DIFFERENTIAL EVOLUTION FOR OPTIMIZATION OF PID GAIN IN ELECTRICAL DISCHARGE MACHINING CONTROL SYSTEM

ABSTRACT PID controller of servo control system maintains the gap between Electrode and workpiece in Electrical Dis- charge Machining (EDM). Capability of the controller is significant since machining process is a stochastic phenomenon and physical behaviour of the discharge is unpredictable. Therefore, a Proportional Integral Derivative (PID) controller using Differential Evolution (DE) algorithm is designed and applied to an EDM servo actuator system in order to find suitable gain parameters. Simulation results verify the capabilities and effectiveness of the DE algorithm to search the best configuration of PID gain to maintain the electrode position. Keywords: servo control system; electrical discharge machining; proportional integral derivative; con- troller tuning; differential evolution

Adaptive optimal digital PID controller

Abstract: It is necessary to change the parameters of PID controller if the parameters of plants change or there are disturbances. Particle swarm optimization algorithm is a powerful optimization algorithm to find the global optimal values in the problem space. In this paper, the particle swarm optimization algorithm is used to identify the model of the plant and the parameter of digital PID controller online. The model of the plant is identified online according to the absolute error of the real system output and the identified model output. The digital PID parameters are tuned based on the identified model and they are adaptive if the model is changed. Simulations are done to validate the proposed method comparing with the classical PID controller.Originally presented at 2014 International Conference on Mechatronics, Automation and Manufacturing (ICMAM 2014), Beijing, October 24-26, 2014

Advanced and Innovative Optimization Techniques in Controllers: A Comprehensive Review

New commercial power electronic controllers come to the market almost every day to help improve electronic circuit and system performance and efficiency. In DC–DC switching-mode converters, a simple and elegant hysteretic controller is used to regulate the basic buck, boost and buck–boost converters under slightly different configurations. In AC–DC converters, the input current shaping for power factor correction posts a constraint. But, several brilliant commercial controllers are demonstrated for boost and fly back converters to achieve almost perfect power factor correction. In this paper a comprehensive review of the various advanced optimization techniques used in power electronic controllers is presented

On the Selection of Tuning Methodology of FOPID Controllers for the Control of Higher Order Processes

In this paper, a comparative study is done on the time and frequency domain tuning strategies for fractional order (FO) PID controllers to handle higher order processes. A new fractional order template for reduced parameter modeling of stable minimum/non-minimum phase higher order processes is introduced and its advantage in frequency domain tuning of FOPID controllers is also presented. The time domain optimal tuning of FOPID controllers have also been carried out to handle these higher order processes by performing optimization with various integral performance indices. The paper highlights on the practical control system implementation issues like flexibility of online autotuning, reduced control signal and actuator size, capability of measurement noise filtration, load disturbance suppression, robustness against parameter uncertainties etc. in light of the above tuning methodologies.Comment: 27 pages, 10 figure

New optimal controller tuning method for an AVR system using a simplified Ant Colony Optimization with a new constrained Nelder-Mead algorithm

[EN] In this paper, an optimal gain tuning method for PID controllers is proposed using a novel combination of a simplified Ant Colony Optimization algorithm and Nelder¿Mead method (ACO-NM) including a new procedure to constrain NM. To address Proportional-Integral-Derivative (PID) controller tuning for the Automatic Voltage Regulator (AVR) system, this paper presents a meta-analysis of the literature on PID parameter sets solving the AVR problem. The investigation confirms that the proposed ACO-NM obtains better or equivalent PID solutions and exhibits higher computational efficiency than previously published methods. The proposed ACO-NM application is extended to realistic conditions by considering robustness to AVR process parameters, control signal saturation and noisy measurements as well as tuning a two-degree-of-freedom PID controller (2DOF-PID). For this type of PID, a new objective function is also proposed to manage control signal constraints. Finally, real time control experiments confirm the performance of the proposed 2DOF-PIDs in quasi-real conditions. Furthermore, the efficiency of the algorithm is confirmed by comparing its results to other optimization algorithms and NM combinations using benchmark functions.This work was supported by the Vanier Canada Graduate Scholarship, the Michael Smith Foreign Study Supplements Program from the Natural Sciences and Engineering Research Council of Canada and by the Ministerio de Economia y Competitividad (Spain), project DPI2015-71443-R. It was also supported by the Bourse Mobilite Etudiante from Ministere de l'Education du Quebec, the CEMF Claudette MacKay-Lassonde Graduate Engineering Ambassador Award and the SWAAC Bourseau merite pour etudiantes de cycles superieurs.Blondin, MJ.; Sanchís Saez, J.; Sicard, P.; Herrero Durá, JM. (2018). New optimal controller tuning method for an AVR system using a simplified Ant Colony Optimization with a new constrained Nelder-Mead algorithm. Applied Soft Computing. 62:216-229. https://doi.org/10.1016/j.asoc.2017.10.007S2162296

