A New Technique of Reduction for the SISO and MIMO System Model for the Compensator Design
A New Technique of Reduction for the SISO and MIMO System Model for the Compensator Design |
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| © 2023 by IJETT Journal | ||
| Volume-71 Issue-6 |
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| Year of Publication : 2023 | ||
| Author : Pragati Shrivastava Deb, Leena G. |
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| DOI : 10.14445/22315381/IJETT-V71I6P223 | ||
How to Cite?
Pragati Shrivastava Deb, Leena G., "A New Technique of Reduction for the SISO and MIMO System Model for the Compensator Design," International Journal of Engineering Trends and Technology, vol. 71, no. 6, pp. 221-234, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I6P223
Abstract
This paper aims to introduce a novel approach for minimizing the order of time-invariant SISO & MIMO high-order systems. A novel mixture of two methods is proposed to acquire the preferred approximated stable model, which conserves the basic structures of the high-order actual plant. The suggested approach retains the original plant dominant poles to acquire approximated model denominator using the advantages of the reciprocal transformation. However, the numerator of ROM is acquired by diminishing the inaccuracy between the transitory part of responses of HOS and the reduced model using the particle swarm optimization algorithm (PSO). Particularly the proposed reduction method is appropriate to the systems which are controlled by large magnitude poles as the usual dominant pole retention methods will lead to bad approximant in such cases. Further, the compensation is designed using the approximated reduced model acquired from the advised reduction methodology for controlling the high-order plant using a new algorithm. The efficacy of the suggested methodology is confirmed by matching responses of time & frequency of the larger and the reduced order models. The suggested technique’s accuracy is verified by calculating performance error indices. Taking into account three standard examples, the performance, usefulness and accuracy of work suggested to reduce system order were validated and also showed that the suggested reduction methodology is suitable for the design of compensation.
Keywords
Reduced order model, Compensator, Particle swarm optimization algorithm, Dominant pole, Reciprocal transformation.
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