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Fuzzy model-based adaptive robust co...

Zeinali Ghayeshghorshagh, Meysar.

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Fuzzy model-based adaptive robust control design and application to robot manipulators.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Fuzzy model-based adaptive robust control design and application to robot manipulators./
Author:	Zeinali Ghayeshghorshagh, Meysar.
Description:	208 p.
Notes:	Source: Dissertation Abstracts International, Volume: 68-04, Section: B, page: 2624.
Contained By:	Dissertation Abstracts International68-04B.
Subject:	Engineering, Robotics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR26662
ISBN:	9780494266625

Fuzzy model-based adaptive robust control design and application to robot manipulators.
Zeinali Ghayeshghorshagh, Meysar.

Fuzzy model-based adaptive robust control design and application to robot manipulators. - 208 p.

Source: Dissertation Abstracts International, Volume: 68-04, Section: B, page: 2624.

Thesis (Ph.D.)--Queen's University (Canada), 2007.

Robust controller design for nonlinear uncertain dynamical systems can be a challenging work. This thesis focuses on the design, analysis and implementation of a high performance fuzzy model-based adaptive robust control (FMARC) for a class of second-order nonlinear uncertain systems (e.g., the robot manipulators), in the presence of structured (parametric) and unstructured uncertainties (e.g., disturbances). In order to provide a simple yet efficient dynamic model, modelling based on the theory of fuzzy logic is selected as a modelling tool to construct the parameterized fuzzy model of the system. In this regard a systematic fuzzy modelling methodology is developed. Sliding mode control methodology is selected as a framework to construct the control law (i.e., formulation to compute the required control input) and address the stability and robustness of the overall closed-loop system. The proposed approach effectively combines the design techniques from sliding mode control (SMC), adaptive control (AC), fuzzy logic (FL) modelling methodology and linear proportional-derivative-integral (PID) control to improve the performance and enhance the robustness property of the controller.

ISBN: 9780494266625Subjects--Topical Terms:

1018454
Engineering, Robotics.

Fuzzy model-based adaptive robust control design and application to robot manipulators.
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020 $a 9780494266625
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100 1 $a Zeinali Ghayeshghorshagh, Meysar. $3 1682710
245 1 0 $a Fuzzy model-based adaptive robust control design and application to robot manipulators.
300 $a 208 p.
500 $a Source: Dissertation Abstracts International, Volume: 68-04, Section: B, page: 2624.
502 $a Thesis (Ph.D.)--Queen's University (Canada), 2007.
520 $a Robust controller design for nonlinear uncertain dynamical systems can be a challenging work. This thesis focuses on the design, analysis and implementation of a high performance fuzzy model-based adaptive robust control (FMARC) for a class of second-order nonlinear uncertain systems (e.g., the robot manipulators), in the presence of structured (parametric) and unstructured uncertainties (e.g., disturbances). In order to provide a simple yet efficient dynamic model, modelling based on the theory of fuzzy logic is selected as a modelling tool to construct the parameterized fuzzy model of the system. In this regard a systematic fuzzy modelling methodology is developed. Sliding mode control methodology is selected as a framework to construct the control law (i.e., formulation to compute the required control input) and address the stability and robustness of the overall closed-loop system. The proposed approach effectively combines the design techniques from sliding mode control (SMC), adaptive control (AC), fuzzy logic (FL) modelling methodology and linear proportional-derivative-integral (PID) control to improve the performance and enhance the robustness property of the controller.
520 $a Two adaptation mechanisms are provided to deal with structured uncertainties and unstructured uncertainties, namely: an adaptive fuzzy model and an adaptive performance/error-based uncertainty estimator mechanism. It is proved that for slowly time-varying uncertainties, asymptotic stability can be achieved in the presence of the two above mentioned uncertainties and without using the high gains in the feedback loop. The design is conceptually simple and uses the desired trajectory information rather than using expensive measured acceleration information for estimation of the uncertainty, thus it is suitable for implementation.
520 $a In the first phase of validation, the proposed FMARC algorithm is compared with Slotine and Li adaptive control and sliding mode control with boundary layer by simulation study of a two degrees of freedom (DOF) direct drive serial robot manipulator. Comparative simulation results revealed that the proposed method has superior performance in terms of tracking accuracy without increasing the control effort. In the second phase of validation, the proposed method is applied to the modelling and trajectory tracking control of 4-DOF wire-actuated robot manipulator. The proposed FMARC is found to provide a very good tracking performance without increasing the control effort.
520 $a The simulation and experimental results show that the proposed method overcomes the drawbacks of controllers designed based on only AC, SMC and high-gain PID control methods and its simplicity makes the approach attractive for real-time applications.
590 $a School code: 0283.
650 4 $a Engineering, Robotics. $3 1018454
690 $a 0771
710 2 $a Queen's University (Canada). $3 1017786
773 0 $t Dissertation Abstracts International $g 68-04B.
790 $a 0283
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NR26662