Dissertations / Theses: 'Proportional-Integral- Derivative controllers'

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Chin, Hui Hui. "All digital design and implementation of proportional-integral-derivative (PID) controllers." Lexington, Ky. : [University of Kentucky Libraries], 2006. http://lib.uky.edu/ETD/ukyelen2006t00394/Thesis.pdf.

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Thesis (M.S.)--University of Kentucky, 2006. Title from document title page (viewed on March 28, 2006). Document formatted into pages; contains viii, 88 p. : ill. Includes abstract and vita. Includes bibliographical references (p. 85-87).

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Chopra, Shubham. "Evolved Design of a Nonlinear Proportional Integral Derivative (NPID) Controller." PDXScholar, 2012. https://pdxscholar.library.pdx.edu/open_access_etds/512.

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This research presents a solution to the problem of tuning a PID controller for a nonlinear system. Many systems in industrial applications use a PID controller to control a plant or the process. Conventional PID controllers work in linear systems but are less effective when the plant or the process is nonlinear because PID controllers cannot adapt the gain parameters as needed. In this research we design a Nonlinear PID (NPID) controller using a fuzzy logic system based on the Mamdani type Fuzzy Inference System to control three different DC motor systems. This fuzzy system is responsible for adapting the gain parameters of a conventional PID controller. This fuzzy system's rule base was heuristically evolved using an Evolutionary Algorithm (Differential Evolution). Our results show that a NPID controller can restore a moderately or a heavily under-damped DC motor system under consideration to a desired behavior (slightly under-damped).

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Ramamurthi, Indu. "A versatile simulation tool for virtual implementation of proportional integral and derivative (PID) controllers." Thesis, Texas A&M University, 2003. http://hdl.handle.net/1969.1/5961.

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This thesis proposes an interactive software tool that can be used to compute complete sets of Proportional Integral Derivative (PID) Controllers from knowledge of the plant transfer function/frequency response data. This is based on research results and algorithms developed by Bhattacharyya and others. Until these research results were published, it was not known if a nominal system could be stabilized using PID Controllers, and current PID Controller designs are carried out using ad hoc tuning rules. By using simulations, engineers can best plan for and observe the stabilizing effect each of the variables has on system performance in a realistic environment. The software application developed calculates and optimizes complete stabilizing sets of PID Controllers for a rational Linear Time Invariant (LTI) system, and has been developed for analytical models of plants with and without time delay. Further, these PID Controller sets are optimized to project subsets simultaneously satisfying multiple performance index specifications. Sets of PID Controllers that stabilize a system are also calculated automatically from knowledge of the frequency response of the plant. It allows the user ease of design and the ability to customize the final solution while permitting full control over source parameters. This thesis includes an introduction to the algorithms that have been developed for plant stabilization, a complete description of the graphical user interface, the simulation of the algorithms performed using LabVIEW, and a summary of future work.

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Narasimhan, Bharat. "An automated virtual tool to compute the entire set of proportional integral derivative controllers for a continuous linear time invariant system." Texas A&M University, 2007. http://hdl.handle.net/1969.1/85831.

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This thesis presents the very practical and novel approach of using the Graphical User Interface (GUI) to compute the entire set of Proportional Integral Derivative (PID) controllers given the transfer function or the frequency response of the system under consideration. Though there is a wide spread usage of PID controllers in the industry, until recently no formal algorithm existed on determining a set of PID values that will stabilize the given system. The industry still relies on algorithms like the Ziegler- Nicholas or ad-hoc approaches in determining the value of PID controllers. Also when it comes to model free approaches, the use of Fuzzy logic and Neural network do not guarantee stability of the system. For a continuous Linear Time Invariant system Bhattacharyya and others have developed an algorithm that determines the entire set of PID controllers given the transfer function or just the frequency response of the system. The GUI has been developed based on this theory. The GUI also evaluates the user input performance specifications and generates a subset of stable controllers given the performance criteria for the system. This thesis presents an approach of automating the computation of entire set of stabilizing Proportional Integral Derivative (PID) controllers given the system transfer function or the frequency response data of the system. The Graphical User Interface (GUI) developed bridges the gap between the developed theory and the industry.

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André, Simon. "Design and Optimization of Controllers for an Electro-Hydraulic System." Thesis, Linköpings universitet, Reglerteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-107620.

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Electro-Hydraulic (EH) systems are commonly used in the industry for applications that require high power-weight ratios and large driving forces. The EH system studied in this master thesis have recently been upgraded with new hardware components and as a part of this upgrade a new controller was requested. The system consists of a controller that computes a control signal for an electric motor. The motor drives a gear pump that generates a flow of hydraulic fluid. The flow is then directed to a cylinder. The movements of a piston in the cylinder is affected by the flow and the piston position can be measured. The measured piston position is then fed back to the controller and the control loop is complete. The system was previously controlled using a Proportional-Integral-Derivative (PID) controller and the purpose of this thesis is to compare the old controller with alternative control strategies suitable for this application. The evaluation of the controllers is based on both software and hardware simulations and results in a recommendation for final implementation of the best suited controller. The control strategies chosen for investigation are: a retuned PID controller, a PID controller with feed forward from reference, a PID based cascade controller, a Linear Quadratic (LQ) controller, and a Model Predictive Controller (MPC). To synthesize the controllers an approximate model of the system is formed and implemented in the software environment Matlab Simulink. The model is tuned to fit recorded data and provides a decent estimation of the actual system. The proposed control strategies are then simulated and evaluated in Simulink with the model posing as the real system. These simulations resulted in the elimination of the cascade controller as a possible candidate since it proved unstable for large steps in the reference signal. The remaining four controllers were all selected for simulation on the real hardware system. Unfortunately the MPC was never successfully implemented on the hardware due to some unknown compatibility error and hence eliminated as a possible candidate. The three remaining control strategies, PID, PID with feed forward from reference and the LQ controller, were all successfully implemented and simulated on hardware. The results from the hardware simulations compared to simulations made with the old controller, as well as the results from the software simulations, were then evaluated. Depending on the purpose one of two control strategies is recommended for this application. The LQ controller achieved the best overall performance and is presented as the control strategy best suited for this application.

