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Power converters are electronic circuits for conversion, control and regulation of electric power for various applications, such as from tablet computers in milliwatts to electric power systems at megawatts range. There are three basic types of power converters: buck (output voltage less than the input voltage), boost (output voltage higher than the input voltage) and buck-boost converters. The reliability of the power converters has become an essential focus of industrial applications. This research presents modeling and control of DC/DC boost converter using several control methods, such as Proportional-Integral (PI), Linear Quadratic Regulator (LQR) control, and nonlinear control concepts. Based on standard circuit laws, a mathematical model of the boost converter is derived which is expressed as a bilinear system. First a small signal model of the converter is derived to analyze the small deviations around the steady-state operating point which is used to develop closed loop control using the PI and the LQR methods. Simulation results show that the performance of the converter is good for operation around the operating state, however is unacceptable if there are large variations in the load or the reference input. To improve the performance of the closed loop system, the nonlinear control concept is used which shows excellent closed loop performance under large variations of load or setpoint. Comparative simulation results are presented for closed loop performance under various types of disturbances including random variations in load. / Electrical and Computer Engineering

Yes / Multistage Flash Desalination (MSF) is currently facing an enormous challenge in cutting of the cost: within the last few years, the MSF experienced a gradual decline in investment compared to other techniques of desalting water and thus, a significant improvement is required to remain attractive for capital investors. Improved process control is a cost effective approach to energy conservation and increased process profitability. In this work, a dynamic model is presented using gPROMS model builder to optimize and control MSF process. The Proportional Integral Derivative Controller (PID) and Generic Model Control (GMC) are used successfully to control the Top Brine Temperature (TBT) and the Brine Level (BL) in the last stage at different times of the year. The objectives of this study are: firstly, to obtain optimum TBT and BL profiles for four different seasons throughout the year by minimizing the Total Seasonal Operating Cost (TSOC); secondly, to track the optimum TBT and BL profiles using PID and GMC controllers with and without the presence of constraints; thirdly, to examine how both types of controllers handle the disturbances which occur in the plant. The results are promising and show that GMC controller provides better performance over conventional PID controller to handle a nonlinear system.

Autonomous underwater vehicles (AUVs) play a vital role in the surveillance and mapping of our oceans, often requiring extensive travel in extreme environments. These data-gathering missions benefit from extended durations, making the minimization of power consumption a key consideration in AUV design. One effective strategy to reduce energy use in AUVs is to implement a variable buoyancy system (VBS) for depth control. The purpose of this work is to design, develop, test, and model a variable buoyancy system to enhance the efficiency and capabilities of a high-speed, long-range AUV. After evaluating various VBS designs, a piston-cylinder buoyancy system was selected and developed. A prototype was produced, featuring two manually controlled piston-cylinder units housed within a cylindrical acrylic shell. This setup was tested at shallow depths, successfully demonstrating the VBS’s ability to achieve depth control and its potential for additional functionalities such as orientation control. A Simulink model of the system was also created to simulate its performance. The results from these simulations were compared to both theoretical calculations and experimental data. This model is then used to establish a framework for the design of a depth controller for the VBS once integrated onto an AUV.

More than half a century of intense research in modern control theory has not stopped practitioners from continuing to use PID controllers for most real-world control problems. While not a mathematical one, this might be the most convincing proof of their robustness: if necessary, they can be implemented with minimal control engineering experience. Often, controllers are designed by individuals who are experts in their specific domain but are not dedicated control theory specialists. To address the needs of these engineers, this article wants to put an approach known as Active Disturbance Rejection Control (ADRC) in the spotlight—a method that has gradually evolved into an industry-ready alternative to PID control. Reflecting on two decades of improvements, this article portrays ADRC as a solution for everyday control problems that can be both easier to use and richer in out-of-the-box features.

