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Robust Control for T-S Fuzzy Systems
2019T-S fuzzy models with actuator saturation and norm-bounded uncertainties have been used to describe nonlinear systems subject to actuator saturation in [10]. An overhead crane model has been described by a class of T-S fuzzy systems with input delays and actuator saturation in [193].
Hongjiu Yang, Yuanqing Xia, Qing Geng
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Impulsive Control of T-S Fuzzy Systems
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007This paper provides a new viewpoint for fuzzy systems via an impulsive technique, i.e. the impulsive control is introduced into the fuzzy systems based on T-S model and the fuzzy system model with impulsive control is established. The main difference between the proposed control strategy and PDC lies in that the subsystems are the linear impulsive ones
Dan Yang, Xiaohong Zhang, Dong Li
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On the controllability of fuzzy multistage systems
Fuzzy Sets and Systems, 1990Abstract We consider the problem of controlling a special fuzzy system so that the states are within given regions. For initial control, existence theorems are proven.
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Adaptive fuzzy control systems
Proceedings Electronic Technology Directions to the Year 2000, 2002Computer based process control systems have been used successfully for a number of years. However, these systems are often highly mathematical, are difficult to understand and implement, and are also inflexible. Fuzzy logic was developed in the early to mid 1960s by Lotfi Zadeh as an alternative to these complex traditional computer control schemes ...
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2018
In Chap. 5, we provided detailed discussions about the classical linear control systems or PID control systems with various design methods. One of the most important and critical key requirements to design and implement a PID control system is that the dynamic model of the process or plant is the prerequisite condition .
Ying Bai, Zvi S. Roth
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In Chap. 5, we provided detailed discussions about the classical linear control systems or PID control systems with various design methods. One of the most important and critical key requirements to design and implement a PID control system is that the dynamic model of the process or plant is the prerequisite condition .
Ying Bai, Zvi S. Roth
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Modelling on fuzzy control systems
Science China Mathematics, 2002A kind of modelling method for fuzzy control systems is first proposed here, which is called modelling method based on fuzzy inference (MMFI). It should be regarded as the third modelling method that is different from two well-known modelling methods, that is, the first modelling method, mechanism modelling method (MMM), and the second modelling method,
Wang Jiayin, Miao Zhihong, LI Hong-xing
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Fuzzy Control Systems: A Retrospective
1983 American Control Conference, 1983One of the most active areas for the application of fuzzy set theory has been in process control. We trace the development of this research, from the first papers by Zadeh to current efforts in both theory and practice. We review some themes that appear in this corpus and suggest some directions for future work.
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1983 American Control Conference, 1983
Summary form only given. The ability of robots to perform desired tasks requires that the robot be supplied with a mechanism in which to carry out the planning of the actions necessary to carry out these tasks. Reference is made to pertinent research by N. Nilsson and others.
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Summary form only given. The ability of robots to perform desired tasks requires that the robot be supplied with a mechanism in which to carry out the planning of the actions necessary to carry out these tasks. Reference is made to pertinent research by N. Nilsson and others.
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Accessibility of Fuzzy Control Systems
2011This paper presents a systematic methodology for delineating the accessibility of fuzzy logic control systems (FLCSs). Accessibility is an essential prior step for determining the controllability of plants in which the state trajectories are verified if they are accessible to a full dimension set.
Alireza Sadeghian +2 more
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Fuzzy Systems, Control, and Connectionism
Kybernetes, 1994Considers and defends the realist understanding of the notion of fuzzy system, that is, the view that fuzzy functions are ontologically respectable for scientific explanations of fuzzy controllers. Looks at the arguments concerned with the revival of fuzzy set theories based on the idea of representation.
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