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Enbiya, Saleh A. "Automatic Control Strategies of Mean Arterial Pressure and Cardiac Output. MIMO controllers, PID, internal model control, adaptive model reference, and neural nets are developed to regulate mean arterial pressure and cardiac output using the drugs sodium Nitroprusside and dopamine." Thesis, University of Bradford, 2013. http://hdl.handle.net/10454/13421.

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High blood pressure, also called hypertension is one of the most common worldwide diseases afflicting humans and is a major risk factor for stroke, myocardial infarction, vascular disease, and chronic kidney disease. If blood pressure is controlled and oscillations in the hemodynamic variables are reduced, patients experience fewer complications after surgery. In clinical practice, this is usually achieved using manual drug delivery. Given that different patients have different sensitivity and reaction time to drugs, determining manually the right drug infusion rates may be difficult. This is a problem where automatic drug delivery can provide a solution, especially if it is designed to adapt to variations in the patient’s conditions. This research work presents an investigation into the development of abnormal blood pressure (hypertension) controllers for postoperative patients. Control of the drugs infusion rates is used to simultaneously regulate the hemodynamic variables such as the Mean Arterial Pressure (MAP) and the Cardiac Output (CO) at the desired level. The implementation of optimal control system is very essential to improve the quality of patient care and also to reduce the workload of healthcare staff and costs. Many researchers have conducted studies earlier on modelling and/or control of abnormal blood pressure for postoperative patients. However, there are still many concerns about smooth transition of blood pressure without any side effect. The blood pressure is classified in two categories: high blood pressure (Hypertension) and low blood pressure (Hypotension). The hypertension often occurred after cardiac surgery, and the hypotension occurred during cardiac surgery. To achieve the optimal control solution for these abnormal blood pressures, many methods are proposed, one of the common methods is infusing the drug related to blood pressure to maintain it at the desired level. There are several kinds of vasodilating drugs such as Sodium Nitroprusside (SNP), Dopamine (DPM), Nitro-glycerine (NTG), and so on, which can be used to treat postoperative patients, also used for hypertensive emergencies to keep the blood pressure at safety level. A comparative performance of two types of algorithms has been presented in chapter four. These include the Internal Model Control (IMC), and Proportional-Integral-Derivative (PID) controller. The resulting controllers are implemented, tested and verified for three sensitivity patient response. SNP is used for all three patients’ situation in order to reduce the pressure smoothly and maintain it at the desire level. A Genetic Algorithms (GAs) optimization technique has been implemented to optimise the controllers’ parameters. A set of experiments are presented to demonstrate the merits and capabilities of the control algorithms. The simulation results in chapter four have demonstrated that the performance criteria are satisfied with the IMC, and PID controllers. On the other hand, the settling time for the PID control of all three patients’ response is shorter than the settling time with IMC controller. Using multiple interacting drugs to control both the MAP and CO of patients with different sensitivity to drugs is a challenging task. A Multivariable Model Reference Adaptive Control (MMRAC) algorithm is developed using a two-input, two-output patient model. Because of the difference in patient’s sensitivity to the drug, and in order to cover the wide ranges of patients, Model Reference Adaptive Control (MRAC) has been implemented to obtain the optimal infusion rates of DPM and SNP. This is developed in chapters five and six. Computer simulations were carried out to investigate the performance of this controller. The results show that the proposed adaptive scheme is robust with respect to disturbances and variations in model parameters, the simulation results have demonstrated that this algorithm cannot cover the wide range of patient’s sensitivity to drugs, due to that shortcoming, a PID controller using a Neural Network that tunes the controller parameters was designed and implemented. The parameters of the PID controller were optimised offline using Matlab genetic algorithm. The proposed Neuro-PID controller has been tested and validated to demonstrate its merits and capabilities compared to the existing approaches to cover wide range of patients. Libyan Ministry of Higher Education scholarship

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Enbiya, Saleh Abdalla. "Automatic control strategies of mean arterial pressure and cardiac output : MIMO controllers, PID, internal model control, adaptive model reference, and neural nets are developed to regulate mean arterial pressure and cardiac output using the drugs Sodium Nitroprusside and Dopamine." Thesis, University of Bradford, 2013. http://hdl.handle.net/10454/13421.