Tilt-fractional order proportional integral derivative control for DC motor using particle swarm optimization

Introduction. Recently, the most desired goal in DC motor control is to achieve a good robustness and tracking dynamic of the set-point reference speed of the feedback control system. Problem. The used model should be as general as possible and consistently represent systems heterogeneous (which may contain electrical, mechanical, thermal, magnetic and so on). Goal. In this paper, the robust tilt-fractional order proportional integral derivative control is proposed. The objective is to optimize the controller parameters from solving the criterion integral time absolute error by particle swarm optimization. The control strategy is applied on DC motor to validate the efficiency of the proposed idea. Methods. The proposed control technique is applied on DC motor where its dynamic behavior is modeled by external disturbances and measurement noises. Novelty. The proposed control strategy, the synthesized robust tilt-fractional order proportional integral derivative speed controller is applied on the DC motor. Their performance and robustness are compared to those provided by a proportional integral derivative and fractional order proportional integral derivative controllers. Results. This comparison reveals superiority of the proposed robust tilt-fractional order proportional integral derivative speed controller over the remaining controllers in terms of robustness and tracking dynamic of the set-point reference speed with reduced control energy.Вступ. Останнім часом найбільш бажаною метою керування двигуном постійного струму є досягнення гарної надійності та динамічного відстеження заданої опорної швидкості системи керування зі зворотним зв’язком. Проблема. Використовувана модель має бути якомога загальнішою і несуперечливо представляти різнорідні системи (які можуть містити електричні, механічні, теплові, магнітні тощо). Мета. У цій статті пропонується робастне управління похідною пропорційного інтеграла дробового порядку нахилу. Мета полягає в тому, щоб оптимізувати параметри контролера шляхом вирішення критерію інтегральної абсолютної тимчасової помилки шляхом оптимізації рою частинок. Стратегія управління застосовується до двигуна постійного струму для перевірки ефективності запропонованої ідеї. Методи. Пропонований метод управління застосовується до двигуна постійного струму, динамічна поведінка якого моделюється зовнішніми перешкодами та шумами вимірів. Новизна. Пропонована стратегія управління, синтезований робастний пропорційно-інтегрально-диференціальний регулятор швидкості нахилу дробового порядку застосовується до двигуна постійного струму. Їх продуктивність та надійність порівнюються з показниками, що забезпечуються контролерами пропорційної інтегральної похідної та пропорційної інтегральної похідної дробового порядку. Результати. Це порівняння показує перевагу запропонованого робастного пропорційно-інтегрально-диференціального регулятора швидкості нахилу дробового порядку над іншими регуляторами з погляду робастності та динамічного відстеження заданої опорної швидкості зі зменшеною енергією управління

Optimization of PID Controller Parameters on Flow Rate Control System Using Multiple Effect Evaporator Particle Swarm Optimization

This study aims to improve the performance of Proportional+Integral+Differential (PID) control to reduce the speed of the steam flow rate and search optimal points in the evaporation process of Multiple Effect Evaporator (MEE). Optimization of PID control tuning parameters using Particle Swarm Optimization (PSO) by adding a weighting factor of inertia is expected to handle nonlinear systems with evaporator undershoot response characteristics that are difficult to treat and improve response of the system with large overshoot, and long rise time. The results showed PSO is able to provide improved performance tuning PID control system to improve system response in MEE control system with a rise time of 0.01 seconds, 3.35% overshoot, settling time of 6.10 seconds and able respond plant undershoot MEE of 28.11%.The results show that, PSO with inertia weight w provides additional tuning better than PID control by ZN method of max criteria over shoot, rise time and settling time of 5.38%, 3.05 seconds, 10.1 seconds, compared to tuning PID control  method with PSO (3.35%, 0.01 seconds, 6.10 seconds).