Abstract
In this paper, a large–order system is reduced by using the self adaptive bat algorithm (SABA) to a reduced-order approximation. The numerator coefficients of a desired reduced-order system are optimized based on integral square error minimization as an objective function pertaining to a unit-step as input. The denominator of the reduced order model is solved by stability equation method. The efficacy of the proposed method is tested with SMIB test systems to get a corresponding reduced-order system. The results are satisfactory in terms of minimum error with the proposed method as compared to Routh approximation and Stability equation based reduced models.
Highlights
High-order system (HOS) is always costly and tedious
Many methods to solve HOS for reduced order model (ROM) of the system are available in literature [2, 3]
Model order reduction using stability equation method [18] and the continued fraction method [19] have been considered for deduction of model order reduction (MOR) systems
Summary
High-order system (HOS) is always costly and tedious. MOR is used for simplification of complicated problems in HOS. The selection of the model reduction technique is based on stability equation method as presented in [1]. Model order reduction using stability equation method [18] and the continued fraction method [19] have been considered for deduction of MOR systems. Alsmadi et al have presented the application of Sylvester based model order reduction for a multi-input multi-output (MIMO) power system [27]. It is based on the preservation of stability by retaining dominant poles and minimization of steady-state error. The application of stability equation method is presented for driving reduced order model of the higher or-.
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