An AHP based optimized tuning of Modified Active Disturbance Rejection Control: An application to power system load frequency control problem. (October 2018)

• Record Type: Journal Article
• Authors: Srikanth, M.V.; Yadaiah, Narri
• Is Part Of: ISA transactions. Volume 81(2018)
• Page Start: 286
• Page End: 305
• Publication Date: 2018-10
• Subjects: Modified Active Disturbance Rejection Control -- Model-assisted-Extended State Observer -- Analytical Hierarchical Process -- Teaching-Learning Based Optimization -- Load frequency control; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2018.07.001
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: This paper presents Modified Active Disturbance Rejection Control (MADRC) scheme and a systematic procedure to tune its tuning variables via. observer and controller gains. The problem of tuning is formulated as a constrained multi-objective optimization problem. Depending upon the application appropriate objective functions are chosen, and a unified objective is developed based on weighted sum approach. Five different weight combinations are considered, which result in five objective functions. Each objective function is individually optimized using Teaching-Learning Based Optimization (TLBO), this leads to five sets of tuning variables. Best among five alternatives will be selected based on Analytical Hierarchy Process (AHP). The effectiveness of this approach is validated through its application to a power system with load frequency control problems. Different simulation examples involving single-area and multi-area power systems are considered in the presence of sudden load disturbances, model uncertainties, and parameter variations. Further stability analyses are carried out in a standard two-degree of freedom Internal Model Control (IMC) framework. Highlights: Design of MADRC involving model assisted ESO and state feedback control law. New tuning procedure for obtaining optimal parameters ω0 and ωc for fast estimation and improved performance. Efficacy of the proposed method is validated through its application on single area and multi-area power system models. Stability analysis of the proposed scheme is carried out in a standard two-degree of freedom Internal Model Control scheme.