An application of fuzzy logic control to a gimballed payload on a space platform

Woodard, Stanley E.; Garg, Devendra P.; Tyan, Ching Yu; Wang, Paul P.

doi:10.1016/1069-0115(95)90037-3

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…To date, almost all FLCs use only "if-then" rules. The basic scheme of using FLC for feedback error control is to generate a control input based upon error information resulting from feedback [5][6][7]21. The control input to the system is a desired or referenced input.…”

Section: Introductionmentioning

confidence: 99%

A numerical optimization approach for tuning fuzzy logic controllers

Woodward

Garg

1999

IEEE Trans. Syst., Man, Cybern. B

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This paper develops a method to tune fuzzy controllers using numerical optimization. The main attribute of this approach is that it allows fuzzy logic controllers to be tuned to achieve global performance requirements. Furthermore, this approach allows design constraints to be implemented during the tuning process. The method tunes the controller by parameterizing the membership functions for error, change-in-error and control output.The resulting parameters form a design vector which is iteratively changed to minimize an objective function. The minimal objective function results in an optimal performance of the system. A spacecraft mounted science instrument line-of-sight pointing control is used to demonstrate results.

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Section: Introductionmentioning

confidence: 99%

A numerical optimization approach for tuning fuzzy logic controllers

Woodward

Garg

1999

IEEE Trans. Syst., Man, Cybern. B

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Perspectives in the use of geno-fuzzy tools for spacecraft control systems

Ortega

Girón-Sierra²

1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation

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Tools and methods for spacecraft control systems: a geno-fuzzy approach

Ortega

Girón-Sierra²

SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218)

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The goal of the paper is to analyze which computational methods and modeling tools based on Fuzzy Logic helped by Genetic Algorithms are available right now. The emphasis is put on the analyses and design of spacecraft control systems due to its complexity. A spacerraft control system measures the position and attitude of the craft and produces guidance and rotation commands to place it in a specific orbit and with a specific orientation. Spacecraft control units are complex systems difficult to handle during the analysis and design phases of the engineering life cycle.The article describes who-is-who in the development arena of the support tools and methods, which commercial products are available, and which of them are freely obtainable. T.L-InL: s12ut: _A_&. af disadvantages of each system are carefully examined h m a critical point of view. is w6ent& & & dvaAw & 1. FUZZY LOGIC AND GENETIC ALGORITHMS FOR SPACECRAFT CONTROLFor a relatively small servicing spacecraft, the control requirements demand a high degree of uncertainty in critical vehicle parameters like total mass, feed-forward thrust impulses, moments of inertia, center of mass, etc. These requirements are translated into huge complexity during the design phase: the navigation block is based on complicated filtering schemes, the guidance block is made of parameter tables of considerable size, with contingency recovery situations, and the control block must be designed wing multiple input-output techniques for a sixdegree-of-freedom vehicle. Much of this complexity in the design of the control system comes from the way in which the variables of the system are represented and manipulatedIn the search for an easy, efficient, cost-effective control design and development technique, fuav logic ( I T ) seems to provide a method of reducing system complexity while haeasing control performance. Fuzzy set theory was originally introduced by Prof. Zadeh in 1965 [12][13]. Since then, many researchers have introduced fuav logic techniques to solve different types of control problems [3][4]. The ability to model problems in a simple and human-oriented way [9][26], and the ability to produce smooth control actions around the set points makes fuzzy logic an especially suitable candidate for use in space applications [171[20][211[231. While the fuzzy controller deals with the uncertainty of the model of the vehicle, the genetic algorithm tries to optimize the 0-7803-4778-1/98 510.00 0 1998 IEEE 31 67 controller for a particular constraint. 'Ihe controller will try to cope with the nonlinear equations of motion of the spacecraft dynamics and kinematics, and the imperfections in sensors and actuators.Fuzzy systems have two parameters, which can be optimized: a rule database and the ~~.IZZY sets. Two approaches can be taken to obtain an optimum solution: either using the heuristic method, in which the control engineer obtains the best system to satis@ the criteria, or by finding an analytical solution to the problem. On most occasions, the design of the optimum system r...

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An application of fuzzy logic control to a gimballed payload on a space platform

Cited by 3 publications

References 4 publications

A numerical optimization approach for tuning fuzzy logic controllers

A numerical optimization approach for tuning fuzzy logic controllers

Perspectives in the use of geno-fuzzy tools for spacecraft control systems

Tools and methods for spacecraft control systems: a geno-fuzzy approach

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