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High blood pressure, also called hypertension is one of the most common worldwide diseases afflicting humans and is a major risk factor for stroke, myocardial infarction, vascular disease, and chronic kidney disease. If blood pressure is controlled and oscillations in the hemodynamic variables are reduced, patients experience fewer complications after surgery. In clinical practice, this is usually achieved using manual drug delivery. Given that different patients have different sensitivity and reaction time to drugs, determining manually the right drug infusion rates may be difficult. This is a problem where automatic drug delivery can provide a solution, especially if it is designed to adapt to variations in the patient’s conditions. This research work presents an investigation into the development of abnormal blood pressure (hypertension) controllers for postoperative patients. Control of the drugs infusion rates is used to simultaneously regulate the hemodynamic variables such as the Mean Arterial Pressure (MAP) and the Cardiac Output (CO) at the desired level. The implementation of optimal control system is very essential to improve the quality of patient care and also to reduce the workload of healthcare staff and costs. Many researchers have conducted studies earlier on modelling and/or control of abnormal blood pressure for postoperative patients. However, there are still many concerns about smooth transition of blood pressure without any side effect. The blood pressure is classified in two categories: high blood pressure (Hypertension) and low blood pressure (Hypotension). The hypertension often occurred after cardiac surgery, and the hypotension occurred during cardiac surgery. To achieve the optimal control solution for these abnormal blood pressures, many methods are proposed, one of the common methods is infusing the drug related to blood pressure to maintain it at the desired level. There are several kinds of vasodilating drugs such as Sodium Nitroprusside (SNP), Dopamine (DPM), Nitro-glycerine (NTG), and so on, which can be used to treat postoperative patients, also used for hypertensive emergencies to keep the blood pressure at safety level. A comparative performance of two types of algorithms has been presented in chapter four. These include the Internal Model Control (IMC), and Proportional-Integral-Derivative (PID) controller. The resulting controllers are implemented, tested and verified for three sensitivity patient response. SNP is used for all three patients’ situation in order to reduce the pressure smoothly and maintain it at the desire level. A Genetic Algorithms (GAs) optimization technique has been implemented to optimise the controllers’ parameters. A set of experiments are presented to demonstrate the merits and capabilities of the control algorithms. The simulation results in chapter four have demonstrated that the performance criteria are satisfied with the IMC, and PID controllers. On the other hand, the settling time for the PID control of all three patients’ response is shorter than the settling time with IMC controller. Using multiple interacting drugs to control both the MAP and CO of patients with different sensitivity to drugs is a challenging task. A Multivariable Model Reference Adaptive Control (MMRAC) algorithm is developed using a two-input, two-output patient model. Because of the difference in patient’s sensitivity to the drug, and in order to cover the wide ranges of patients, Model Reference Adaptive Control (MRAC) has been implemented to obtain the optimal infusion rates of DPM and SNP. This is developed in chapters five and six. Computer simulations were carried out to investigate the performance of this controller. The results show that the proposed adaptive scheme is robust with respect to disturbances and variations in model parameters, the simulation results have demonstrated that this algorithm cannot cover the wide range of patient’s sensitivity to drugs, due to that shortcoming, a PID controller using a Neural Network that tunes the controller parameters was designed and implemented. The parameters of the PID controller were optimised offline using Matlab genetic algorithm. The proposed Neuro-PID controller has been tested and validated to demonstrate its merits and capabilities compared to the existing approaches to cover wide range of patients.

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Sola, Yoann. "Contributions to the development of deep reinforcement learning-based controllers for AUV." Thesis, Brest, École nationale supérieure de techniques avancées Bretagne, 2021. http://www.theses.fr/2021ENTA0015.

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L’environnement marin est un cadre très hostile pour la robotique. Il est fortement non-structuré, très incertain et inclut beaucoup de perturbations externes qui ne peuvent pas être facilement prédites ou modélisées. Dans ce travail, nous allons essayer de contrôler un véhicule sous-marin autonome (AUV) afin d’effectuer une tâche de suivi de points de cheminement, en utilisant un contrôleur basé sur de l’apprentissage automatique. L’apprentissage automatique a permis de faire des progrès impressionnants dans de nombreux domaines différents ces dernières années, et le sous-domaine de l’apprentissage profond par renforcement a réussi à concevoir plusieurs algorithmes très adaptés au contrôle continu de systèmes dynamiques. Nous avons choisi d’implémenter l’algorithme du Soft Actor-Critic (SAC), un algorithme d’apprentissage profond par renforcement régularisé en entropie permettant de simultanément remplir une tâche d’apprentissage et d’encourager l’exploration de l’environnement. Nous avons comparé un contrôleur basé sur le SAC avec un contrôleur Proportionnel-Intégral-Dérivé (PID) sur une tâche de suivi de points de cheminement et en utilisant des métriques de performance spécifiques. Tous ces tests ont été effectués en simulation grâce à l’utilisation de l’UUV Simulator. Nous avons décidé d’appliquer ces deux contrôleurs au RexROV 2, un véhicule sous-marin téléguidé (ROV) de forme cubique et à six degrés de liberté converti en AUV. Grâce à ces tests, nous avons réussi à proposer plusieurs contributions intéressantes telles que permettre au SAC d’accomplir un contrôle de l’AUV de bout en bout, surpasser le contrôleur PID en terme d’économie d’énergie, et réduire la quantité d’informations dont l’algorithme du SAC a besoin. De plus nous proposons une méthodologie pour l’entraînement d’algorithmes d’apprentissage profond par renforcement sur des tâches de contrôle, ainsi qu’une discussion sur l’absence d’algorithmes de guidage pour notre contrôleur d’AUV de bout en bout The marine environment is a very hostile setting for robotics. It is strongly unstructured, very uncertain and includes a lot of external disturbances which cannot be easily predicted or modelled. In this work, we will try to control an autonomous underwater vehicle (AUV) in order to perform a waypoint tracking task, using a machine learning-based controller. Machine learning allowed to make impressive progress in a lot of different domain in the recent years, and the subfield of deep reinforcement learning managed to design several algorithms very suitable for the continuous control of dynamical systems. We chose to implement the Soft Actor-Critic (SAC) algorithm, an entropy-regularized deep reinforcement learning algorithm allowing to fulfill a learning task and to encourage the exploration of the environment simultaneously. We compared a SAC-based controller with a Proportional-Integral-Derivative (PID) controller on a waypoint tracking task and using specific performance metrics. All the tests were performed in simulation thanks to the use of the UUV Simulator. We decided to apply these two controllers to the RexROV 2, a six degrees of freedom cube-shaped remotely operated underwater vehicle (ROV) converted in an AUV. Thanks to these tests, we managed to propose several interesting contributions such as making the SAC achieve an end-to-end control of the AUV, outperforming the PID controller in terms of energy saving, and reducing the amount of information needed by the SAC algorithm. Moreover we propose a methodology for the training of deep reinforcement learning algorithms on control tasks, as well as a discussion about the absence of guidance algorithms for our end-to-end AUV controller

