Adaptive control design for nonlinear systems via successive approximations
Salamci, M. U.
Karakurt, A. H.
ASME 2017 Dynamic Systems and Control Conference, DSCC 2017
American Society of Mechanical Engineers
1 - 8
Item Usage Stats
MetadataShow full item record
The paper presents an approach to the Model Reference Adaptive Control (MRAC) design for nonlinear dynamical systems. A nonlinear reference system is considered such that its response is designed to be stable via Successive Approximation Approach (SAA). Having designed the stable reference model through the SAA, MRAC is then formulated for nonlinear plant dynamics with a new adaptation rule to guarantee the convergence of the nonlinear plant response to that of the response of the nonlinear reference model. The proposed design methodology is illustrated with examples for different case studies. Copyright © 2017 ASME.
KeywordsAdaptive control systems
Advanced driver assistance systems
Advanced vehicle control systems
Linear control systems
Nonlinear dynamical systems
Adaptive control designs
Successive approximation approach
Model reference adaptive control
Published Version (Please cite this version)http://dx.doi.org/10.1115/DSCC2017-5353
Showing items related by title, author, creator and subject.
Abidi, K.; Yildiz, Y. (IFAC Secretariat, 2015)In this paper, we present the discrete version of the Adaptive Posicast Controller (APC) that deals with parametric uncertainties in systems with input time-delays. The continuous-time APC is based on the Smith Predictor ...
Yu, R.; Ocali, O; Sezer, E. S. (IEEE, 1993)Robust adaptive sampled-data control of a class of linear systems under structured perturbations is considered. The controller is a time-varying state-feedback law having a fixed structure, containing an adjustable parameter, ...
Effects of linear filter on stability and performance of human-in-the-loop model reference adaptive control architectures Yousefi, E.; Demir, D. F.; Sipahi, R.; Yucelen, T.; Yildiz, Y. (American Society of Mechanical Engineers, 2017)Model reference adaptive control (MRAC) can effectively handle various challenges of the real world control problems including exogenous disturbances, system uncertainties, and degraded modes of operations. In human-in-the-loop ...