Model predictive controller design for boost DC–DC converter using T–S fuzzy cost function. Issue 11 (2nd November 2017)

• Record Type: Journal Article
• Authors: Seo, Sang-Wha; Kim, Yong; Choi, Han Ho
• Is Part Of: International journal of electronics. Volume 104:Issue 11(2017)
• Page Start: 1838
• Page End: 1853
• Publication Date: 2017-11-02
• Subjects: Finite control set model predictive control (FCSMPC) -- Takagi–Sugeno (T–S) fuzzy system -- DC–DC converter -- boost converter -- optimal control; Electronics -- Periodicals; Electronic control -- Periodicals; 621.381
• DOI: 10.1080/00207217.2017.1329945
• Languages: English
• ISSNs: 0020-7217

Abstract

ABSTRACT: This paper proposes a Takagi–Sugeno (T–S) fuzzy method to select cost function weights of finite control set model predictive DC–DC converter control algorithms. The proposed method updates the cost function weights at every sample time by using T–S type fuzzy rules derived from the common optimal control engineering knowledge that a state or input variable with an excessively large magnitude can be penalised by increasing the weight corresponding to the variable. The best control input is determined via the online optimisation of the T–S fuzzy cost function for all the possible control input sequences. This paper implements the proposed model predictive control algorithm in real time on a Texas Instruments TMS320F28335 floating-point Digital Signal Processor (DSP). Some experimental results are given to illuminate the practicality and effectiveness of the proposed control system under several operating conditions. The results verify that our method can yield not only good transient and steady-state responses (fast recovery time, small overshoot, zero steady-state error, etc.) but also insensitiveness to abrupt load or input voltage parameter variations.