Temperature Control System Based on Fuzzy Self-Adaptive PID Controller

Xin, Hongbo; Huang, Ting-lei; Liu, Xiaoyu; Tang, Xiangjiao

doi:10.1109/wgec.2009.45

Cited by 5 publications

(3 citation statements)

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“…Additional file 1. Fuzzy Control Rules [20,21]. Authors' contributions AG developed the theoretical formalism, performed the analytic calculations, and performed the numerical simulations.…”

Section: Simulation Modelmentioning

confidence: 99%

Looper and tension control in hot strip finishing mills based on different control approaches

2022

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The looper control of hot strip finishing mill is one of the most critical control items in hot strip rolling mill process. It is a highly complex nonlinear system, with strong states coupling and uncertainty that present a difficult control challenge. Loopers are placed between finishing mill stands not only to control the mass flow of the two stands but also to generate a constant specific strip tension during rolling, independent of the actual strip stock which influences the width of the strip. Some of the applicable control architectures for the finishing mill are reviewed. Two general approaches are considered: the first is based on a loop or SISO (single input single output) strategy, while the second is based on a MIMO strategy:In the loop approach, two different schemes are considered with distinct loop configuration. For both schemes, PID and fuzzy-PID are considered for comparison purposes. Since in the second scheme the most important loop is the looper control loop, it is investigated whether a nonlinear sliding mode control can significantly improve the response.In the multi-variable or MIMO approach, standard LQR (linear quadratic regulator) is investigated after linearization of the system.

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Section: Simulation Modelmentioning

confidence: 99%

Looper and tension control in hot strip finishing mills based on different control approaches

2022

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“…In the formula above, KP is the scale factor, TI is the integral time constant, TD is the derivative time constant. Functions of all the calibration parts in the PID control model are [4]:…”

Section: Fig 1 Pid Control Modelmentioning

confidence: 99%

The Design and Implementation of an Automatic Tracking System of Solar Energy Based on the PID Control Algorithm

Zhao

Man

2011

AMM

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This text, under the guidance of PID control algorithm, designs and implements a new type of solar water heater which can change orientation of its solar panel in real time to automatically follow the direction where the light is strongest by sensing the incident angle of the sun. Tests show that the new solar water heater can succeed in keeping a real-time trace of light source, which can effectively meliorate the traditional solar water heater's shortcoming of producing insufficient heat in winter in some areas and greatly improve the utilization efficiency of solar energy.

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“…In this research, one possible application of fuzzy logic will be proposed, whose performances will be compared both with the reference building in its current operation and with those ones provided by ordinary PID control, that was widely used in HVAC systems, as proved in many research works [5], [6]. Sometimes, fuzzy logic was integrated with PID control units in order to adjust their parameters according to control needs [7]. In this paper we will apply fuzzy logic as the supervisor sub-system of several local PID controllers.…”

Section: Introductionmentioning

confidence: 99%

Design and Simulation of a Fuzzy Supervisory Control System Integrated in a Small Public Building

Carbonari¹,

Meschini²,

Benedettelli³

2016

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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-Public administrations are encouraged to adopt actions for energy requalification of public buildings, which are responsible for considerable amounts of energy consumption. Low-cost technology improvements for energy renovation with high return on investment is a good opportunity when resource shortage hampers the adoption of expensive refurbishment. To this purpose, the integration of advanced control policies may optimize energy use of buildings with minimum hardware enhancement.In this contribution, we evaluated the performances of a control system based on fuzzy logic, supervising local Proportional-IntegrativeDerivative (PID) controllers, through numerical simulation. First, the design process will be described, with particular concern to the proper selection of the rules in the knowledge base and the design of the inference engine. Then, its performances will be compared with the ones provided by the use of just ordinary PID control units. The fuzzy based control system was simulated as an addiction to the heating system of an existing small public building, that is the "San Elpidio a Mare" community clinic located in Italy. The performances were assessed by means of simulations of an energy dynamic model developed in the Dymola TM environment, that had been previously validated with real consumption measurements. In this paper we will show not only what energy saving can be obtained by means of the fuzzy supervisor, but also its satisfactory performances in terms of stability of the control outputs.

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Temperature Control System Based on Fuzzy Self-Adaptive PID Controller

Cited by 5 publications

References 0 publications

Looper and tension control in hot strip finishing mills based on different control approaches

Looper and tension control in hot strip finishing mills based on different control approaches

The Design and Implementation of an Automatic Tracking System of Solar Energy Based on the PID Control Algorithm

Design and Simulation of a Fuzzy Supervisory Control System Integrated in a Small Public Building

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