A memetic algorithm based on Artificial Bee Colony for optimal synthesis of mechanisms

En este documento se presenta una propuesta novedosa de un algoritmo híbrido modular, como herramienta para resolver problemas de ingeniería del mundo real. Se implementa y aplica un algoritmo memético, MemMABC, para la solución de dos casos de diseño de mecanismos, con el fin de evaluar su eficiencia y rendimiento. El algoritmo propuesto es simple y flexible debido a su modularidad; estas características lo vuelven altamente reutilizable para ser aplicado en una amplia gama de problemas de optimización. Las soluciones de los casos de estudio también son modulares, siguiendo un esquema de programación estructurada que incluye el uso de variables globales para la configuración, y de subrutinas para la función objetivo y el manejo de las restricciones. Los algoritmos meméticos son una buena opción para resolver problemas duros de optimización, debido a la sinergia derivada de la combinación de sus componentes: una metaheurística poblacional para búsqueda global y un método de refinamiento local. La calidad en los resultados de las simulaciones sugiere que el MemMABC puede aplicarse con éxito para la solución de problemas duros de diseño en ingeniería.In this paper a novel proposal of a modular hybrid algorithm as a tool for solving real-world engineering problems is presented. A memetic algorithm, MemMABC, is implemented with this approach and applied to solve two case studies of mechanism design, in order to evaluate its efficiency and performance. Because of its modularity, the proposed algorithm is simple and flexible; these features make it quite reusable to be applied on different optimization problems, with a wide scope. The solutions of the optimization problems are also modular, following a scheme of structured programming that includes the use of global variables for configuration, and subroutines for the objective function and the restrictions. Memetic algorithms are a good option to solve hard optimization problems, because of the synergy derived from the combination of their components: a global search population-based metaheuristic and a local refinement method. The quality of simulation results suggests that MemMABC can be successfully applied to solve hard problems in engineering design.Peer Reviewe

Application of model based predictive control to a pumped storage hydroelectric plant

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Modelling and controlling hydropower plants

Hydroelectric power stations are a major source of electricity around the world; understanding their dynamics is crucial to achieving good performance.  Modelling and Controlling Hydropower Plants discusses practical and well-documented cases of modelling and controlling hydropower station modelling and control, focussing on a pumped storage scheme based in Dinorwig, North Wales.  Single-input-single-output and multiple-input-multiple-output models, which cover the linear and nonlinear characteristics of pump-storage hydroelectric power stations, are reviewed. The most important dynamic features are discussed, and the verification of these models by hardware in the loop simulation is described. To show how the performance of a pump-storage hydroelectric power station can be improved, classical and modern controllers are applied to simulated models of the Dinorwig power plant. These include PID, fuzzy approximation, feed-forward and model-based predictive control with linear and hybrid prediction models. Modelling and Controlling Hydropower Plants will be of value to control engineers working in industry. In addition, the theoretical treatment of modern and classic controllers will be useful for academic researchers and graduate students in control and power engineering. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control

Fractional Order PI-Based Control Applied to the Traction System of an Electric Vehicle (EV)

This paper presents a design of a cruise control based on a fractional-order proportional and integral (PI) direct torque control applied to the traction system of an electric vehicle (EV). The paper also discusses the modeling, control design and simulation, resulting in a numerical simulator composed of detailed models of the main components: transmission system, induction motor, power electronics, control system, and vehicle dynamics. The simulation was developed in MATLAB/Simulink and will allow the estimation of the energy consumption of an EV under specific configurations. Simulation results show the efficiency of the designed control. These simulations were carried out using the velocity profiles given by the New Europe Drive Cycle (NEDC)

A memetic algorithm based on Artificial Bee Colony for optimal synthesis of mechanisms

In this paper a novel proposal of a modular hybrid algorithm as a tool for solving real-world engineering problems is presented. A memetic algorithm, MemMABC, is implemented with this approach and applied to solve two case studies of mechanism design, in order to evaluate its efficiency and performance. Because of its modularity, the proposed algorithm is simple and flexible; these features make it quite reusable to be applied on different optimization problems, with a wide scope. The solutions of the optimization problems are also modular, following a scheme of structured programming that includes the use of global variables for configuration, and subroutines for the objective function and the restrictions. Memetic algorithms are a good option to solve hard optimization problems, because of the synergy derived from the combination of their components: a global search population-based metaheuristic and a local refinement method. The quality of simulation results suggests that MemMABC can be successfully applied to solve hard problems in engineering design

Bounded Attitude Control with Active Disturbance Rejection Capabilities for Multirotor UAVs

International audienceThis paper addresses an attitude tracking control design applied to multirotor unmanned aerial vehicles (UAVs) based on an ADRC approach. The proposed technique groups the endogenous and exogenous disturbances into a total disturbance, and then this is estimated online via an extended state observer (ESO). Further, a quaternion-based feedback is developed, which is assisted by a feedforward term obtained via the ESO to relieve the total disturbance actively. The control law is bounded; consequently, it takes into account the maximum capabilities of the actuators to reject the disturbances. The stability is analyzed in the ISS framework, guaranteeing that the closed loop (controller-ESO-UAV) is robustly stable. The simulation results allow validation of the theoretical features

Validation of Sliding Mode and Passivity Control in High-Power Quadratic Buck Converter Through Rapid Prototyping

This document introduces a rapid control prototyping (RCP) approach applied to the industrial sector using a non-linear Quadratic Buck Converter (QBC) DC-DC. The goal is to reduce manufacturing costs for materials and electronic devices while enhancing the power quality in the system’s response. An experimental setup is utilized to create a functional model, converting 380 VDC to 48 VDC at a power level of 500 W. dSPACE CP1103 is employed to implement Model in the Loop (MIL), Software in the Loop (SIL), and Hardware in the Loop (HIL) simulations. Modern control techniques, including sliding mode control (SMC) and passivity-based control (PBC), are employed to devise a robust control scheme capable of maintaining stability in real-time (RT) and resisting disturbances. The document concludes with a performance analysis, PI, Cp, CpK, Z-score, and ITAE considering response time, signal accuracy, system stability, and resource utilization efficiency