Title :
Model predictive control of DC/DC converter for ultracapacitors energy storage union based on T-S model
Author :
Jianfeng Liu ; Qing Yan ; Zhiwu Huang ; Cheng Luo
Author_Institution :
Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
Abstract :
Ultracapacitors is becoming increasingly popular as an energy storage device for the power system. In reality, the control of the DC/DC converter is still a challenging problem to meet the precise charging/discharging of ultracapacitors. In this paper, a discrete-time converter model and a model predictive control scheme are proposed to address this issue. The model is presented by using T-S fuzzy model, which can solve the difficulties in the controller design of the DC/DC converter with nonlinear characteristics. Based on this model, an optimal control problem with the constraints of the duty cycle and the system parameters is formulated. The T-S based model predictive control approach is introduced to design a control system for a highly nonlinear process. In this approach, a process system is described by a fuzzy convolution model. In the controller design, prediction errors and control energy are minimized through an optimization process. A Kalman filter based state estimating is to account for unmeasured load variations and to achieve zero steady-state output error. The proposed scheme can also achieve the real-time control of the system. The simulation and experimental results validate the effectiveness and stability of the designed controller.
Keywords :
DC-DC power convertors; Kalman filters; control system synthesis; discrete time systems; energy storage; fuzzy control; load management; minimisation; nonlinear control systems; optimal control; power system control; power system state estimation; predictive control; supercapacitors; DC-DC converter; Kalman filter based state estimation; T-S fuzzy model; control energy minimization; controller design; discrete-time converter model; duty cycle constraints; energy storage device; fuzzy convolution model; model predictive control scheme; nonlinear characteristics; optimal control problem; optimization process; power system; prediction errors; system parameters; ultracapacitors charging; ultracapacitors discharging; ultracapacitors energy storage union; unmeasured load variations; zero steady-state output error; Integrated circuit modeling; Mathematical model; Predictive control; Predictive models; Supercapacitors; Voltage control; DC/DC converter; Kalman filter based state estimating; T-S fuzzy model; Ultracapacitors; model predictive control;
Conference_Titel :
Energy Conversion Congress and Exposition (ECCE), 2014 IEEE
Conference_Location :
Pittsburgh, PA
DOI :
10.1109/ECCE.2014.6953712