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McCluskey, Emmet Gerard. "Rule-based automatic PID controller tuning." Thesis, Queen's University Belfast, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335433.

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Chin, Hui Hui. "ALL DIGITAL DESIGN AND IMPLEMENTAION OF PROPORTIONAL-INTEGRAL-DERIVATIVE (PID) CONTROLLER." UKnowledge, 2006. http://uknowledge.uky.edu/gradschool_theses/272.

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Due to the prevalence of pulse encoders for system state information, an all-digital proportional-integral-derivative (ADPID) is proposed as an alternative to traditional analog and digital PID controllers. The basic concept of an ADPID stems from the use of pulse-width-modulation (PWM) control signals for continuous-time dynamical systems, in that the controllers proportional, integral and derivative actions are converted into pulses by means of standard up-down digital counters and other digital logic devices. An ADPID eliminates the need for analog-digital and digital-analog conversion, which can be costly and may introduce error and delay into the system. In the proposed ADPID, the unaltered output from a pulse encoder attached to the systems output can be interpreted directly. After defining a pulse train to represent the desired output of the encoder, an error signal is formed then processed by the ADPID. The resulting ADPID output or control signal is in PWM format, and can be fed directly into the target system without digital-to-analog conversion. In addition to proposing an architecture for the ADPID, rules are presented to enable control engineers to design ADPIDs for a variety of applications.

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Gogoi, Manoj. "Proportional-Integral-Derivative (PID) controller design for robust stability of arbitrary order plants with time-delay and additive uncertainty." Thesis, Wichita State University, 2010. http://hdl.handle.net/10057/3478.

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In the process control industry, majority of control loops are based on Proportional-Integral-Derivative (PID) controllers. The basic structure of the PID controllers makes it easy to regulate the process output. Design methods leading to an optimal and effective operation of the PID controllers are economically vital for process industries. Robust control has been a recent addition to the field of control engineering that primarily deals with obtaining system robustness in presences of uncertainties. In this thesis, a graphical design method for obtaining the entire range of PID controller gains that robustly stabilize a system in the presence of time delays and additive uncertainty is introduced. This design method primarily depends on the frequency response of the system, which can serve to reduce the complexities involved in plant modeling. The fact that time-delays and parametric uncertainties are almost always present in real time processes makes our controller design method very vital for process control. We have applied our design method to a DC motor model with a communication delay and a single area non-reheat steam generation unit. The results were satisfactory and robust stability was achieved for the perturbed plants. Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science.

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Holgersson, Anton, and Johan Gustafsson. "Trajectory Tracking for Automated Guided Vehicle." Thesis, Linköpings universitet, Reglerteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176423.

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The purpose of this thesis is to investigate different control strategies on a differential drive vehicle. The vehicle should be able to drive in turns at high speed and slowly when it should park next to a charger. In both these cases, good precision in both orientation and distance to the path is important. A PID and an LQ controller have been implemented for this purpose. The two controllers were first implemented in a simulation environment. After implementing the controllers on the system itself, tests to evaluate the controllers were made to imitate real-life situations. This includes tests regarding driving with different speeds in different turns, tests with load distributions, and tests with stopping accuracy. The existing controller on the system was also tested and compared to the new controllers. After evaluating the controllers, it was stated that the existing controller was the most robust. It was not affected much by the load distribution compared to the new controllers. However, the LQ controller was slightly better in most cases, even though it was highly affected by the load distribution. The PID controller performed best regarding stopping accuracy but was the least robust controller by the three. Since the existing controller has a similar performance as the LQ controller but is more robust, the existing controller was chosen as the best one.

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Jowkar, Saeid. "The Application of Programmable Logic Controller (PLC) to Control Temperature in Cold-room Based on TIA PORTAL Software." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

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A temperature sensor is a device to measure the temperature through an electrical signal. It requires a thermocouple or resistance temperature detectors (RTD) and will interface with a programmable logic controller (PLC). A temperature transmitter is a device that connects to a temperature sensor to transmit the signal elsewhere for monitoring and control purposes that its role is to convert the temperature sensor's signal to a 0-10V DC voltage in the PLC. The PLC voltage signal setting is compared to the temperature deviation after the Proportional Integral Derivative (PID) operation. Then, the system will issue a temperature control signal to achieve the cooling system voltage control so that it implements continuous monitoring and temperature control. The temperature control system in the industrial field has a certain value that it is an important factor for controlling temperature. A certain value of the temperature of the desired environment has to be set with a minimum and maximum set-point temperature which is suitable for that environment and the set-point value can be variable and can be changed with Human Machine Interface (HMI) easily.

