Adaptive Robust Control Scheme Applied to a Single-Zone HVAC System

Chen, Y.H.; Lee, K.M.; Wepfer, William J.

doi:10.23919/acc.1990.4790905

Cited by 9 publications

(6 citation statements)

References 4 publications

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“…Chen et al conclude that simulation results depict a satisfactory transient performance, in the sense of maintaining small overshoot, under significant deviation of the initial state from the comfort region. A drawback reported in Chen et al (1990) is that the steady state performance has certain oscillations.…”

Section: Introductionmentioning

confidence: 99%

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Real-time tuning of PI controllers in HVAC systems

Zaheeruddin

2004

Int. J. Energy Res.

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SUMMARYThe problem of tuning single-loop controllers in heating, ventilating and air conditioning (HVAC) systems is explored. The HVAC process was described by a first-order-plus-dead-time (FOPDT) model. By using recursive least squares method, the model parameters were updated while the system remained in closedloop. The H 1 loop-shaping tuning rules published in the literature were transformed to discrete-time tuning rules and were implemented in an adaptive PI control strategy. The methodology was applied to a discharge air temperature (DAT) control system. The output responses of adaptive PI controller were compared with a LQR optimal adaptive controller. Simulation results show that the adaptively tuned PI controller is able to track setpoint changes very well in the presence of changes in plant parameters, disturbances and external noise acting on the system.

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Section: Introductionmentioning

confidence: 99%

“…The author noted that unmodelled load disturbances, drifting parameters and actuator nonlinearity are limitations of self-tuning controllers. Chen et al (1990) have presented an adaptive robust control scheme applied to a single-zone HVAC system. It is a nonlinear system, and the uncertainty is assumed bounded but the bound is unknown.…”

Section: Introductionmentioning

confidence: 99%

Real-time tuning of PI controllers in HVAC systems

Zaheeruddin

2004

Int. J. Energy Res.

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“…Using equations (2) and (4), the center line trajectory under the forces of buoyance and gravity was derived in [3], and can be writ,ten as =,…”

Section: A T ( ? ) = a T G Z P ( -~+~)mentioning

confidence: 99%

“…It has been thoroughly studied in [4] that under the conditions of constant bodily heat production and clothing insulation, human thermal comfort is dependent on several environmental variables such as air temperature, vapor pressure, air velocity, and mean radiant temperature. T o establish a thermally comfortable environment, these variables must be properly regulated within some value range [2] or in a certain combination manner [ll], [5].…”

Section: Introductionmentioning

confidence: 99%

A distributed-parameter-model approach to optimal comfort control in air conditioning systems

Liu

Proceedings of 1994 American Control Conference - ACC '94

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This paper discusses the problem of optimizing the thermal comfort level in an air-conditioned room by treating the room as a distributed parameter system rather than a single-zone system with homogeneous thermal properties. A distributed room model is developed to explicitly describe the spatial distribution of room air temperature and velocity. This model is paramet,erized by the variable control setting of an air Conditioner, e.g. temperature and velocity at the air flow outlet as well as the outlet diffuser angle. Given a certain control setting, t,he thermal comfort level can be expressed as an explicit function of spatial coordinates in a room. T h e criterion for selecting t h r control setting of an air conditioner is defined as to maximize the sum of squares of comfort index values a t several discrete spatial points while keeping the power consumption rate minimal. This paper presents the derivations of the distributed parametric model of the room and a recursive numerical algorithm for solving the optimization problem. Some simulation results are provided.

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“…It has been proposed as a means to account for and compensate for both the uncertainty associated with the model used in controller design and the nonlinear nature of HVAC systems [4]. SISO robust controllers have been implemented and their performance verified in simulation [13] and on an experimental HVAC system [8].…”

Section: Overview Of Hvac Controlmentioning

confidence: 99%

MIMO robust control for heating, ventilating and air conditioning (HVAC) systems

Anderson

Young

Hittle

et al.

Proceedings of the 41st IEEE Conference on Decision and Control, 2002.

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Abstract-Potential improvements in heating, ventilating, and air conditioning (HVAC) system performance are investigated through the application of multiple-input, multiple-output (MIMO) robust controllers. This approach differs dramatically from today's prevalent method of building HVAC controllers using multiple single-input, single-output (SISO) control loops.A simulation model of an experimental HVAC system is used in the design and simulation testing of controllers. While simulation can be insightful, the only way to truly verify the performance provided by different HVAC controller designs is by actually using them to control an HVAC system. Thus, an experimental system for testing advanced HVAC controllers is built. The construction and modeling of this system is the focus of a separate article [2].While this system is only a portion of an overall HVAC system, it is representative of a typical hot water-to-air heating system. The performance of controllers in regulating the discharge air temperature and flow rate is verified using the experimental system.While simple optimal and SISO robust HVAC controllers have been designed and their performance experimentally verified, this project does so using MIMO robust controllers. The design and testing of these controllers provides valuable insight into potential improvements in performance, as well as constraints, associated with applying this control methodology to HVAC systems. Test results demonstrated that performance gains (reductions in discharge air temperature settle time) in excess of 300% may be achieved. Furthermore, it may be possible for such performance gains to be achieved without significant impact to current HVAC system architecture (interconnection).

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Adaptive Robust Control Scheme Applied to a Single-Zone HVAC System

Cited by 9 publications

References 4 publications

Real-time tuning of PI controllers in HVAC systems

Real-time tuning of PI controllers in HVAC systems

A distributed-parameter-model approach to optimal comfort control in air conditioning systems

MIMO robust control for heating, ventilating and air conditioning (HVAC) systems

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