Dynamic PID loop control

The Horizontal Test Stand (HTS) SRF Cavity and Cryomodule 1 (CM1) of eight 9-cell, 1.3GHz SRF cavities are operating at Fermilab. For the cryogenic control system, how to hold liquid level constant in the cryostat by regulation of its Joule-Thompson JT-valve is very important after cryostat cool down to 2.0 K. The 72-cell cryostat liquid level response generally takes a long time delay after regulating its JT-valve; therefore, typical PID control loop should result in some cryostat parameter oscillations. This paper presents a type of PID parameter self-optimal and Time-Delay control method used to reduce cryogenic system parameters' oscillation.Comment: 7 pp. Cryogenic Engineering Conference and International Cryogenic Materials Conference CEC-ICMC 2011, 13-17 June 2011. Spokane, Washingto

Optimal frequency control in microgrid system using fractional order PID controller using Krill Herd algorithm

This paper investigates the use of fractional order Proportional, Integral and Derivative (FOPID) controllers for the frequency and power regulation in a microgrid power system. The proposed microgrid system composes of renewable energy resources such as solar and wind generators, diesel engine generators as a secondary source to support the principle generators, and along with different energy storage devices like fuel cell, battery and flywheel. Due to the intermittent nature of integrated renewable energy like wind turbine and photovoltaic generators, which depend on the weather conditions and climate change this affects the microgrid stability by considered fluctuation in frequency and power deviations which can be improved using the selected controller. The fractional-order controller has five parameters in comparison with the classical PID controller, and that makes it more flexible and robust against the microgrid perturbation. The Fractional Order PID controller parameters are optimized using a new optimization technique called Krill Herd which selected as a suitable optimization method in comparison with other techniques like Particle Swarm Optimization. The results show better performance of this system using the fractional order PID controller-based Krill Herd algorithm by eliminates the fluctuations in frequency and power deviation in comparison with the classical PID controller. The obtained results are compared with the fractional order PID controller optimized using Particle Swarm Optimization. The proposed system is simulated under nominal conditions and using the disconnecting of storage devices like battery and Flywheel system in order to test the robustness of the proposed methods and the obtained results are compared.У статті досліджено використання регуляторів пропорційного, інтегрального та похідного дробового порядку (FOPID) для регулювання частоти та потужності в електромережі. Запропонована мікромережева система складається з поновлюваних джерел енергії, таких як сонячні та вітрогенератори, дизельних генераторів як вторинного джерела для підтримки основних генераторів, а також з різних пристроїв для накопичування енергії, таких як паливна батарея, акумулятор і маховик. Через переривчасту природу інтегрованої відновлювальної енергії, наприклад, вітрогенераторів та фотоелектричних генераторів, які залежать від погодних умов та зміни клімату, це впливає на стабільність мікромережі, враховуючи коливання частоти та відхилення потужності, які можна поліпшити за допомогою вибраного контролера. Контролер дробового порядку має п’ять параметрів порівняно з класичним PID-контролером, що робить його більш гнучким та надійним щодо збурень мікромережі. Параметри PID-контролера дробового порядку оптимізовані за допомогою нової методики оптимізації під назвою «зграя криля», яка обрана як підходящий метод оптимізації порівняно з іншими методами, такими як оптимізація методом рою частинок. Результати показують кращі показники роботи цієї системи за допомогою алгоритму «зграя криля», заснованого на PID-контролері дробового порядку, виключаючи коливання частоти та відхилення потужності порівняно з класичним PID-контролером. Отримані результати порівнюються з PID-контролером дробового порядку, оптимізованим за допомогою оптимізації методом рою частинок. Запропонована система моделюється в номінальному режимі роботи та використовує відключення накопичувальних пристроїв, таких як акумулятор та маховик, щоб перевірити надійність запропонованих методів та порівняти отримані результати

Multivariable predictive controller for a test stand of air conditionning

In this paper a Multivariable Predictive Controller has been proposed in a stochastic framework for a M-input N-output system. It has been investigated using a simulation study based on an experimental model of an industrial test stand of air conditioning. Comparisons with the existing PID regulation show a great improvement : both step response and coupling effect limitation have been improved. With a 32 ms calculation time on a PC with 486DX processor (or 8 ms with a Pentium 100 processor), this regulator is able to answer the problems raised by this industrial test stand. Compatible with the industrial regulation hardware, this control algorithm will be soon set up and tested to lead the future air conditioning tests

Split PID control: two sensors can be better than one

The traditional proportional-integral-derivative (PID) algorithm for regulation suffers from a tradeoff: placing the sensor near the sample being regulated ensures that its steady-state temperature matches the desired setpoint. However, the propagation delay (lag) between heater and sample can limit the control bandwidth. Moving the sensor closer to the heater reduces the lag and increases the bandwidth but introduces offsets and drifts into the temperature of the sample. Here, we explore the consequences of using two probes---one near the heater, one near the sample---and assigning the integral term to the sample probe and the other terms to the heater probe. The \textit{split-PID} algorithm can outperform PID control loops based on one sensor.Comment: Rev. Sci. Instrum., to appear. 4 pages, 2 figure