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Jebelli, Ali. "Development of Sensors and Microcontrollers for Underwater Robots." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31283.

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Nowadays, small autonomous underwater robots are strongly preferred for remote exploration of unknown and unstructured environments. Such robots allow the exploration and monitoring of underwater environments where a long term underwater presence is required to cover a large area. Furthermore, reducing the robot size, embedding electrical board inside and reducing cost are some of the challenges designers of autonomous underwater robots are facing. As a key device for reliable operation-decision process of autonomous underwater robots, a relatively fast and cost effective controller based on Fuzzy logic and proportional-integral-derivative method is proposed in this thesis. It efficiently models nonlinear system behaviors largely present in robot operation and for which mathematical models are difficult to obtain. To evaluate its response, the fault finding test approach was applied and the response of each task of the robot depicted under different operating conditions. The robot performance while combining all control programs and including sensors was also investigated while the number of program codes and inputs were increased.

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Nkwanyana, Thamsanqa Bongani. "Multi-input multi-output proportional integral derivative controller tuning based on improved particle swarm optimization." Diss., 2021. http://hdl.handle.net/10500/27692.

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The PID controller is regarded as a dependable and reliable controller for process industry systems. Many researchers have devoted time and attention to PID controller tuning and they all agree that PID controllers are very important for control systems. A PID equation is very sensitive; its parameters must always be varied following the specific application to increase performance, such as by increasing the system’s responsiveness. PID controllers still have many problems despite their importance for control systems in industries. The problem of big overshoot on the conventional gain tuning is one of the serious problems. Researchers use the PSO algorithm to try and overcome those problems. The tuning of the MIMO PID controller based on the PSO algorithm shows many disadvantages such as high-quality control with a short settle time, steady-state error, and periodical step response. The traditional PSO algorithm is very sensitive and it sometimes affects the quality of good PID controller tuning. This research has proposed a new equation for improving the PSO algorithm. The proposed algorithm is the combination of linearly decreasing inertia weight and chaotic inertia weight, after which a control factor was introduced as an exponential factor. This was very useful for simulations as it is adjustable. The Matlab simulation results of the experiments show that the simulations as it is adjustable. The Matlab simulation results of the experiments show that the new proposed equation converges faster and it gives the best fitness compared to linear inertia weight and oscillating inertia weight and other old equations. The MIMO PID controller system that consists of four plants was tuned based on the new proposed equation for the PSO algorithm (LCPSO). The optimized results show the best rise time, settling time, time delays, and steady-state compared to the systems that are tuned using the old equations. The exploration was directed at considering the impact of using the PSO calculation as an instrument for MIMO PID tuning. The results obtained in the examination reveal that the PSO tuning output improved reactions and can be applied to various system models in the measure control industry. The results for the MIMO PID controller tuned using PSO were assessed using integral square error (ISE), integral absolute error (IAE), and the integral of time expanded by absolute error (ITAE). The five well-known benchmark functions were also used to endorse the feasibility of the improved PSO and excellent results in terms of convergence and best fitness were attained. Electrical and Mining Engineering M. Tech. (Electrical Engineering)

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(13830958), Saravana Kumar Krishnamoorthy. "A New Machine-learning Algorithm for Hybrid Electric Vehicle Applications with Hardware Implementation." Thesis, 2025. https://figshare.com/articles/thesis/A_New_Machine-learning_Algorithm_for_Hybrid_Electric_Vehicle_Applications_with_Hardware_Implementation/29207867.

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As the global shift toward sustainable transportation intensifies, Hybrid Electric Vehicles (HEVs) have emerged as a promising alternative to traditional internal combustion engine vehicles. Achieving higher energy efficiency, reducing emissions, and improving overall vehicle performance in HEVs largely depends on advanced control algorithms that can effectively manage powertrain systems and optimize energy distribution. This research introduces a novel machine-learning-based control algorithm for HEVs, integrating Proportional-Integral-Derivative (PID), Fuzzy Logic, and Artificial Neural Network (ANN) controllers. By combining the strengths of each controller, the proposed hybrid approach addresses the limitations of conventional control methods and improves adaptability to complex driving conditions. This thesis presents key contributions to the field of HEV control systems and predictive maintenance for Brushless Direct Current (BLDC) motors. A hybrid control algorithm is developed and validated, enhancing energy management and producing improved fuel efficiency and reduced emissions. The algorithm is trained using real-world driving data and tested through hardware-in-the-loop simulations under various driving conditions, including urban, highway, and mixed environments. The research also introduces an Enhanced Whale Optimization Algorithm-Tuned PID (EWOA-TPID) Controller for BLDC motor speed regulation, addressing key challenges in improving Rise Time, Settling Time, Maximum Overshoot, and overall efficiency. A comparative analysis with conventional control techniques demonstrates the superior performance of the proposed hybrid algorithm in optimizing HEV energy management and the EWOA-TPID Controller's effectiveness in improving BLDC motor speed control. The study addresses key gaps in the research knowledge, such as the need for hybrid control algorithms that can manage powertrain responses in real-time under diverse driving conditions; and challenges in tuning PID parameters to improve motor performance. Data collected from real-world HEV driving scenarios is used to validate the algorithm’s applicability, while performance metrics, including Rise Time, Settling Time, Maximum Overshoot, and efficiency, are employed to evaluate the proposed system's effectiveness in BLDC motor applications.

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Kumar, M. Prasanna. "Studies On Application Of Control Systems For Urban Water Networks." Thesis, 2008. https://etd.iisc.ac.in/handle/2005/874.

