210 research outputs found

    A review and analysis of control techniques in HVAC systems

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    Heating Ventilating and Air Conditioning (HVAC) systems are the core energy-absorbing equipment in buildings. Building HVAC system with effective control technique can greatly reduce energy consumption. The high demand for HVAC system Placing in buildings, using an effective control technique to decrease the energy absorbing of the equipment while meeting the thermal comfort demands in buildings are the most important goals of control designers. The different control methods for HVAC systems. This paper defines control techniques used in HVAC systems, MATLAB/simulation design and implementation of controller’s technique with the transfer function for the HVAC system. Keywords-HVAC, PID controller, MPC Controller, Adaptive Controller, Fuzzy Controller

    Fault Diagnosis Of Sensor And Actuator Faults In Multi-Zone Hvac Systems

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    Globally, the buildings sector accounts for 30% of the energy consumption and more than 55% of the electricity demand. Specifically, the Heating, Ventilation, and Air Conditioning (HVAC) system is the most extensively operated component and it is responsible alone for 40% of the final building energy usage. HVAC systems are used to provide healthy and comfortable indoor conditions, and their main objective is to maintain the thermal comfort of occupants with minimum energy usage. HVAC systems include a considerable number of sensors, controlled actuators, and other components. They are at risk of malfunctioning or failure resulting in reduced efficiency, potential interference with the execution of supervision schemes, and equipment deterioration. Hence, Fault Diagnosis (FD) of HVAC systems is essential to improve their reliability, efficiency, and performance, and to provide preventive maintenance. In this thesis work, two neural network-based methods are proposed for sensor and actuator faults in a 3-zone HVAC system. For sensor faults, an online semi-supervised sensor data validation and fault diagnosis method using an Auto-Associative Neural Network (AANN) is developed. The method is based on the implementation of Nonlinear Principal Component Analysis (NPCA) using a Back-Propagation Neural Network (BPNN) and it demonstrates notable capability in sensor fault and inaccuracy correction, measurement noise reduction, missing sensor data replacement, and in both single and multiple sensor faults diagnosis. In addition, a novel on-line supervised multi-model approach for actuator fault diagnosis using Convolutional Neural Networks (CNNs) is developed for single actuator faults. It is based a data transformation in which the 1-dimensional data are configured into a 2-dimensional representation without the use of advanced signal processing techniques. The CNN-based actuator fault diagnosis approach demonstrates improved performance capability compared with the commonly used Machine Learning-based algorithms (i.e., Support Vector Machine and standard Neural Networks). The presented schemes are compared with other commonly used HVAC fault diagnosis methods for benchmarking and they are proven to be superior, effective, accurate, and reliable. The proposed approaches can be applied to large-scale buildings with additional zones

    A robust controlling methodology for a grouting process

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    The grouting technology is an effective and economic method in the grouting industry field. In this paper, a nonlinear model for the grouting dynamic process was established, and the controlling parameters were further modified through a robust method. Moreover, the grouting pressure system for the neural network was also modelled based on a sensitivity analysis algorithm, and in particular, the iterative learning algorithm and Lyapunov asymptotical theory. The results showed that such a robust controlling methodology was better than the normal manual operation method. The subsequent numerical simulations demonstrated that the tuning methodology could meet all the requirements for the grouting control with the maximum pressure variable in the range of 8.1%. The present study and the proposed method could be applied to various engineering projects and especially, to implement in the real control of damming grouting

    Improved gravitational search algorithm for proportional integral derivative controller tuning in process control system

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    Proportional-Integral-Derivative (PID) controller is one of the most used controllers in the industry due to the reliability and simplicity of its structure. However, despite its simple structure controller, the tuning process of PID controller for nonlinear, high-order and complex plant is difficult and faces lots of challenges. Conventional method such as Ziegler-Nichols are still being used for PID tuning process despite its lack of tuning accuracy. Nowadays researchers around the world shift their attention from conventional method to optimisation-based methods. For the last five years, optimisation techniques become one of the most popular methods used for tuning process of PID controller. Optimisation techniques such as Genetic Algorithm (GA), Particle Swarm Optimisation (PSO) as well as Gravitational Search Algorithm (GSA) are widely used for the PID controller application. Despite the effectiveness of GSA for PID controller tuning process compared to the GA and PSO technique, there is still a room for improvement of GSA performance for PID controller tuning process. This research represents the additional characters in GSA to enhance the PID controller parameter tuning performance which are Linear Weight Summation (LWS) and alpha parameter range tuning. Performance of optimisation-based PID controllers are measured based on the transient response performance specification (i.e. rise time, settling time, and percentage overshoot). By implementing these two approaches, results show that Improved Gravitational Search Algorithm (IGSA) based PID controller produced 20% to 30% faster rise and settling time and 25% to 35% smaller percentage overshoot compared to GA-PID and PSO-PID. For real implementation analysis, IGSA based PID controller also produced faster settling time and lower percentage overshoot than other optimisation-based PID controller. A good controller viewed as a controller that produced a stable dynamic system. Therefore, by producing a good transient response, IGSA based PID controller is able to provide a stable dynamic system performance compared to other controllers

    A Simulation and Experimental Study of Active Disturbance Rejection for Industrial Pressure Control