Model predictive control (MPC) has gained great acceptance in the industry since it was developed and first applied about 25 years ago [1]. It has established its place mainly in the advanced control community. Traditionally, MPC configurations are developed and commissioned by control experts. MPC implementations have usually been only worthwhile to apply on processes that promise large profit increase in return for the large cost of implementation. Thus the scale of MPC applications in terms of number of inputs and outputs has usually been large. This is the main reason why MPC has not made its way into low-level loop control. In recent years, academia and control system vendors have made efforts to broaden the range of MPC applications. Single loop MPC and multiple PID strategy replacements for processes that are difficult to control with PID controllers have become available and easier to implement. Such processes include deadtime-dominant processes, override strategies, decoupling networks, and more. MPC controllers generally have more "knobs" that can be adjusted to gain optimum performance than PID. To solve this problem, general PID replacement MPC controllers have been suggested. Such controllers include forward modeling controller (FMC)[2], constraint LQ control[3] and adaptive controllers like ADCO[4]. These controllers are meant to combine the benefits of predictive control performance and the convenience of only few (more or less intuitive) tuning parameters. However, up until today, MPC controllers generally have only succeeded in industrial environments where PID control was performing poorly or was too difficult to implement or maintain. Many papers and field reports [5] from control experts show that PID control still performs better for a significant number of processes. This is on top of the fact that PID controllers are cheaper and faster to deploy than MPC controllers. Consequently, MPC controllers have actually replaced only a small fraction of PID controllers. This research shows that deficiencies in the feedback control capabilities of MPC controllers are one reason for the performance gap between PID and MPC. By adopting knowledge from PID and other proven feedback control algorithms, such as statistical process control (SPC) and Fuzzy logic, this research aims to find algorithms that demonstrate better feedback control performance than methods commonly used today in model predictive controllers. Initially, the research focused on single input single output (SISO) processes. It is important to ensure that the new feedback control strategy is implemented in a way that does not degrade the control functionality that makes MPC superior to PID in multiple input multiple output (MIMO) processes. / text

The GE Healthcare Life sciences organization develop and manufacture bioreactors, mixers, filtration skids and chromatography systems used together in a biomanufacturing platform. The platform is monitored and controlled by a distributed control system through a Programmable Logic Controller (PLC). The automation software controlling the platform is today tested and verified together with the physical units. The software use PROFIBUS, an industry standard for industrial automation, for communication and control of the units. Limited access to the physical units is usually a bottleneck and it's difficult to test abnormal situations to make sure the correct alarms are triggered. To reduce the hardware dependency and to provide support during test and verification, a virtual environment is developed to simulate the behavior of a bioreactor during execution. A .NET application has been developed together with a mathematical framework to simulate a cell culture and to return relevant process parameters such as pH, dissolved oxygen, temperature and weight. The results show that it's possible to simulate a bioreactor and to communicate with the control system. The software can be a valuable tool when developing and testing automation software but should not be used for process optimization or tuning of control parameters.

[pt] Os laboratórios projetados para testes de motores de combustão interna trabalham sob normas que especificam métodos de ensaios aplicados à avaliação do desempenho do motor. Um motor veicular testado em um dinamômetro de bancada possui equipamentos auxiliares necessários para garantir condições de ensaio específicas, tal como a temperatura do ar de admissão, que deve ser mantida dentro dos valores indicados nas condições-padrão de referência da aplicação pretendida. Diante deste cenário, é evidente a importância de um estudo dos sistemas de condicionamento presentes nas salas de testes de motores. Esta dissertação apresenta o projeto, dimensionamento e simulação de um sistema de condicionamento que controla a temperatura e umidade do ar de admissão para realização de testes de motores de combustão dispostos em dinamômetros de bancada, independente das condições ambientais. A modelagem dinâmica do condicionador de ar e seus componentes (trocador de calor de água gelada, aquecedor elétrico e umidificador) foi implementada no EES. O sistema de controle PID com dois esquemas de ajuste de ganhos (utilizando a fórmula de Ziegler-Nichols, e auto-sintonizado on-line por um sistema supervisório fuzzy) foi desenhado no MATLAB. Para avaliar o desempenho do condicionador e do seu sistema de controle foi estabelecida uma comunicação através do intercâmbio dinâmico de dados entre o MATLAB e o EES. Um estudo de simulação comparativa entre ambos esquemas de ajuste dos controladores, mostra que a estratégia de controle fuzzy supervisório PID proposta permite obter um melhor desempenho dinâmico do sistema condicionador, em termos de estabilidade diante variações tanto na vazão quanto nas condições do ar de admissão, segundo os resultados obtidos na simulação com dados experimentais de um motor Diesel testado sob o ciclo de ensaios dos 13 modos em estado estacionário (ESC test) para certificação de emissões. / [en] Engine testing laboratories designed for automotive vehicles operate under standards that specify test methods used to evaluate the performance of internal combustion engines. A vehicle engine tested on a dynamometer bench has auxiliary equipment required in order to ensure the test conditions, such as intake air temperature which must be maintained within the specified values by standard reference conditions of the intended application. Given this backdrop, it is clear the importance of study of conditioning systems present in engine test facilities. This dissertation presents the design, implementation and simulation of a conditioning system that controls temperature and humidity of the intake air for testing of combustion engines arranged in a dynamometer bench, regardless of ambient conditions. The dynamical modelling of the air conditioner and its components (chilled water heat exchanger, electric heater and humidifier) was implemented in EES. The PID control system with two gains adjustment schemes (using the Ziegler-Nichols formula, and self-tuned on-line with a fuzzy supervisory system) was designed in MATLAB. The conditioning unit performance and its control system was assessed using a communication established through of the dynamic data exchange between EES and MATLAB. A comparative simulation study on both schemes for tuning of controllers shows that the use of the PID supervisory fuzzy control strategy proposed allows for considerable improvements in dynamic performance of the system, in terms of stability on both variation in flow rate and conditions of the intake air, according to the results obtained in the simulation with experimental data of a heavy-duty Diesel engine over the test cycle 13 steady state modes (ESC test) for emission certification.