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Management and supply of water in an urban water distribution system is a complex process, which include various complexities like pressure variations across the network depending on topography, demand variations depending on customers’ requirement and unaccounted water etc. Applying automatic control methods to water distribution systems is a way to improve the management of water distribution. There have been some attempts in recent years to develop optimal control algorithms to assist in the operation of complex water distribution systems. The difficulties involved by these hydraulic systems such as non-linearity, and diurnal demand patterns make the choice of a suitable automatic control method a challenge. For this purpose, this study intends to investigate the applicability of different controllers which would be able to meet the targets as quickly as possible and without creating undue transients. As a first step towards application of different controllers, PD and PID linear controllers have been designed for pump control and valve control in water distribution systems. Then a Dynamic Inversion based nonlinear controller has been designed by considering the non-linearities in the system. Here, different cases considering the effects of initial conditions used, linearization methods used, time step used for integration and selection of gains etc., have been studied before arriving at best controller. These controllers have been designed for both the flow control problems and level control problems. It is found that Dynamic Inversion-based nonlinear controller outperforms other controllers. It is well known that the performance of controllers is much dependent on the tuning of the gains (parameters). Thus in this study various alternative techniques such as Ziegler--Nichols rules (ZNPID), Genetic algorithms (GAPID) and fuzzy algorithms (FZPID) have been studied and a comparative study has been made Although with all the three gain tuning methods, required states have reached their target values, but the responses vary much in reaching to final targets. The self-tuned FZPID controller outperforms other two controllers, especially with regard to overshoots and the time taken to tune the gains for each problem. Further, an optimal DI controller is developed for the over determined case with more controls and less targets. Energy loss is considered as an objective function and normal DI controller equations are considered as constraints. Hence, an attempt is made to reduce the energy minimization in water distribution system by formulating an optimal control problem using optimal Dynamic Inversion concept. Finally, leakage reduction model is developed based on excessive pressure minimization problem by locating valves optimally as well as by setting valves optimally. For this purpose, optimization problem is solved using Pattern search algorithms and hydraulic analysis is carried out using EPANET program.

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Kumar, M. Prasanna. "Studies On Application Of Control Systems For Urban Water Networks." Thesis, 2008. http://hdl.handle.net/2005/874.

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Management and supply of water in an urban water distribution system is a complex process, which include various complexities like pressure variations across the network depending on topography, demand variations depending on customers’ requirement and unaccounted water etc. Applying automatic control methods to water distribution systems is a way to improve the management of water distribution. There have been some attempts in recent years to develop optimal control algorithms to assist in the operation of complex water distribution systems. The difficulties involved by these hydraulic systems such as non-linearity, and diurnal demand patterns make the choice of a suitable automatic control method a challenge. For this purpose, this study intends to investigate the applicability of different controllers which would be able to meet the targets as quickly as possible and without creating undue transients. As a first step towards application of different controllers, PD and PID linear controllers have been designed for pump control and valve control in water distribution systems. Then a Dynamic Inversion based nonlinear controller has been designed by considering the non-linearities in the system. Here, different cases considering the effects of initial conditions used, linearization methods used, time step used for integration and selection of gains etc., have been studied before arriving at best controller. These controllers have been designed for both the flow control problems and level control problems. It is found that Dynamic Inversion-based nonlinear controller outperforms other controllers. It is well known that the performance of controllers is much dependent on the tuning of the gains (parameters). Thus in this study various alternative techniques such as Ziegler--Nichols rules (ZNPID), Genetic algorithms (GAPID) and fuzzy algorithms (FZPID) have been studied and a comparative study has been made Although with all the three gain tuning methods, required states have reached their target values, but the responses vary much in reaching to final targets. The self-tuned FZPID controller outperforms other two controllers, especially with regard to overshoots and the time taken to tune the gains for each problem. Further, an optimal DI controller is developed for the over determined case with more controls and less targets. Energy loss is considered as an objective function and normal DI controller equations are considered as constraints. Hence, an attempt is made to reduce the energy minimization in water distribution system by formulating an optimal control problem using optimal Dynamic Inversion concept. Finally, leakage reduction model is developed based on excessive pressure minimization problem by locating valves optimally as well as by setting valves optimally. For this purpose, optimization problem is solved using Pattern search algorithms and hydraulic analysis is carried out using EPANET program.

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Wang, Pei-Shan, and 王珮珊. "Incomplete Differential Proportional Integral Derivative Controlled DC-AC Converters." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/t49th6.

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碩士 義守大學 電機工程學系 103 Traditional PID (proportional-integral-derivative) controllers have been broadly applied to DC-AC inverters due to their simple structures and easy designs. However, in cases with large external interferences, noises of the system may easily be magnified due to the derivative term of traditional PID controllers, further causing system oscillations and instability. To reduce the disadvantage of the derivative term of traditional PID controllers, this thesis proposed an incomplete differential PID controller, by adding a low-pass filter to a traditional PID controller to inhibit external interferences. This proposed controller features not only the advantages of traditional PID controllers, which include simple structures and easy designs, but also higher precisions of tracking control and better overall system performances as the result of adding a low-pass filter to resolve the issue of magnified noises under large external interferences caused by the derivative term of traditional PID controllers. The simulation result shows that the output voltage of the proposed DC-AC converter can still achieve low total harmonic distortion (THD) and fast dynamic response even in cases with highly non-linear load.

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(9798401), Yazeed Ghadi. "Advanced fuzzy logic based control systems for an institutional building in subtropical climate." Thesis, 2018. https://figshare.com/articles/thesis/Advanced_fuzzy_logic_based_control_systems_for_an_institutional_building_in_subtropical_climate/13446071.

