칠러장비의 온도제어를 위한 최적 PID 제어
Optimal PID Control for Temperature Control of Chiller Equipment
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초록
The demand for chiller equipment that keeps each machine at a constant temperature to maintain the best possible condition is growing rapidly. PID (Proportional Integral Derivation) control is a popular temperature control method. The error, which is the difference between the desired target value and the current system output value, is calculated and used as an input to the system using a proportional, integrator, and differentiator. Through such a closed-loop configuration, a desired final output value of the system can be reached using only the target value and the feedback signal. Furthermore, various temperature control methods have been devised as the control performance of various high-performance equipment becomes important. Therefore, it is necessary to design for accurate data-driven temperature control for chiller equipment. In this research, support vector regression is applied to the classic PID control for accurate temperature control. Simulated annealing is applied to find optimal PID parameters. The results of the proposed control method show fast and effective control performance for chiller equipment.
Abstract
The demand for chiller equipment that keeps each machine at a constant temperature to maintain the best possible condition is growing rapidly. PID (Proportional Integral Derivation) control is a popular temperature control method. The error, which is the difference between the desired target value and the current system output value, is calculated and used as an input to the system using a proportional, integrator, and differentiator. Through such a closed-loop configuration, a desired final output value of the system can be reached using only the target value and the feedback signal. Furthermore, various temperature control methods have been devised as the control performance of various high-performance equipment becomes important. Therefore, it is necessary to design for accurate data-driven temperature control for chiller equipment. In this research, support vector regression is applied to the classic PID control for accurate temperature control. Simulated annealing is applied to find optimal PID parameters. The results of the proposed control method show fast and effective control performance for chiller equipment.
참고문헌 (12)
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