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2. |
- Driankov, Dimiter, 1952-, et al.
(author)
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A Takagi-Sugeno fuzzy gain-scheduler
- 1996
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In: Proceedings of the Fifth IEEE International Conference on Fuzzy Systems. - New York, USA : IEEE conference proceedings. - 0780336453 ; , s. 1053-1059
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Conference paper (peer-reviewed)abstract
- In the present paper we describe the design of a fuzzy gain scheduler for tracking a reference trajectory of a nonlinear autonomous system. The proposed fuzzy gain scheduling method has two major advantages over the existing crisp gain scheduling methods. First, it provides a general and formally motivated method for the interpolation of available local control laws into a global gain scheduling control law. Second, the method for determining the weights of the local control laws in the global gain scheduling control law is general and computationally efficient. It is shown that a fuzzy gain scheduler can be designed such that robust asymptotic stability is met. Finally, an LQR control design based method is presented
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3. |
- Driankov, Dimiter, 1952-, et al.
(author)
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An Introduction to Fuzzy Control
- 1996. - 2nd revised
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Book (peer-reviewed)abstract
- Fuzzy controllers are a class of knowledge based controllers using artificial intelligence techniques with origins in fuzzy logic. They can be found either as stand-alone control elements or as integral parts of a wide range of industrial process control systems and consumer products. Applications of fuzzy controllers are an established practice for Japanese manufacturers, and are spreading in Europe and America. The main aim of this book is to show that fuzzy control is not totally ad hoc, that there exist formal techniques for the analysis of a fuzzy controller, and that fuzzy control can be implemented even when no expert knowledge is available. The book is mainly oriented to control engineers and theorists, although parts can be read without any knowledge of control theory and may interest AI people. This 2nd, revised edition incorporates suggestions from numerous reviewers and updates and reorganizes some of the material.
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- Driankov, Dimiter, 1952-, et al.
(author)
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Chaining of fuzzy IF-THEN rules in Mamdani-controllers
- 1995
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In: Proceedings of 1995 IEEE International conference on fuzzy systems, Vols I-IV.. - : IEEE conference proceedings. - 0780324617 ; , s. 103-108
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Conference paper (peer-reviewed)abstract
- The problem of chaining of fuzzy IF-THEN rules has so far received a rather theoretic treatment in the literature on approximate reasoning. In particular, different types of composition operators, fuzzy implication operators, etc., have been identified such that the conclusion obtained via a chain of fuzzy rules coincides with the conclusion derived from the “abbreviated” version of the same chain. This “abbreviated” version is a single fuzzy rule which the rule-antecedent is the rule-antecedent of the first rule in the chain, and its rule-consequent is the rule-consequent of the last rule in the chain. However, in the case of more than one chain of rules and when the fuzzy sets defining the meaning of the rule-antecedents and rule-consequents from different chains overlap, then the above theoretical results do not hold in general. In the present paper we identify two major problems with the chaining of fuzzy rules in the case of more than one chain and overlapping rule-antecedents and rule-consequents that belong to different chains
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5. |
- Driankov, Dimiter, 1952-, et al.
(author)
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Towards a systematic analysis of fuzzy observers
- 1999
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In: Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society, 1999. NAFIPS.. - : IEEE conference proceedings. - 0780352114 ; , s. 179-183
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Conference paper (peer-reviewed)abstract
- The paper deals with the analysis of local fuzzy observers for nonlinear plants. The plant is approximated by a TS fuzzy model for which a local linear fuzzy observer is designed. This type of fuzzy observer reconstructs the non-measurable states if the parameters of the locally linearized plant are given. Matched uncertainties in the plant model can be eliminated by an additional nonlinear fuzzy sliding mode observer. Conditions are given under which the combination of the linear and the nonlinear observer lead to a reconstruction of non-measurable states
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6. |
- Fodor, George A., 1954-, et al.