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Building management systems (BMS) have the ability to monitor and control buildings mechanical and electrical systems, such as heating, ventilation and air conditioning (HVAC) and lighting systems, for providing indoor thermal comfort and reducing energy consumption. However, most HVAC systems are controlled using conventional controller the functions of which are based on ON/OFFs controller and Proportional-Integral-Derivative (PID) controllers. These controllers are not efficient at saving energy because of the operations of HVAC systems are nonlinear. Thus, the implementation of fuzzy-logic-based control systems within smart buildings are necessary as they are more efficient and will consequently reduce building energy consumption as well as negative impacts on environment. The main aim of this study was to design and develop an advanced fuzzy-logic-based controller for HVAC and indoor lighting systems for an institutional building in subtropical Central Queensland (Australia) to assess its energy and environmental performances, and compare these with the performances of conventional ON/OFF and PID controllers. The fuzzy-logic-based model and control strategies were designed and developed to control indoor temperature, humidity, air quality, air velocity, daylight integration, thermal comfort and energy balance. In addition, the model for indoor temperature and humidity transfer matrix, uncertainties of users’ comfort preference set-points and a fuzzy algorithm were developed. The performances of both ON/OFF and PID control system, and proposed fuzzy-logic-based control systems were simulated using MATLAB software. DAYSIM software was used to simulate the illuminance of lighting system. DesignBuilder and EnergyPlus software were used to develop case study building layout and thermal performance modelling. The simulation was done for indoor and outdoor temperature and humidity control, indoor air quality, and illuminance control. The simulated results were analysed on the basis of real-life events such as the usage of ambient air when its temperature and humidity matches indoor thermal comfort set-point, the usage of existing daylighting rather than the usage of electric lighting, and the consideration of the building’s occupancy level taking into account the controllers’ execution performance panel containing response speed, overshot and robustness adaptability. It was found that an energy savings of about 10% can be achieved if fuzzy-logic-based controllers are introduced compared to conventional PID controllers at full occupancy level for the case study building’s HVAC and lighting systems. The simulation was also done for 50% occupancy and 25% occupancy levels which indicated an energy savings of about 14% at 50% occupancy level, and 24% at 25% occupancy level compared to full occupancy at a given time. In addition, life cycle costs savings of about 20.5% can be achieved using the proposed fuzzy-logic controller. The systems payback period is expected to be nine years, and the system is able to reduce greenhouse gas emissions of 25.5 tonnes of CO2 per annum from the case study building. The thesis has contributed to the process development and design of advanced fuzzy logic controllers for smart buildings in subtropical climate of Australia which is a successful alternative to conventional control systems especially where indoor air quality and mould growth issue is a big concern, e.g. in hospitals, libraries and museums. The novelty of this work is the development of an energy efficient and environment friendly control of HVAC and lighting systems using real life and time events such as ambient air, day-light and actual occupancy levels which have not been addressed previously within an Australian institutional building, specifically under the subtropical climate conditions. Thus, the outcomes of the study will provide designers, developers and decision makers with the essential information and knowledge of applications of advanced fuzzy logic control system for smart buildings.

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Liao, Kuo-Yuan, and 廖國淵. "Design of a Single-Phase Inverter using Trapezoidal Integration-Based Proportional Integral Derivative Controller." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/2vsau7.

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碩士 義守大學 電機工程學系 103 Traditional PID (proportional-integral-derivative) controllers have been broadly applied to single-phase inverters due to their simple structures and easy designs. Yet, the integral term of traditional PID controllers is based on rectangular integration. If the load of the inverter is highly non-linear, the precision of calculations will be low, and there will be steady-state errors. This thesis proposed a PID controller based on trapezoidal integration. Unlike rectangular integration, trapezoidal integration does not underestimate the error area, which can further result in calculation errors. Thus, the proposed single-phase inverter can achieve low total harmonic distortion (THD) output voltage and fast dynamic response. The problem with inverters using traditional PID controller of possible tracking errors in cases with highly non-linear loads can be resolved. To verify the effectiveness of the proposed controller, this thesis used the software MATLAB to run simulations. And the results showed that the AC output voltage of the proposed single-phase inverter is of high quality in any case with resistive load, step load change, or non-linear load.

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Chuang, Chih-Hsien, and 莊志賢. "Design of Proportional Integral Derivative Controller with Feedforward Control and Dead Zone for PWM Inverters." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/s59srs.

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碩士 義守大學 電機工程學系 103 Traditional proportional-integral-derivative (PID) controllers have been broadly applied to pulse-width modulation (PWM) inverters due to their simple structures and easy designs. However, traditional PID controllers are sensitive to parameter changes and load interferences. This fact may result in high total harmonic distortion (THD) and slow dynamic response in cases with an inverter of highly non-linear load. Thus, this thesis proposes a (PID) controllers with feedforward control and dead zone. With the dead zone PID controller, the sensitivity to large parameter changes and highly non-linear load can be reduced. And the feedforward control can enhance dynamic response, that in cases with an inverter of highly non-linear load, there can be low THD and fast dynamic response. To verify the effectiveness of the proposed controller, this thesis used the software MATLAB to run simulations. And the results showed that the proposed inverter can achieve low THD and fast dynamic response in cases with non-linear load.

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Lin, Yenku, and 林彥谷. "Design and Implementation of Modified Proportional Integral Derivative Controller with Differential Forward for DC-AC Inverters." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/56116073130236878859.