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    The quality of control loop is very important in hydraulic machineries, where pressure must be accurately regulated in the presence of various disturbances. Proportional-Integral-Derivative (PID) control has dominated the industry for a long time and it is by far the most popular general purpose controller for pressure control. The purpose of this study is to conduct a simulation and experimental study comparing PID with an emerging new technology, namely active disturbance rejection control (ADRC). For the purpose of this study, an experimental testbed similar to those used in industry settings is used; its mathematic model is derived and used in the simulation study. A linearized model is also derived for the purpose of PID tuning, where various methods such as the standard Ziegler-Nichols method, the pole-placement and the trial-and-error method are tested. As for the tuning of ADRC, a method is proposed to determine the critical gain parameter, which is the only plant parameter needed. All the simulation and experimental tests are designed based on the practical scenarios, so that the controller tuning, the tracking performance, the disturbance rejection capability and the energy consumption can be studied meaningfully for future industrial applications. Initial results indicate that, with the same bandwidth, ADRC can be used in a wider range of set point tracking than PID. Furthermore, ADRC is easy to tune and has clear advantages over PID in terms of disturbance rejection and energy saving in all simulation and experiment results. In summary, results of this study indicates that ADRC, as a general purpose controller, is a viable solution for pressure control applications, and an alternative to PID

    A feasibility study for the development of sustainable theoretical framework for smart air-conditioning

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    Air-conditioning as a technical solution to protect inhabitants from excessive heat exposure creates the challenge of expanding global warming and climate change. While air-conditioning has mostly been applied as an improvement to living conditions, health and environmental problems associated with its use frequently occur. Therefore, this study challenges and extends existing knowledge on sustainability-related to smart air-conditioning systems, where social, environmental and economic dynamics were considered. For instance, when exploring renewable-based options, advanced smart control techniques and profitability measures of air-conditioning reinforce the three pillars of sustainability. In addition to eradicating indoor health effects, this also helps to combat climate change through the system’s sustainability. As an exercise in conceptual modelling, the principal component analysis accounts for sustainable planning and its integration into the theoretical framework. The newly proposed photovoltaic solar air-conditioning was optimised using Polysun to demonstrate the significant application of solar energy in air-conditioning systems, thereby reducing the level of energy consumption and carbon emissions. The newly proposed fuzzy proportional-integral-derivative controller and backpropagation neural network were optimised using Matlab to control the indoor temperature and CO2 level appropriately. The controller of the indoor environment was designed, and the proportional-integral-derivative control was utilised as a result of its suitability. The smart controllers were designed to regulate the parameters automatically to ensure an optimised control output. The performance of photovoltaic solar air-conditioning in different temperate climates of Rome, Toulouse and London districts achieved a higher coefficient of performance of 3.37, 3.69 and 3.97, respectively. The system saved significant amount of energy and carbon emissions. The indoor temperature and indoor CO2 possess an appropriate time constant and settling time, respectively. The profitability assessment of the system revealed its adequate efficiency with an overall payback period of 5.5 years

    Development of robust building energy demand-side control strategy under uncertainty

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    The potential of carbon emission regulations applied to an individual building will encourage building owners to purchase utility-provided green power or to employ onsite renewable energy generation. As both cases are based on intermittent renewable energy sources, demand side control is a fundamental precondition for maximizing the effectiveness of using renewable energy sources. Such control leads to a reduction in peak demand and/or in energy demand variability, therefore, such reduction in the demand profile eventually enhances the efficiency of an erratic supply of renewable energy. The combined operation of active thermal energy storage and passive building thermal mass has shown substantial improvement in demand-side control performance when compared to current state-of-the-art demand-side control measures. Specifically, "model-based" optimal control for this operation has the potential to significantly increase performance and bring economic advantages. However, due to the uncertainty in certain operating conditions in the field its control effectiveness could be diminished and/or seriously damaged, which results in poor performance. This dissertation pursues improvements of current demand-side controls under uncertainty by proposing a robust supervisory demand-side control strategy that is designed to be immune from uncertainty and perform consistently under uncertain conditions. Uniqueness and superiority of the proposed robust demand-side controls are found as below: a. It is developed based on fundamental studies about uncertainty and a systematic approach to uncertainty analysis. b. It reduces variability of performance under varied conditions, and thus avoids the worst case scenario. c. It is reactive in cases of critical "discrepancies" observed caused by the unpredictable uncertainty that typically scenario uncertainty imposes, and thus it increases control efficiency. This is obtainable by means of i) multi-source composition of weather forecasts including both historical archive and online sources and ii) adaptive Multiple model-based controls (MMC) to mitigate detrimental impacts of varying scenario uncertainties. The proposed robust demand-side control strategy verifies its outstanding demand-side control performance in varied and non-indigenous conditions compared to the existing control strategies including deterministic optimal controls. This result reemphasizes importance of the demand-side control for a building in the global carbon economy. It also demonstrates a capability of risk management of the proposed robust demand-side controls in highly uncertain situations, which eventually attains the maximum benefit in both theoretical and practical perspectives.Ph.D.Committee Chair: Augenbroe, Gofried; Committee Member: Brown, Jason; Committee Member: Jeter, Sheldon; Committee Member: Paredis,Christiaan; Committee Member: Sastry, Chellur

    Who wrote this scientific text?

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    The IEEE bibliographic database contains a number of proven duplications with indication of the original paper(s) copied. This corpus is used to test a method for the detection of hidden intertextuality (commonly named "plagiarism"). The intertextual distance, combined with the sliding window and with various classification techniques, identifies these duplications with a very low risk of error. These experiments also show that several factors blur the identity of the scientific author, including variable group authorship and the high levels of intertextuality accepted, and sometimes desired, in scientific papers on the same topic
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