Robust Adaptive Sliding Mode Control Design with Genetic Algorithm for Brushless DC Motor

This study aims to design a control scheme that is capable to improve performance and efficiency of brushless DC motor (BLDC) in operating condition. The control scheme is composed of sliding mode controller (SMC) with proportional-integral-derivative (PID) sliding surface. The PID sliding surface is used to improve the system transient response. Then, the SMC-PID is optimized by genetic algorithm optimization for further improvement on the stability and robustness against nonlinearities and disturbances. Chattering problem that appear in the SMC is minimized by employing an adaptive switching gain for the SMC that is integrated with Luenberger Observer. Lyapunov function candidate is applied to guarantee the stability of the system. Simulation on the proposed work is done in Matlab Simulink. Results of the simulation works indicate that the proposed control scheme can improve the transient response, the stability and robustness of the BLDC motor compared to the conventional SMC in the existence of nonlinearities and disturbances

Robust and Accurate Positioning Control of Solar Panel System Tracking based Sun Position Image

This study contains the robust and accurate positioning control design for solar panel system consisting of elevation and azimuth axis tracker. The ultimate objective of the study is to ensure the solar panel move accurately to follow its tracking reference against mechanical load and other disturbances. The tracking reference was the images of actual sun position. Image processing result as the initial reference and high precision encoder as the controller feedback path were intended to obtain the accurate position of hardware response. Sliding Mode Controller (SMC) with Proportional Integral Derivative (PID) Sliding Surface was employed as control technique that guarantee the solar panel system robust against disturbances or load variation. The proposed method was evaluated through software simulation and hardware validation. The software for the simulation and validation was LabVIEW. While the software for image processing was Vision Assistant. From hardware validation, accuracy of the solar panel system to track the sun position image for elevation and azimuth were 2.622% (0.03007 ) and 0.244% (0.00893 ), respectively. These results indicate that the solar panel system was available to move accurately to track the sun position both in azimuth and elevation axis

Sizing Optimization and Operational Strategy of Hres (PV-WT) using Differential Evolution Algorithm

The instability of energy resources and corresponding cost of the system are the main two problems for designing the hybrid solar-wind power generation systems. The configuration of the system must have a high reliability on the power supply availability but with a minimum cost. The purpose of this paper is to find the most optimum or balanced configuration between technical reliability and total annual cost for the PV module number, the wind turbine number, and the battery number. The appropriate strategy of load management is needed by adjusting the potential energy resource to the load power demand. Loss of Power Supply Probability (LPSP) is a method to determine the ratio of power generation unavailability by the system configuration which used as technical analysis. Annualized Cost of System (ACS) is a method to determine the total annualized cost of the project lifetime which used as economic analysis. The result from the simulation showed that the Differential Evolution (DE) algorithm can be an alternative method to find the best configuration with a low number of LPSP and ACS. Since DE has a better efficacy and faster time to find global optimum than other algorithms

Adaptive-Fuzzy-PID Controller Based Disturbance Observer for DC Motor Speed Control

DC motors are one of the most widely used actuators in industry applications. In its use, the reliability of DC motor performance becomes an important prerequisite that must be met. Therefore, a control scheme is required to meet the above performance demands, especially in the transient, steady state, and system stability aspects. The main problems in DC motor control system, especially in terms of speed control, are the occurrence of changes in system parameters and the presence of disturbances such as load changes. This study offers an Adaptive- Fuzzy-PID (AFPID) control scheme equipped with Disturbance Observer (DOb). AFPID scheme plays a role in handling the change of system parameters, while DOb serves to estimate the occurrence of disturbance. The AFPID control scheme was verified experimentally on a DC motor test-rig that was subjected to load-bearing disturbance. The results of the experiments show that the AFPID control scheme with DOb has a better transient response performance than AFPID without DOb, as well as in the ability to compensate the load changes. The combination of AFPID with DOb offers a more stable performance to DC motor has and is more insensitive to disturbance

Active Fault Tolerance Control For Sensor Fault Problem in Wind Turbine Using SMO with LMI Approach

In this paper, we start to investigate the sensor fault problem in a Wind Turbine model with Fault Tolerant Control (FTC). FTC is used to allow the parameters of the controller to be reconfigured in accordance error information obtained online from sensors to improve the stability and overall performance of the system when an error occurs. The design is divided into two parts. The first part is designed Sliding Mode Observer (SMO) based Fault Detection Filter (FDF) to generate a residual signal to estimate fault. FDF is designed to maximize sensitivity fault. The second is a design output feedback control and Fault Compensation to guarantee the stability and performance system from disturbance by ignoring faults. Moreover, the function of fault compensation is to minimize effect fault of the system. The main contribution of this research is FTC proved to solve the sensor fault problem in a Wind Turbine model. The simulation showed the effectiveness of this method to estimate the fault and stabilized the system faster to a steady condition

