Adaptive Quantized Tracking Control for a Class of Nonlinear Systems
Xiaowei Yu, Yan Lin
Abstract
In this article, an adaptive quantized tracking control for a class of nonlinear systems with both input and state quantization is investigated. For the state quantization, instead of quantizing all the system states, only two signals need to be quantized and transmitted, which greatly reduces the communication burden. It is proved that with this proposed scheme, global stability of the closed-loop system can be achieved even with very coarse quantizers, and the tracking errors can be made arbitrarily small by choosing some design parameters appropriately.
Topics & Concepts
Quantization (signal processing)Control theory (sociology)Nonlinear systemTracking (education)Adaptive controlComputer scienceClass (philosophy)State (computer science)Stability (learning theory)Exponential stabilityTracking errorMathematicsControl (management)Artificial intelligenceAlgorithmPhysicsPedagogyMachine learningPsychologyQuantum mechanicsAdaptive Control of Nonlinear SystemsStability and Control of Uncertain SystemsAdvanced Control Systems Optimization