Passing from a gas to an electric water heater system: adaptive PID versus Smith predictive control
Type
article
Creator
Publisher
Identifier
VIEIRA, José; MOTA, Alexandre (2007) - Passing from a gas to an electric water heater system: adaptive PID versus Smith predictive control. In International Conference on Intelligent Engineering Systems,11,Budapeste,29 Junho-2 Julho. [S. l.]: IEEE. p. 201-206
Title
Passing from a gas to an electric water heater system: adaptive PID versus Smith predictive control
Subject
Adaptive PID
Electrical water heater
Physical model identification
Smith predictive control
Electrical water heater
Physical model identification
Smith predictive control
Date
2011-12-07T18:12:51Z
2011-12-07T18:12:51Z
2007-06-29
2011-12-07T18:12:51Z
2007-06-29
Description
“Copyright © [2007] IEEE. Reprinted from 11th International Conference on Intelligent Engineering Systems , 2007. ISBN:1-4244-1147-5
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This paper presents the control results of an electric water heater system using two approaches: adaptable proportional integral derivative and Smith predictive control based in the physical internal model control structure. The electric water heater was modelled with two variable blocks connected in series: a first order system and a time delay. In fact, the gain, the time constant and the time delay of the system change linearly with the water that flows in the permutation chamber. The physical model of the electric water heater system was retched based in energy dynamic equations and validated with open loop data of the system in a similar way that was made in a previews study about modelling and controlling a gas water heater. The two different control algorithms explored are the adaptive proportional integral derivative (APID) and the Smith predictive control (SPC) based in the internal physical model control algorithm. The first approach has some problems dealing with the time constant and the time delay variations of the system. This solution can control the overshoot for all different water flows but the time constant of the close loop systems changes with the water flow. The APID does not deal well with water flow variations. The second approach is more adequate to control this kind of systems (first order system followed by a time delay that changes in time). The SPC loop is indicated for control time delay systems and with the à priori knowledge of the physical model we can achieve a very good control result. Finally, these two algorithms are applied in controlling the system and the results are compared using the mean square error criterion.
This paper presents the control results of an electric water heater system using two approaches: adaptable proportional integral derivative and Smith predictive control based in the physical internal model control structure. The electric water heater was modelled with two variable blocks connected in series: a first order system and a time delay. In fact, the gain, the time constant and the time delay of the system change linearly with the water that flows in the permutation chamber. The physical model of the electric water heater system was retched based in energy dynamic equations and validated with open loop data of the system in a similar way that was made in a previews study about modelling and controlling a gas water heater. The two different control algorithms explored are the adaptive proportional integral derivative (APID) and the Smith predictive control (SPC) based in the internal physical model control algorithm. The first approach has some problems dealing with the time constant and the time delay variations of the system. This solution can control the overshoot for all different water flows but the time constant of the close loop systems changes with the water flow. The APID does not deal well with water flow variations. The second approach is more adequate to control this kind of systems (first order system followed by a time delay that changes in time). The SPC loop is indicated for control time delay systems and with the à priori knowledge of the physical model we can achieve a very good control result. Finally, these two algorithms are applied in controlling the system and the results are compared using the mean square error criterion.
Access restrictions
openAccess
Language
eng
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