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碩士 義守大學 電機工程學系 101 Due to simple structure and good dynamic property, Differential forward PID (DFPID) controller is widely used in DC-AC inverters control. However, the conventional DFPID controller is difficult to inhibit the disturbance of output signal, thus causing the deterioration of the inverter performance. In order to inhibit the disturbance of output signal and enhance the system robustness, a modified differential forward PID (MDFPID) controller for the DC-AC inverter design is proposed in this thesis. The performances of the DC-AC output are low total harmonic distortion, and fast dynamic response under linear and non-linear loading. In addition to retaining the advantages of simple structure and good dynamic property as the conventional DFPID controller, the MDFPID controller has also allowed easy adjustment of control parameters and significant inhibition of disturbance of output signal. To verify the effectiveness of this proposed controller, the Psim software is used to simulate the inverter and the experiment is also realized with digital signal processor. Finally, a high-quality AC output voltage can be obtained under non-linear loading.

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Chang, Chin-Ping, and 張進評. "DESIGN OF A HYBRID FUZZY LOGIC PROPORTIONAL PLUS INTEGRAL-DERIVATIVE CONTROLLER FOR A CLASS OF NONLINEAR SYSTEMS." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/02072317454608048046.

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碩士 大同大學 電機工程學系(所) 93 In this thesis, we used PID-type controller as the foundation, to develop a hybrid fuzzy logic proportional term plus conventional integral and derivative terms (FUZZY P+ID) controller for improving the control response. This kind of controller is constructed by using an incremental fuzzy logic controller in place of the proportional term in the conventional PID controller. This thesis basic principle of this study is to reduce the parameters of a fuzzy controller to be tuned so that, in comparison with the PID-type controller, only one additional parameter should be adjusted. Using conventional PID controller, however, it is difficult to achieve a desired tracking control performance since the dynamic equations of a plant for the manipulator are tightly coupled, highly nonlinear and uncertain. In order to improve the tracking control performance under uncertainty, we propose a new hybrid control scheme for the nonlinear plants, which consists of a fuzzy logic proportional controller and a conventional integral and derivative controller (FUZZY P+ID). Finally, detailed numerical design processes and simulation results are performed to illustrate the effectiveness of the proposed scheme.

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Mendes, Carlos Hugo Ribeiro. "Robust Controller Design for an Autonomous Underwater Vehicle." Master's thesis, 2017. http://hdl.handle.net/10400.6/7956.

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Worldwide there has been a surge of interest in Autonomous Underwater Vehicles (AUV). The ability to operate without human intervention is what makes this technology so appealing. On the other hand, the absence of the human narrows the AUV operation to its control system, computing, and sensing capabilities. Therefore, devising a robust control is mandatory to allow the feasibility of the AUV. Motivated by this fact, this thesis aims to present, discuss and evaluate two linear control solutions being proposed for an AUV developed by a consortium led by CEiiA. To allow the controller design, the dynamic model of this vehicle and respective considerations are firstly addressed. Since the purpose is to enable the vehicle’s operation, devising suitable guidance laws becomes essential. A simple waypoint following and station keeping algorithm, and a path following algorithms are presented. To devise the controllers, a linear version of the dynamic model is derived considering a single operational point. Then, through the decoupling of the linear system into three lightly interactive subsystems, four Proportional Integral Derivative controllers (PIDs) are devised for each Degree Of Freedom (DOF) of the vehicle. A Linear Quadratic Regulator (LQR) design, based on the decoupling of the linear model into longitudinal and lateral subsystems is also devised. To allocate the controller output throughout the actuators, a control allocation law is devised, which improves maneuverability of the vehicle. The results present a solid performance for both control methods, however, in this work, LQR proved to be slightly faster than PID. É visível, a nível mundial, um aumento considerável do interesse em Veículos Autónomos Subaquáticos (Autonomous Underwater Vehicles - AUV). O que torna esta tecnologia tão atraente é a capacidade de operar sem intervenção humana. Contudo, a ausência do ser humano restringe a operação do AUV ao seu sistema de controlo, computação e capacidades de detecção. Desta forma, conceber um controlo robusto é obrigatório para viabilizar o AUV. Motivado por este facto, esta tese tem como objetivo apresentar, discutir e avaliar duas soluções de controlo linear, a propor a um AUV desenvolvido por um consórcio liderado pelo CEiiA. Para que o projeto do controlador seja possível, o modelo dinâmico deste veículo e respectivas considerações são primeiramente abordados. Com a finalidade de possibilitar a operação do veículo, torna-se essencial a elaboração de leis de guidance adequadas. Para este efeito são apresentados algorítmos de Waypoint following e Station keeping, e de path following. Para a projeção dos controladores é derivada uma versão linear do modelo dinâmico, considerando um único ponto operacional. Através da separação do modelo linear em três subsistemas são criados quatro controladores Proporcional Integral Derivativo (PID) para cada grau de liberdade (Degree Of Freedom - DOF) do veículo. É também projetado um Regulador Linear Quadrático (LQR), baseado na separação do modelo linear em dois subsistemas, longitudinal e lateral. É ainda apresentada uma lei de alocação de controlo para distribuir o sinal de saída dos controladores pelos diferentes atuadores. Esta provou melhorar a manobrabilidade do veículo. Os resultados finais apresentam um desempenho sólido para ambos os métodos de controlo. No entanto, neste trabalho, o LQR provou ser mais rápido do que o PID.

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Dissertations / Theses on the topic 'Proportional-Integral- Derivative controllers'

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