Abstract-Fuzzy logic control has been successfully utilized in various industrial applications; it is generally used in complex control systems, such as chemical process control. Today, most of the fuzzy logic controls are still implemented on expensive highperformance processors. This paper analyzes the effectiveness of a fuzzy logic control using a low-cost controller applied to a water level control system. The paper also gives a low-cost hardware solution and practical procedure for system identification and control. First, the mathematical model of the process was obtained with the help of Matlab. Then two methods were used to control the system, PI (Proportional, Integral) and fuzzy control. Simulation and experimental results are presented.
This article presents the application of the harmony search (HS) optimization algorithm for selective harmonic elimination PWM (SHEPWM) in a new topology of multilevel inverters with reduced number of electronic switching elements. The main objective of the harmonic elimination strategy is eliminating undesired low-rank harmonics in order to improve the quality of the output waveform. The harmonic elimination strategy is achieved by solving a system of nonlinear equations. In this paper harmony search optimization is applied using artificial neural networks (ANNs) on a new 21-level inverter topology. The algorithm is based on a music improvisation process. MATLAB programming software is used to develop a harmony search optimization program for harmonic elimination. A small-scale laboratory of the proposed 21-level inverter is built to validate the simulation results and to prove the efficiency of the proposed control scheme.
Summary Fuzzy controllers are a powerful tool for controlling complex processes. However, its robustness capacity remains moderately limited because it loses its property for large ranges of parametric variations. This paper presents a new form of adaptive control used as a remedy for this issue, applied to the speed control of a multiphase multimachine motor drives system. The multimachines under investigation are a six‐phase and a three‐phase induction motors whose stator windings are connected in series and supplied by a single six‐leg converter and controlled using vector control approach. Fuzzy controllers are used to implement this type of control to increase its robustness. This leads to a fuzzy behavior model control (BMC). The results of the simulation confirm the validity and effectiveness of the control strategy proposed in both terms of performance and robustness (rotor inertia variations J1 = 5 J1nominal) of the provision of such an adaptive control for electrical drives with the two independently controlled machines.
Abstract-This paper presents the application of differential evolution algorithm to obtain optimal switching angles for a single-phase seven-level to improve AC voltage quality. The proposed inverter in this article is composed of two H-bridge cells with non-equal DC voltage sources in order to generate multiple voltage levels. Selective harmonic elimination pulse width modulation (SHPWM) strategy is used to improve the AC output voltage waveform generated by the proposed inverter. The differential evolution (DE) optimization algorithm is used to solve non-linear transcendental equations necessary for the (SHPWM). Computational results obtained from computer simulations presented a good agreement with the theoretical predictions. A laboratory prototype based on STM32F407 microcontroller was built in order to validate the simulation results. The experimental results show the effectiveness of the proposed modulation method.
The main objective of this study is the improvement of output voltage waveform quality generated by a new modified Cascaded H-bridge (CHB) multilevel inverter using Selective Harmonic Elimination (SHE) method and passive LC filters. A PWM technique with SHE is used to control fundamental harmonic and eliminate harmonics of chosen lower-order in CHB multilevel inverter. A passive LC filter is added to the inverter in order to eliminate the high-order harmonics. The switching angles are drawn by solving a non-linear equations system using Hybrid Genetic Algorithm (HGA). In order to evaluate the performance of the HGA in solving the non-linear equations of the system presented in this study, the proposed optimization algorithm was compared to the well-known particle swarm optimization method. Different cases including 5-and 7-level inverters with different values of modulation indices are reported. The simulation findings are validated through experimental results. ARTICLE HISTORY
This article presents the application of the harmony search (HS) optimization algorithm for harmonic elimination in a new topology of multilevel inverters with a reduced number of electronic switching elements. The main objective of the harmonic elimination strategy is eliminating undesired low rank harmonics in order to improve the quality of the output waveform. The harmonic elimination strategy is achieved by solving a system of nonlinear equations. In this paper, HS optimization is applied using artificial neural networks (ANNs) on a new 21-level inverter topology. The algorithm is based on the music improvisation process. MATLAB programming software was used to develop a HS optimization program for harmonic elimination. The main reason for using selective harmonic elimination based on ANNs in this study is to control the proposed multilevel inverter in real-time. In order to assess the performance of the proposed optimization method, it was compared to particle swarm optimization and the genetic algorithm. A small-scale laboratory of the proposed 21-level inverter is built to validate the simulation results and to prove the efficiency of the proposed control scheme.
In this paper, a control scheme based on lookup table fuzzy proportionalintegral-derivate (PID) controller for the quadrotor unmanned aerial vehicle (UAV) movement control is proposed. This type of control provides enhanced quadrotor movement control beyond what can be achieved with conventional controllers and has a less computational burden on the processor. The proposed control scheme uses three lookup table based fuzzy logic controllers to control the different movement ranges of a quadrotor (i.e. roll, pitch, and yaw) to achieve stability. The mathematical model of a quadrotor, used to design the proposed controller, is derived based on the Lagrange approach. The processor in the loop (PIL) technique was used to test and validate the proposed control scheme. MATLAB/Simulink environment was used as a platform for the quadrotor model, whereas a low cost and high-performance STM32F407 microcontroller was used to implement the controllers. Data transfer between the hardware and software is via serial communication converter. The control system designed based on simulation is tested and validated using “processor in the loop” techniques.
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