Contributions to the model reduction problem

Gutman, Per‐Olof; Mannerfelt, Carl-Fredrik; Molander, Per

doi:10.1109/tac.1982.1102930

Cited by 157 publications

(20 citation statements)

References 3 publications

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“…2) Differentiation method [29]: This method is based on differentiation of polynomials of numerator and denominator of transfer function and then adjusting the gain of the reduced model with original system to obtain the correct steady state response. On applying this technique, the reduced transfer function becomes…”

Section: B Reduced Model Identificationmentioning

confidence: 99%

“…Therefore, we can involve this state of the art MOR concept to derive optimal controller. Moreover, MOR has wide application in simulation and optimization of system modeling but its utility in controller synthesis is less reported [24], [25]. Our aim is to show that PI controller for same the performance objectives can replace the PID controller easily.…”

Section: Introductionmentioning

confidence: 99%

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Dimensionality reduction based IMC-PI tuning for DC servomotor

Saxena

Hote

2016

2016 Indian Control Conference (ICC)

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In this paper, an internal model control (IMC) based proportional integral (PI) controller is designed for DC servomotor using the concept of model order reduction. The beauty of the presented approach is that the optimal performance can be achieved by lower-order controller, hence reduces the size of the controller. Moreover, there is no need for extra filter which is generally augmented with IMC-PID controller. Particularly here, it is shown that without using additional filter, the performance of IMC-PI controller is better in comparison to IMC-PID controller with additional filter. The proposed methodology has been validated on an experimental set up of precision modular servo (PMS) system using its different reduced-order models. Further, it is shown that the reduced model based on Routh array is the best suited for obtaining optimal performance for speed control of PMS system.

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Section: B Reduced Model Identificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dimensionality reduction based IMC-PI tuning for DC servomotor

Saxena

Hote

2016

2016 Indian Control Conference (ICC)

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“…In this final example, we will consider an eighth-order system TF that has been recently considered by different researchers [16,[37][38][39][40]. However, we will now apply the proposed GA reduction method without the restriction of retaining the system dominant frequencies in the reduced-order model.…”

Section: Examplementioning

confidence: 99%

Genetic algorithm approach with frequency selectivity for model order reduction of MIMO systems

Alsmadi

Abo-Hammour

Al-Smadi

et al. 2011

Mathematical and Computer Modelling of Dynamical Systems

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A novel genetic algorithm (GA) approach with frequency selectivity advantage for model order reduction (MOR) of multi-input-multi-output (MIMO) systems is presented in this article. Motivated by singular perturbation and other reduction techniques, the new MOR method is formulated using GAs, which can be applied to single-input-single-output (SISO)-or MIMO-type systems. The GA procedure is based on maximizing the fitness function corresponding to the response deviation between the full-order model and the reduced-order model with the option of substructure preservation. The proposed GA-MOR method is compared to the well-known reduction techniques, such as the Schur decomposition balanced truncation, proper orthogonal decomposition (POD) and state elimination through balancing-related frequency-weighted realization in addition to other recent methods. Simulation results validate the superiority and robustness of the new MOR technique as it can search the solution space for almost optimal solutions.

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“…Differentiation method [29] was proposed by Gutman for fixed coefficients and Author has extended this method to interval systems and also proposes some new mixed methods.…”

Section: Introductionmentioning

confidence: 99%