Optimization of DC - DC boost converter using fuzzy logic controller

DC-DC converters are electronic devices used to change DC electrical power efficiently from one voltage level to another. Operation of the switching devices causes the inherently nonlinear characteristic of the DC-DC converters including one known as the Boost converter. Consequently, this converter requires a controller with a high degree of dynamic response. Proportional-Integral- Differential (PID) controllers have been usually applied to the converters because of their simplicity. However, the main drawback of PID controller is unable to adapt and approach the best performance when applied to nonlinear system. It will sufer from dynamic response, produces overshoot, longer rise time and settling time which in turn will influenced the output voltage regulation of the Boost converter. Therefore, the implementation of practical Fuzzy Logic controller that will deal to the issue must be investigated. Fuzzy logic controller using voltage output as feedback for significantly improving the dynamic performance of boost dc-dc converter by using MATLAB@Simulink software. The design and calculation of the components especially for the inductor has been done to ensure the converter operates in continuous conduction mode. The evaluation of the output has been carried out and compared by software simulation using MATLAB software between the open loop and closed loop circuit between fuzzy logic control (FLC) and PID control. The simulation results are shown that voltage output is able to be control in steady state condition for DC-DC boost converter by using this methodology. Scope of this project limited only one types that is Triangle membership function for fuzzy logic control

Future Interests

I denna rapport utreds olika metoder för att kunna reglera vattennivån i vattenkraftverket Avesta Lillfors i Dalarna. Två kraftverk ligger endast 900 m uppströms och detta gör att svarstiderna blir korta och regleringen blir lätt nervös. Att använda sig av vattennivåreglering i ett kraftverk för-enklar dess styrning då anpassning till inflödet sker automatiskt. En flödestabell har tagits fram genom mätningar i turbinen, med hjälp av Winter-Kennedy-metoden. Denna tabell används för att kunna fram-koppla regulatorn och därmed dämpa stora variationer i inflödet. Dessu-tom har en modell av älven skapats och testats med en återkopplad PID-regulator. Utefter dessa tester har lämpliga parametrar tagits fram, som ger önskad stabilitet, noggrannhet och snabbhet. Simuleringar har även gjorts med reglermetoden Fuzzy logic.This report evaluates different methods to create a stable regulation of the water level in the hydro power plant Avesta Lillfors, in county Dalar-na. Another pair of plants are located just 900 m up the stream, which is why the regulation has to act fast. If the water level can be regulated and automatically adjust to the incoming flow, it facilitates the control of the plant. A flow chart is created from measurements in the turbine, using the Win-ter-Kennedy method. The results are used for feedforward control. A PID-regulator with feedback is also simulated in a model of the river. This helps finding the parameters that provide a stable, accurate and fast regu-lation. Fuzzy logic control has also been simulated

Model relative adaptive control (MRAC) for temperature regulation of herb drying system

This project describe the development of temperature regulation for herb drying system. The most important factor for herb drying is temperature. The purposes of temperature are to maintain the quality of herb, prevent degradation of product and also to fast the dry process. The design of this project based on PID and MRAC. PID used as the benchmark on this project. For PID controller, P and PI controllers also build to do the comparison. There are two model of MRAC used which are standard MRAC and modified MRAC. Model reference adaptive control without integral (MRACWI) lastly achieve a better regulation temperature for herb drying system. Based on the results, it is shows that the MRACWI have better percentage improvement in term of settling time compared to PID and standard MRAC. For percentage of performance for MRACWI with 45℃, in terms of settling time it has 80.58% better than PID. For 50℃, it has 71.75% while when 55℃, it has 64.85% and 56.35% when 60℃. In conclusion, the biggest temperature, the lesser percentage of performance. It also shows that MRACWI has none overshoot. It provide that MRACWI is capable to provide robust and precise performance in controlling the temperature and produce better performance in terms of rise time, settling time and percentage overshoot as compared with PID controller and standard MRAC

A Modified Method for Tuning PID Controller for Buck-Boost Converter

This paper presents a design and simulation of simplified method for designing a proportional – integral–derivative(PID)controller operating in continuous conduction mode for the Buck-Boost converter ,this method provides good voltage regulation and is suitable for Buck-Boost Dc-Dc converter, it is exposed to significant variations which may take this system away from nominal conditions caused by the line change and parameters variation at the input .Simulation results shows that this PID controller provides good voltage regulation and is suitable for the Buck-Boost purposes. The obtained results prove the robustness of proposed Controller against variation of the input voltage ,load resistance and the referent voltage of the studied converter

Practical Robust Control Using Self-regulation Nonlinear PID Controller for Pneumatic Positioning System

This paper investigates the robustness of the pneumatic positioning system controlled by Self-regulation Nonlinear PID (SNPID) controller. This controller is executed by utilizing the characteristic of rate variation of the nonlinear gain that are readily available in Nonlinear PID (NPID) controller. A Self-regulation Nonlinear Function (SNF) is used to reprocess the error signal with the purpose to generate the value of the rate variation, continuously. Simulation and experimental tests are conducted. The controller is implemented to a variably loads and pressures. The comparison with the other existing method i.e. NPID and conventional PID are performed and evaluated. The effectiveness of SNPID + Dead Zone Compensator (DZC) has been successfully demonstrated and proved through simulation and experimental studie