www.ijep.org International Journal of Energy and Power (IJEP) Volume 4, 2015 doi: 10.14355/ijep.2015.04.015
Parallel Constrained Control for Solid Oxide Fuel Cell Based on PID and CMAC Neural Network Dezhi Xu*1, Nan Ji1, Yao Tang2 Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation, Jiangnan University, Wuxi, 214122, China 1
Editorial Office of Journal Systems Engineering and Electronics, Beijing, 100854, China
2
*1Email: xudezhi@jiangnan.edu.cn
Abstract This paper proposes a cerebellar model articulation controller (CMAC) based parallel adaptive constrained PID control scheme for a solid oxide fuel cell (SOFC). Conventional PID controller with fixed parameters can hardly adapt to time varying of characteristics in wide range. To improve the control performance, CMAC is used to learn the controller through parallel structure. At same time, in order to solve the input saturation problem, we design an anti‐windup compensator for accommodating the reference. Finally, the simulation results on the dynamic model of SOFC are provided to demonstrate the effectiveness of the proposed constrained control approach. Keywords Cerebellar Model Articulation Controller; Solid Oxide Fuel Cell; Constrained PID; Anti‐Windup
Introduction Solid oxide fuel cells (SOFCs) are a class of fuel cells characterized by the use of a solid oxide material as the electrolyte. SOFCs use a solid oxide electrolyte to conduct negative oxygen ions from the cathode to the anode. The electrochemical oxidation of the oxygen ions with hydrogen or carbon monoxide thus occurs on the anode side. Therefore, a great deal of attention is paid to the use of SOFCs to generate electricity. Because the SOFCs do not produce radiation or air pollution, it is forming a wave in the world [1]. But it presents a challenging control problem owing to slow dynamics, nonlinearity and tight operating constraints of the SOFC [2‐4]. In order to prevent over used and under used fuel conditions, the desired range of fuel utilization is from 0.7 to 0.9. And in practice, the actuator saturation problem needs to be considered. At present, most control approach of SOFCs focus on predictive control [3‐7]. In [3], the authors developed a novel offset free input to state stable fuzzy predictive controller via identified fuzzy model. A fuzzy Hammerstein model based model predictive control of an SOFC was presented in [6]. The PID controllers are widely used in the industrial process control because of their simplicity and robustness. Conventional PID controller with fixed parameters can hardly adapt to time varying of characteristics in wide range. To improve the control performance, several schemes of self‐tuning PID controllers were proposed in the past [8‐11]. However, few self‐tuning PID methods consider the actuator saturation problem. If the actuator saturation factor is not considered, the integral part of PID may appear saturated and parameter estimation may diverge. In this paper, we focus on how to design parallel PID and Cerebellar Model Articulation Controller (CMAC) constrained controller. In order to fulfill the requirements for fuel utilization and control constraints, a dynamic constraint unit and an anti‐windup scheme are adopted. The rest of this paper is organized as follows. In Section II, a brief description of the SOFC is given. Next, main result of parallel PID and CMAC constrained control is proposed in Section III. Simulation results are presented to show the effectiveness of the proposed technique in Section IV. Finally, some conclusions are made at end of this paper.
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