Object Detection of Omnidirectional Vision Using PSO-Neural Network for Soccer Robot

The vision system in soccer robot is needed to recognize the object around the robot environment. Omnidirectional vision system has been widely developed to find the object such as a ball, goalpost, and the white line in a field and recognized the distance and an angle between the object and robot. The most challenging in develop Omni-vision system is image distortion resulting from spherical mirror or lenses. This paper presents an efficient Omni-vision system using spherical lenses for real-time object detection. Aiming to overcome the image distortion and computation complexity, the distance calculation between object and robot from the spherical image is modeled using the neural network with optimized by particle swarm optimization. The experimental result shows the effectiveness of our development in the term of accuracy and processing time

Optimization of Modified Sliding Mode Control for an Electro-Hydraulic Actuator System with Mismatched Disturbance

This paper presents a modified sliding mode controller (MSMC) for tracking purpose of electro-hydraulic actuator system with mismatched disturbance. The main contribution of this study is in attempting to find the optimal tuning of sliding surface parameters in the MSMC using a hybrid algorithm of particle swarm optimization (PSO) and gravitational search algorithms (GSA), in order to produce the best system performance and reduce the chattering effects. In this regard, Sum square error (SSE) has been used as the objective function of the hybrid algorithm. The performance was evaluated based on the tracking error identified between reference input and the system output. In addition, the efficiency of the designed controller was verified within a simulation environment under various values of external disturbances. Upon drawing a comparison of PSOGSA with PSO and GSA alone, it was learnt that the proposed controller MSMC, which had been integrated with PSOGSA was capable of performing more efficiently in trajectory control and was able to reduce the chattering effects of MSMC significantly compared to MSMC-PSO and MSMC-GSA, respectively when the highest external disturbance, 10500N being injected into the system's actuator

Chattering Analysis of an Optimized Sliding Mode Controller for an Electro-Hydraulic Actuator System

Wear and tear are usually caused by various factors, which reduce the life span of a mechanical part. In the control engineering of an Electrohydraulic actuator system, the wear and tear can be caused by the system or the controller itself. This article examines the chattering effect that occurs during the sliding mode controller (SMC) design, and its effect on the nonlinear electrohydraulic actuator (EHA) system. To examine the chattering phenomenon, signum function is first applied on the switching function of the SMC. Then, parameters of the controller are obtained using single objective particle swarm optimization (PSO) method. These parameters are then applied to the switching function with hyperbolic tangent function. Lastly, the performance of both functions is analysed and compared based on graph and numerical data. From the output data, chattering phenomenon generated on the signum function is greatly eliminated by using hyperbolic tangent function

Improved Third Order PID Sliding Mode Controller for Electrohydraulic Actuator Tracking Control

An electrohydraulic actuator (EHA) system is a combination of hydraulic systems and electrical systems which can produce a rapid response, high power-to-weight ratio, and large stiffness. Nevertheless, the EHA system has nonlinear behaviors and modeling uncertainties such as frictions, internal and external leakages, and parametric uncertainties, which lead to significant challenges in controller design for trajectory tracking. Therefore, this paper presents the design of an intelligent adaptive sliding mode proportional integral and derivative (SMCPID) controller, which is the main contribution toward the development of effective control on a third-order model of a double-acting EHA system for trajectory tracking, which significantly reduces chattering under noise disturbance. The sliding mode controller (SMC) is created by utilizing the exponential rule and the Lyapunov theorem to ensure closed-loop stability. The chattering in the SMC controller has been significantly decreased by substituting the modified sigmoid function for the signum function. Particle swarm optimization (PSO) was used to lower the total of absolute errors to adjust the controller. In order to demonstrate the efficacy of the SMCPID controller, the results for trajectory tracking and noise disturbance rejection were compared to those obtained using the proportional integral and derivative (PID), the proportional and derivative (PD), and the sliding mode proportional and derivative (SMCPD) controllers, respectively. In conclusion, the results of the extensive research given have indicated that the SMCPID controller outperforms the PD, PID, and SMCPD controllers in terms of overall performance.

Modeling and controller design of an industrial hydraulic actuator system in the presence of friction and internal leakage

This paper presents a robust controller scheme and its capabilities to control the position tracking performance of an electro-hydraulic actuator system. Sliding mode control with fixed and varying boundary layer is proposed in the scheme. It is aimed to compensate nonlinearities and uncertainties caused by the presence of friction and internal leakage. Its capabilities are verified through simulations in Matlab Simulink environment. The friction was represented by the LuGre model and the internal leakage was assumed to change. The results indicate that the scheme successfully improves the robustness and the tracking accuracy of the system. This improvement offers a significant contribution in the control of modern equipment positioning applications