6533b837fe1ef96bd12a1fcc

RESEARCH PRODUCT

Adaptive Neural Control of MIMO Nonstrict-Feedback Nonlinear Systems with Time Delay

Yanzheng ZhuHamid Reza KarimiXudong ZhaoHaijiao Yang

subject

0209 industrial biotechnologyComputer scienceMIMOAdaptive trackingoutput-feedback controller02 engineering and technologyNonlinear controlmultiple-input and multiple-output (MIMO)020901 industrial engineering & automationControl theoryAdaptive system0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringArtificial neural networkControl engineeringComputer Science Applications1707 Computer Vision and Pattern RecognitionFilter (signal processing)neural networksComputer Science ApplicationsHuman-Computer InteractionNonlinear systemControl and Systems EngineeringBackstepping020201 artificial intelligence & image processingAdaptive tracking; multiple-input and multiple-output (MIMO); neural networks; output-feedback controller; Control and Systems Engineering; Software; Information Systems; Human-Computer Interaction; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic EngineeringSoftwareInformation Systems

description

In this paper, an adaptive neural output-feedback tracking controller is designed for a class of multiple-input and multiple-output nonstrict-feedback nonlinear systems with time delay. The system coefficient and uncertain functions of our considered systems are both unknown. By employing neural networks to approximate the unknown function entries, and constructing a new input-driven filter, a backstepping design method of tracking controller is developed for the systems under consideration. The proposed controller can guarantee that all the signals in the closed-loop systems are ultimately bounded, and the time-varying target signal can be tracked within a small error as well. The main contributions of this paper lie in that the systems under consideration are more general, and an effective design procedure of output-feedback controller is developed for the considered systems, which is more applicable in practice. Simulation results demonstrate the efficiency of the proposed algorithm.

yearjournalcountryeditionlanguage
2016-06-01
10.1109/tcyb.2015.2441292http://hdl.handle.net/11311/1017795