| 1. |
- Emami, Reza, et al.
(författare)
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Systematic design and analysis of fuzzy-logic control and application to robotics : Part II. Control
- 2000
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Ingår i: Robotics and Autonomous Systems. - 0921-8890 .- 1872-793X. ; 33:2-3, s. 89-108
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Tidskriftsartikel (refereegranskat)abstract
- This paper (Part II) follows the task of systematic synthesis and analysis of fuzzy-logic control (FLC) systems introduced in Part I [M.R. Emami, et al., Robotics and Autonomous Systems 33 (2000) 65–88]. First, a generalized formulation of the sliding mode control is obtained for a class of nonlinear multi-input–multi-output systems. This formulation has two distinguishing features that are necessary for the formulation of the proposed approach: (i) it is applicable to “black box” systems with no need to identify the internal parameters or to assume a specific structure; (ii) it is possible to design the robust controller for each system state independently while the stability and robustness of the entire system is guaranteed. The robust fuzzy control rules are designed based on the generalized formulation to guarantee the stability and satisfactory system performance. The proposed FLC has been applied to trajectory control of the four degree-of-freedom IRIS arm (Emami et al., 2000), and was compared with high-gain PID controllers. A superior tracking performance was achieved.
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| 2. |
- Emami, Reza, et al.
(författare)
-
Systematic design and analysis of fuzzy-logic control and application to robotics : Part 1. Modeling
- 2000
-
Ingår i: Robotics and Autonomous Systems. - 0921-8890 .- 1872-793X. ; 33:2-3, s. 65-88
-
Tidskriftsartikel (refereegranskat)abstract
- A systematic methodology for synthesis and analysis of fuzzy-logic controllers is proposed in this paper (Part I) and its follow up (Part II) [M.R. Emami, et al., Robotics and Autonomous Systems 33 (2000) 89–108]. A robust model-based control structure is suggested that includes a fuzzy-logic inverse dynamics model and several robust fuzzy control rules. The model encapsulates the knowledge of the system dynamics in the form of IF–THEN rules. The paper focuses on how to obtain this knowledge systematically from the input–output data of a complex system; one that is ill-defined or contains complicated phenomena that are difficult to interpret analytically. All practical steps, from data acquisition to model validation, are illustrated using a four degree-of-freedom robot manipulator. Comparing the results with those of a complete analytical model and a heuristic fuzzy modeling technique illustrates the strength of the proposed methodology in terms of capturing effects that are difficult to model. In the follow-up paper, this model is used in the proposed control structure.
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| 3. |
- Goldenberg, Andrew A., et al.
(författare)
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Fuzzy-logic control of dynamic systems : From modeling to design
- 2000
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Ingår i: Engineering applications of artificial intelligence. - 0952-1976 .- 1873-6769. ; 13:1, s. 47-69
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Tidskriftsartikel (refereegranskat)abstract
- A systematic methodology for the synthesis and analysis of fuzzy-logic controllers for multi-input multi-output nonlinear dynamic systems is proposed in this paper. A robust model-based control structure is suggested that includes the fuzzy-logic dynamics model of the system and several robust fuzzy control rules. The fuzzy-logic model is systematically constructed from the input-output data, and the robust control rules are designed using the sliding-mode control theory. The stability and completeness of the control structure is guaranteed, based on a generalized formulation of the sliding-mode control developed in this paper. The proposed fuzzy-logic control scheme has been applied to trajectory control of a four-degree-of-freedom robot manipulator, and was compared with high-gain PID controllers. Superior tracking performance was achieved.
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