O elemento final de controle mais usado nas malhas de processo na indústria é a válvula de controle. Portanto, é necessário assegurar que ela possua o melhor desempenho possível, a fim de assegurar um funcionamento satisfatório da malha de controle. Devido ao desgaste natural das partes móveis e o ressecamento das gaxetas, as válvulas apresentam atrito que insere oscilações na abertura da válvula e devido a seu comportamento não linear que diminui a eficiência do controle. A presença de oscilações nas malhas de controle aumenta a variabilidade das variáveis de processo, o desgaste dos componentes e o consumo de energia, além de provocar o desperdício de materiais. Por isto, no presente trabalho são estudados e implementados diferentes compensadores de atrito existentes na literatura, visando reduzir o efeito do atrito nas válvulas e, por sua vez as oscilações na variável do processo. Estes métodos são aplicados na Planta Piloto de Neutralização de pH do Laboratório de Controle de Processos Industriais (LCPI). O processo de neutralização de pH é não-linear e apresenta características variantes no tempo, as quais tornam mais complexo o controle do processo. Inicialmente foi feita a implementação dos compensadores em um software acadêmico (MATLAB®), devido à familiaridade que se tem com ele, o que facilitou um melhor entendimento dos métodos de compensação junto com o controlador PID no processo. Em uma segunda etapa, a fim de trazer os estudos a um ambiente mais prático, foram implementados os algoritmos de compensação de atrito em um sistema de controle industrial (ABB®). Nos dois casos se realizaram testes em modo servo e regulatório e se avaliaram os resultados obtidos usando o índice ITAE (Integral Time Absolute Error). Os resultados evidenciam que os compensadores conseguem diminuir a variabilidade na válvula de controle, sendo que o compensador CR2 apresentou o melhor desempenho para o modo servo e regulatório. / The most used final control element in process loops in the industry is the control valve. It must ensure that it has the best possible performance in order to guarantee a satisfactory operation of the control loop. Due of the natural wear of moving parts and drying gaskets, valves exhibit friction. This friction inserts oscillations in the valve opening and due to its non-linear behavior; this causes the efficiency to decrease. The presence of oscillations in the control loop increases the variability of the process variables, the component wear, energy consumption and cause a waste of materials. Therefore, in this work we studied and implemented different friction compensation methods that exist in literature, in order to reduce the effect of friction on the valves and in turn the oscillations in the process variable. These methods are applied in the Pilot Plant Neutralization pH of Industrial Process Control Laboratory (LCPI), the pH neutralization process is nonlinear and presents time-varying characteristics, these characteristics become the control process more complex. Initially, it was made the implementation of compensation methods in academic software (MATLAB®), due to the familiarity that already exist with it, which facilitated a better comprehension of the compensation methods with the PID controller in the process. In a second step, in order to bring the study to a more practical environment, the friction compensation algorithms were implemented in an industrial control system (ABB®). In both cases were performed tests inn servo and regulatory mode, and evaluated the results using the ITAE index (Integral Time Absolute Error). The results show that in general terms that the compensating methods showing a very satisfactory performance, with the compensator CR2 showed the best performance for the servo and regulatory mode.