171 research outputs found

    Control of DC Motor Using Integral State Feedback and Comparison with PID: Simulation and Arduino Implementation

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    The Direct Current (DC) motor is widely applied in various implementations. The main problem in the DC motor is controlling the angular speed on the specific reference. This research then proposed an integral state feedback design for tracking control in DC motor, with Simulink Matlab simulation and the Arduino hardware implementation. The results will be compared with the implementation of the PID controller. The integral state feedback controller can handle the system to reach the setpoint with good performance in the simulations, even with changing different poles and setpoints. In the hardware implementation, the current sensor (INA219) and encoder sensor are used since all state variables need to be calculated. Based on the result, the controller can reach the setpoint stably with oscillation. Similar results are showed in simulations with different setpoints. Compared with the PID Controller, the integral state feedback controller has a better response with faster rise time and faster settling time

    Synchronizing of Stabilizing Platform Mounted on a Two-Wheeled Robot

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    This paper represents the designing, building, and testing of a self-stabilizing platform mounted on a self-balancing robot. For the self-stabilizing platform, a servo motor is used and for the self-balancing robot, two dc motors are used with an encoder, inertial measurement unit, motor driver, an Arduino UNO microcontroller board. A PID controller is used to control the balancing of the system. The PID controller gains (Kp, Ki, and Kd) were evaluated experimentally. The value of the tilted angle from IMU was fed to the PID controller to control the actuated motors for balancing the system. For the self-stabilizing control part, whenever the robot tilted, it maintained the horizontal position by rotating that much in the opposite direction

    Fuzzy Logic Control and PID Controller for Brushless Permanent Magnetic Direct Current Motor: A Comparative Study

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    Electrical machines based on permanent magnet material excitations have been applied in many sectors since they are distinguished by their high torque-to-size ratio and offer high efficiency. Brushless permanent magnetic direct current (BLPMDC) motors are one type of these machines. They are preferable over conventional DC motors. one of the main challengings of the BLPMDC motor drives is the inherited feature of nonlinearity. Therefore, a conventional PID controller would not be an efficient choice for the speed control of such motors. The object of this paper is to design an efficient speed control for the BLPMDC motor. The proposed controller is based on the Fuzzy logic technique. MATLAB/ Simulink has been employed to design and test the drive system. Simulations were carried out for three cases, the first without a controller, the other using conventional control, and the third using expert systems. The results proved the possibility of improving the engine's working performance using the control systems. They also proved that the adoption of expert systems is better than the traditional nonlinear systems. The simulation response shows that the Rise Time(tr) at PID equals 66.306ms, while it equals 19.530ms for the Fuzzy logic controller. Moreover, Overshoot for PID and Fuzzy logic controller are 6.989% and 1.531%, respectively. On the other hand, undershoot is equal to 1.788% and 11.924% for PID and Fuzzy logic controller, respectively

    Fuzzy control system review

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    Overall intelligent control system which runs on fuzzy, genetic and neural algorithm is a promising engine for large –scale development of control systems . Its development relies on creating environments where anthropomorphic tasks can be performed autonomously or proactively with a human operator. Certainly, the ability to control processes with a degree of autonomy is depended on the quality of an intelligent control system envisioned. In this paper, a summary of published techniques for intelligent fuzzy control system is presented to enable a design engineer choose architecture for his particular purpose. Published concepts are grouped according to their functionality. Their respective performances are compared. The various fuzzy techniques are analyzed in terms of their complexity, efficiency, flexibility, start-up behavior and utilization of the controller with reference to an optimum control system condition

    Exposure level of ergonomic risk factors in grocery retail industries

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    Generally, grocery retail work requires manual material handling tasks that Involve Ergonomic Risk Factors (ERFs) such as posture, repetition and movements. The aim of this study was to examine the level of Ergonomic Risk Factors (ERFs) among material handlers in grocery retail industries. This study was conducted by using two different types of tools which were Workplace Ergonomic Risk Assessment (WERA) and Rapid Entire Body Assessment (REBA) as a direction observation method. For WERA method, results showed most of them experienced high exposure level for leg and contact stress while for REBA method, results showed most of them experienced medium exposure level for upper arm and trunk. From the research conducted, MSDs and ERFs do related as it showed that musculoskeletal disorders may arise if the workers ignored the safety in ergonomic risk factors. Hence, some ergonomic improvements are needed in order to prevent workers from developing MSDs

    Speed and Current Limiting Control Strategies for BLDC Motor Drive System: A Comparative Study

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    As a result of increasing the use of the brushless direct current (BLDC) motor in many life applications instead of the traditional motors, it is important to list and specify the more for its controlling methods. This paper presents a number of speed and current controlling methods as hysteresis band, variable dc-link bus voltage and pulse width modulation (PWM) controlling methods. These controlling methods have proportional integral derivative (PID) gains which are optimized by using particle swarm optimization (PSO) algorithm. By using fast Fourier transform (FFT) analysis to study the controller behavior from frequency analysis of the output signals and compute total harmonic distortion (THD), it can specify the more useful controlling method. The framework is modeled and fabricated by using Matlab/Simulink

    An application of modified adaptive bats sonar algorithm (MABSA) on fuzzy logic controller for dc motor accuracy

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    Controllers are mostly used to improve the control system performance. The works related to controllers attract researchers since the controller can be applied to solve many industrial problems involving speed and position. Fuzzy logic controller (FLC) gains popularity since it is widely used in industrial application. However, the FLC structure is still lacking in terms of the accuracy and time response. Although there are optimization technique used to obtain both accuracy and time response, it is still lacking. Therefore, this research presents works on the FLC system which is the fuzzy inference system that will be optimized by the modified adaptive bats sonar algorithm (MABSA) for the DC servo motor position control. The MABSA will be optimized with the range of the membership input in the FLC. The research aims are to achieve accuracy while minimizing the time response of the DC servo motor. This is done by designing the FLC using the Matlab toolbox. After the FLC is designed completely, the Simulink block diagram for the DC servo motor and FLC are built to see the performance of the controller. The range of the membership function for inputs and outputs will be optimized by the MABSA to get the best positional values. The performance of the developed FLC with the optimized MABSA is verified through the simulation and robustness tests with the system that did not use the FLC and also the system without MABSA. It was demonstrated from the study that the proposed FLC with optimization of MABSA algorithm was able to yield an improvement of 3.8% with respect to the rise time in comparison to other control schemes evaluated. When compared with PSO algorithm, proposed FLC optimized by MABSA showed improvement by 12.5% in rise time and 10% in settling time. PSO-FLC also give 0.6% steady state error compared to the MABSA-FLC. In conclusion, the results validate the better performance in terms of rise time and settling time of the developed FLC that has been optimized by the MABSA

    Sliding Mode Control

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    The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area
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