Model Based Fuzzy Control

Palm, Rainer; Hellendoorn, Hans; Driankov, Dimiter

doi:10.1007/978-3-662-03401-9

Cited by 163 publications

(63 citation statements)

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“…For w ij ob = 1 the results of (24) and (20) are the same which is however not the case for w ij ob = 1.…”

Section: B Mbo Between Active Mobile Platforms and Passive Obstaclesmentioning

confidence: 77%

“…4. Z -ZERO, S -SMALL, M -MEDIUM, B -BIG are fuzzy sets (see [20]). The corresponding membership functions µ α , µ vt , and µ coef are triangular and shown in Fig.…”

Section: B "Deformation" Of Potential Fields Using Fuzzy Rulesmentioning

confidence: 99%

“…Coming back to the equation of the system of mobile robots (10) (20) where vo i is a subset of the RHS of (5) -a combination of different velocities (tracking velocity, control terms, etc. ), v ij p reflects the repelling forces between platforms P i and P j .…”

Section: A Mbo Between Active Mobile Platformsmentioning

confidence: 99%

“…The difference between (24) and (20) is that in (20) the repulsive velocities between platforms and obstacles v ij ob are included in vo i whereas in (24) v ij ob appear explicitely. For w ij ob = 1 the results of (24) and (20) are the same which is however not the case for w ij ob = 1.…”

Section: B Mbo Between Active Mobile Platforms and Passive Obstaclesmentioning

confidence: 99%

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Market-based algorithms and fuzzy methods for the navigation of mobile robots

Palm

Bouguerra

2012

2012 IEEE International Conference on Fuzzy Systems

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Abstract-An important aspect of the navigation of mobile robots is the avoidance of static and dynamic obstacles. This paper deals with obstacle avoidance using artificial potential fields and selected traffic rules. The potential field method is optimized by a mixture of fuzzy methods and market-based optimization (MBO) between competing potential fields of mobile robots. Here, depending on the local situation, some potential fields are strengthened and some are weakened. The optimization takes place especially when several mobile robots act in a small area. In addition, to avoid an undesired behavior of the mobile platform in the vicinity of obstacles, central symmetrical potential fields are 'deformed' by using fuzzy rules.

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“…For w ij ob = 1 the results of (24) and (20) are the same which is however not the case for w ij ob = 1.…”

Section: B Mbo Between Active Mobile Platforms and Passive Obstaclesmentioning

confidence: 77%

“…4. Z -ZERO, S -SMALL, M -MEDIUM, B -BIG are fuzzy sets (see [20]). The corresponding membership functions µ α , µ vt , and µ coef are triangular and shown in Fig.…”

Section: B "Deformation" Of Potential Fields Using Fuzzy Rulesmentioning

confidence: 99%

Section: A Mbo Between Active Mobile Platformsmentioning

confidence: 99%

Section: B Mbo Between Active Mobile Platforms and Passive Obstaclesmentioning

confidence: 99%

See 2 more Smart Citations

Market-based algorithms and fuzzy methods for the navigation of mobile robots

Palm

Bouguerra

2012

2012 IEEE International Conference on Fuzzy Systems

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“…Fuzzy systems, more specifically fuzzy knowledge-based systems (FKBS) or fuzzy rulebased systems (FRBS), are significantly applicable in areas like control [1], classification [2], and modeling [3]. The essential feature of FKBS is the incorporation of human expert knowledge which is in the form of fuzzy [4] extended if-then rules.…”

Section: Introductionmentioning

confidence: 99%

A new approach for tuning interval type-2 fuzzy knowledge bases using genetic algorithms

Shukla

Tripathi

2014

J. Uncertain. Anal. Appl.

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Fuzzy knowledge-based systems (FKBS) are significantly applicable in the area of control, classification, and modeling, having knowledge in the form of fuzzy if-then rules. Type-2 fuzzy theory is used to make these systems more capable of dealing with inherent uncertainties in real-world problems. In this paper, the authors have proposed a genetic tuning approach named lateral displacement and expansion/compression (LDEC) in which α and β parameters are calculated to adjust the parameters of interval type-2 membership functions. α tuning deals with lateral displacement, whereas β tuning carries out compression/expansion operation. The interpretability and accuracy features are considered during the development of this approach. The experimental results show the performance of the proposed approach.

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Foundations of Fuzzy Control

Jantzen¹

2013

163

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Model Based Fuzzy Control

Cited by 163 publications

References 0 publications

Market-based algorithms and fuzzy methods for the navigation of mobile robots

Market-based algorithms and fuzzy methods for the navigation of mobile robots

A new approach for tuning interval type-2 fuzzy knowledge bases using genetic algorithms

Foundations of Fuzzy Control

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