Interpolative-Type Control Solutions

Dale, Sanda; Dragomir, Toma-Leonida

doi:10.1007/978-3-642-00448-3_9

Cited by 8 publications

(10 citation statements)

References 4 publications

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“…The results allow to consider pure interpolative algorithms implemented as interpolative blocks and used in control structures as candidates for implementation on microcontrollers. One of the advantages of using such blocks are, mainly, based on simplifying the solutions (easier implementation and reduced calculus time, meaning the first requirement is fulfilled) and the possibility to ensure for the control systems, in a relative easy way, some robustness properties [5]. In the same time, as in [4], [6] and [9], the controllers based on interpolation table, on the same form as in Drechsels RIP (Regelbasierte Interpolation) controllers introduced in [12], can be developed in much more situations than those based on linguistic rules.…”

confidence: 99%

“…The controllers with interpolative blocks as introduced in [5] and [9] represents an alternative to the controllers obtained by various design procedures, that are replaced with controllers containing interpolation tables and algorithms and participate to the partial or integral control law elaboration. The idea of using interpolative blocks, named also table-type blocks its not a new one.…”

Section: Design Procedures For Controllers With Interpolative Blocks mentioning

confidence: 99%

“…In the present paper the interpolative blocks will be synthesized through the method exposed above, as in [5] and [9], followed by off-line GA-based correction, as in [6] and [4]. GA-based techniques seems very appropriate in such cases due to the fact that GAs represent themselves improvement methods based on natural and genetic selection, compare and sorting mechanisms, which combine artificial surviving of best individuals with specific natural operators and form a searching mechanism, usable in various purposes.…”

Section: Design Procedures For Controllers With Interpolative Blocks mentioning

confidence: 99%

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Intelligent Design Environment for Second-Order Positioning Systems

Dale

Silaghi

Zmaranda³

et al. 2014

INT J COMPUT COMMUN

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From the designer perspective, in real-time applications as mechatronic systems -the control algorithm has to be easy to understand and to implement, easy to optimize and last but not least, to ensure the best possible behavior for the controlled system. The paper presents a design environment which provides the possibility to choose between a classical control algorithm (as state feedback stabilization represents) and a new approach (interpolative controllers) with the possibility to modify the designed parameters such as to obtain the optimum behavior for the controlled system. This opportunity is given through the inner structure and operating laws of the algorithm and exploited using genetic algorithm-based techniques. Interpolative-type controller category covers the controllers based on fuzzy, neural and pure interpolative algorithms, due to their common capability to make an approximate reasoning. The first ones, fuzzy and neural algorithms, are already well-known in the control area. A pure interpolative controller presumes to contain at least one block, placed no matter where in his structure, in which interpolation as mathematical operation to have place. The approach presented in the present paper uses this kind of blocks to reproduce and to optimize the behavior of an already existing controller (in this case the state feedback one) [1]. This type of controllers meets all the requirements stated at the beginning: they are easy to implement, easy to understand, they need reduced calculus time and gives notable results in specific cases. The above mentioned kind of controllers will be presented with all the necessary details in the paper. The design environment is presented as a collection of MATLAB functions, SIMULINK configurable schemes and a user interface. A case study ends the presentation with some experimental results obtained through a simulation for a specific second order positioning system.

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confidence: 99%

Section: Design Procedures For Controllers With Interpolative Blocks mentioning

confidence: 99%

Section: Design Procedures For Controllers With Interpolative Blocks mentioning

confidence: 99%

See 1 more Smart Citation

Intelligent Design Environment for Second-Order Positioning Systems

Dale

Silaghi

Zmaranda³

et al. 2014

INT J COMPUT COMMUN

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“…The RIP (Rule Based Interpolation) method, proposed by Dirk Drechsel (Regelbasierte Interpolation und fuzzy Control, Vieweg, 1996) is the most direct application of the interpolative networks in the automatic control [1,2]. The rule based systems are able to represent and process expert knowledge.…”

Section: Introduction the Interpolative Systemsmentioning

confidence: 99%

On the FPGA implementation of the fuzzy-interpolative systems

Bălaş

Sajgo

Belean

2011

2011 5th International Symposium on Computational Intelligence and Intelligent Informatics (ISCIII)

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The interpolative networks represent a familiar concept in our reasoning. On behalf of their ability to approximate with low costs the usual engineering mathematical functions, the linear interpolations are widely used by the intelligent control systems (RIP method for instance). A relatively new technology, the FPGA, promises new steps forward in the field of the control applications using interpolative networks, in terms of reducing the costs, increasing the operation speed, etc. The paper presents a bird's eye view on the field and a FPGA implementation of a controller able to perform linear implementations.

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“…Generally, the interpolative controllers implement the control algorithms through support points defined in interpolative blocks, which are used either alone as in [4], or integrated in dynamic structures (as in [1] and [2]). …”

Section: Introductionmentioning

confidence: 99%