Adaptive Neural Network Control of a Class of Fractional Order Uncertain Nonlinear MIMO Systems with Input Constraints
An adaptive backstepping control scheme for a class of incommensurate fractional order uncertain nonlinear multiple-input multiple-output (MIMO) systems subjected to constraints is discussed in this paper, which ensures the convergence of tracking errors even with dead-zone and saturation nonlineari...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2019/1410278 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832551053362462720 |
|---|---|
| author | Changhui Wang Mei Liang Yongsheng Chai |
| author_facet | Changhui Wang Mei Liang Yongsheng Chai |
| author_sort | Changhui Wang |
| collection | DOAJ |
| description | An adaptive backstepping control scheme for a class of incommensurate fractional order uncertain nonlinear multiple-input multiple-output (MIMO) systems subjected to constraints is discussed in this paper, which ensures the convergence of tracking errors even with dead-zone and saturation nonlinearities in the controller input. Combined with backstepping and adaptive technique, the unknown nonlinear uncertainties are approximated by the radial basis function neural network (RBF NN) in each step of the backstepping procedure. Frequency distributed model of a fractional integrator and Lyapunov stability theory are used for ensuring asymptotic stability of the overall closed-loop system under input dead-zone and saturation. Moreover, the parameter update laws with incommensurate fractional order are used in the controller to compensate unknown nonlinearities. Two simulation results are presented at the end to ensure the efficacy of the proposed scheme. |
| format | Article |
| id | doaj-art-71ea9d6a19314480a6d65698bd738088 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-71ea9d6a19314480a6d65698bd7380882025-02-03T06:05:10ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/14102781410278Adaptive Neural Network Control of a Class of Fractional Order Uncertain Nonlinear MIMO Systems with Input ConstraintsChanghui Wang0Mei Liang1Yongsheng Chai2School of Electromechanical and Automotive Engineering, Yantai University, 32 Qingquan Road, Laishan District, Yantai, ChinaSchool of Electromechanical and Automotive Engineering, Yantai University, 32 Qingquan Road, Laishan District, Yantai, ChinaSchool of Electromechanical and Automotive Engineering, Yantai University, 32 Qingquan Road, Laishan District, Yantai, ChinaAn adaptive backstepping control scheme for a class of incommensurate fractional order uncertain nonlinear multiple-input multiple-output (MIMO) systems subjected to constraints is discussed in this paper, which ensures the convergence of tracking errors even with dead-zone and saturation nonlinearities in the controller input. Combined with backstepping and adaptive technique, the unknown nonlinear uncertainties are approximated by the radial basis function neural network (RBF NN) in each step of the backstepping procedure. Frequency distributed model of a fractional integrator and Lyapunov stability theory are used for ensuring asymptotic stability of the overall closed-loop system under input dead-zone and saturation. Moreover, the parameter update laws with incommensurate fractional order are used in the controller to compensate unknown nonlinearities. Two simulation results are presented at the end to ensure the efficacy of the proposed scheme.http://dx.doi.org/10.1155/2019/1410278 |
| spellingShingle | Changhui Wang Mei Liang Yongsheng Chai Adaptive Neural Network Control of a Class of Fractional Order Uncertain Nonlinear MIMO Systems with Input Constraints Complexity |
| title | Adaptive Neural Network Control of a Class of Fractional Order Uncertain Nonlinear MIMO Systems with Input Constraints |
| title_full | Adaptive Neural Network Control of a Class of Fractional Order Uncertain Nonlinear MIMO Systems with Input Constraints |
| title_fullStr | Adaptive Neural Network Control of a Class of Fractional Order Uncertain Nonlinear MIMO Systems with Input Constraints |
| title_full_unstemmed | Adaptive Neural Network Control of a Class of Fractional Order Uncertain Nonlinear MIMO Systems with Input Constraints |
| title_short | Adaptive Neural Network Control of a Class of Fractional Order Uncertain Nonlinear MIMO Systems with Input Constraints |
| title_sort | adaptive neural network control of a class of fractional order uncertain nonlinear mimo systems with input constraints |
| url | http://dx.doi.org/10.1155/2019/1410278 |
| work_keys_str_mv | AT changhuiwang adaptiveneuralnetworkcontrolofaclassoffractionalorderuncertainnonlinearmimosystemswithinputconstraints AT meiliang adaptiveneuralnetworkcontrolofaclassoffractionalorderuncertainnonlinearmimosystemswithinputconstraints AT yongshengchai adaptiveneuralnetworkcontrolofaclassoffractionalorderuncertainnonlinearmimosystemswithinputconstraints |