstepping in this paper. Firstly, an MTN-based nonlinear state observer is designed to estimate the unmeasured states. Secondly, multi-dimensional Taylor networks (MTNs) are used to deal with the unknown nonlinear functions, based on this, the procedure of the adaptive MTN output-feedback controller design is developed by combining backstepping approach and dynamic surface control technique, and then the stability of the closed-loop system is proved based on the principle of Lyapunov stability theory. Finally, the theoretical results of this paper are demonstrated by two examples.
Topics & Concepts
BacksteppingControl theory (sociology)Nonlinear systemController (irrigation)Lyapunov stabilityObserver (physics)Strict-feedback formLyapunov functionConstraint (computer-aided design)Stability (learning theory)Saturation (graph theory)Nonlinear controlAdaptive controlComputer scienceControl engineeringMathematicsControl (management)EngineeringArtificial intelligenceAgronomyQuantum mechanicsMachine learningPhysicsGeometryCombinatoricsBiologyAdaptive Control of Nonlinear SystemsDistributed Control Multi-Agent SystemsNeural Networks Stability and Synchronization