(author)
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The implications of the object/unified modeling language approach to the problem of fault detection and isolation in dynamical systems
- 1999
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In: Proceedings of the 1999 IEEE International Symposium on Computer Aided Control System Design. - New York, USA : IEEE conference proceedings. - 0780355008 ; , s. 176-181
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Conference paper (peer-reviewed)abstract
- There is a growing trend to use object-based implementations and modeling in industrial control applications. However, the object-based approach imposes new theoretical and practical problems. Those problems are due to a higher abstraction level that is achievable with objects as compared to the more traditional, state-based fault detection and isolation methods (FDI) approaches. This paper presents a description of the problems and solutions to them in the framework of a discrete FDI method referred to as ontological control. The results are also relevant in respect to domain-independent failure recovery methods... (Fodor et al., 1997)
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7. |
- Fodor, George, 1954-, et al.
(author)
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Modeling the real-time recovery of complex control systems : A fuzzy approach
- 1997
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In: 1997 IEEE International Conference on Systems, Man, and Cybernetics. - New York, USA : IEEE conference proceedings. - 0780340531 ; , s. 2163-2168
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Conference paper (peer-reviewed)abstract
- This paper presents an approach to complex system recovery based on a fuzzy specification method. The method can be applied when controllers of different types and makes are connected in a common control architecture. The method allows a controller B to trigger a recovery operation on a controller A when B has the recovery specification of A. The approach has important potential applications in industry, e.g. as a possible complement to PLC standards such as IEC1131, and to the design of hybrid and complex control systems
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8. |
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Fuzzy model identification : Selected approaches
- 1997
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Editorial collection (peer-reviewed)abstract
- This carefully edited volume presents a collection of recent works in fuzzy model identification. It opens the field of fuzzy identification to conventional control theorists as a complement to existing approaches, provides practicing control engineers with the algorithmic and practical aspects of a set of new identification techniques, and emphasizes opportunities for a more systematic and coherent theory of fuzzy identification by bringing together methods based on different techniques but aiming at the identification of the same types of fuzzy models. In control engineering, mathematical models are often constructed, for example based on differential or difference equations or derived from physical laws without using system data (white-box models) or using data but no insight (black-box models). In this volume the authors choose a combination of these models from types of structures that are known to be flexible and successful in applications. They consider Mamdani, Takagi-Sugeno, and singleton models, employing such identification methods as clustering, neural networks, genetic algorithms, and classical learning. All authors use the same notation and terminology, and each describes the model to be identified and the identification technique with algorithms that will help the reader to apply the presented methods in his or her own environment to solve real-world problems. Furthermore, each author gives a practical example to show how the presented method works, and deals with the issues of prior knowledge, model complexity, robustness of the identification method, and real-world applications.
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9. |
- Grantner, J.L., et al.
(author)
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Hybrid fuzzy-Boolean automata for ontological controllers
- 1998
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In: The 1998 IEEE International Conference on Fuzzy Systems Proceedings. - New York, USA : IEEE conference proceedings. - 078034863X ; , s. 400-404
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Conference paper (peer-reviewed)abstract
- This paper introduces a hybrid fuzzy-Boolean finite state machine (HFB FSM) model for ontological control. Ontological control is a novel type supervisory control that deals with the problems of error detection and recovery in complex control systems. The HFB FSM is used as a specification method for the problem of recovery when an autonomous control system encounters unexpected changes in its environment. The method allows a controller B (the ontological controller) to trigger a recovery operation on controller A when B has the recovery specification of A. The approach has important potential applications in industry
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10. |
- Grantner, Janos L., et al.
(author)
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Using fuzzy logic for bounded recovery of autonomous agents
- 1997
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In: 1997 Annual Meeting of the North American Fuzzy Information Processing Society. - New York, USA : IEEE conference proceedings. ; , s. 317-322
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Conference paper (peer-reviewed)abstract
- The solution to the problem of application-independent fault recovery of autonomous agents requires a specification method for the agent's capacity to act outside of its normal operational limits. This paper presents a recovery method based upon the theory of a fuzzy finite state machine. A fuzzy specification is given for the bounds within which an autonomous agent is capable to recover after an unexpected situation has occurred in its environment. It has been shown that the three main components of the recovery problem: fault detection, fault recovery, and the properties of the actuator/sensor gear of an autonomous agent are interrelated. The suggested method can be implemented either by an application-independent software algorithm, or by fuzzy logic hardware
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