Hashimah Ismail

Self-tuning fuzzy PID controller for electro-hydraulic cylinder

Hydraulic systems are widely used in industrial applications. This is due to its high speed of response with fast start, stop and speed reversal possible. The torque to inertia ratio is also large with resulting high acceleration capability. The nonlinear properties of hydraulic cylinder make the position tracking control design challenging. This paper presents the development and implementation of self-tuning fuzzy PID controller in controlling the position variation of electro-hydraulic actuator. The hydraulic system mathematical model is approximated using system identification technique. The simulation studies were done using Matlab Simulink environment. The output performance was compared with the design using pole-placement controller. The roots mean squared error for both techniques showed that self-tuning Fuzzy PID produced better result compared to using pole-placement controller.

Optimized PID control using Nelder-Mead method for electro-hydraulic actuator systems

Despite the application of advanced control technique to improve the performance of electro-hydraulic position control, PID control scheme seems able to produce satisfactory result. PID is preferable in industrial applications because it is simple and robust. The main problem in its application is to tune the parameters to its optimum values. This study will look into an optimization of PID parameters using Nelder-Mead approach for electro-hydraulic position control system. The electro-hydraulic system was represented by an ARX model structure obtained through MATLAB System Identification Toolbox. Second-order and third-order model of the system had been evaluated. Simulation and real-time studies show that ARX211 produced the best response in terms of transient speed and RMSE performance criteria even though the model has the least percentage of best fit.

Tracking control for electro-hydraulic actuator using ZPETC

Hydraulic actuator is widely used in industrial applications because it exhibits linear movements, fast response, smooth reversal and accurate positioning of heavy load. The torque to inertia ratio is also large which resulting high acceleration capability. Reducing the position tracking error of the hydraulic system is a very challenging task. This paper presents the development and implementation of Zero Phase Error Tracking Control (ZPETC) in controlling the position variation of electro-hydraulic actuator. The electro-hydraulic system mathematical model was approximated using system identification technique with non-minimum phase system being considered. The studies were done using Matlab Simulink environment. The simulated tracking performance was validated with the real-time system. The tracking root mean squared error for real-time system was slightly higher than the simulation due to plant-model mismatch. Both results provide good performances in tracking control.

PI-Fuzzy Logic Control for 3 Phase BLDC Motor for Electric Vehicle Application

Brushless DC motor has been widely used in electric vehicle because of its high performance and simplicity. However this motor is a multi-variable, non-linear system and easily can be influenced by the parameter variations and disturbances. The conventional controllers are unable to handle this problem. To overcome this problem a nonlinear PI-fuzzy logic controller is used to control the speed of electric vehicle traction motor. The development of this control strategy is presented in this paper. The proposed controller has simple structure and also due to its modest fuzzy rule in rulebase is relatively easy for implementation. The control is performed by Matlab/Simulink software. The simulation test results have been satisfactory in both steady and transient states. This controller has high accuracy, suitable performance, high robustness and high tracking efficiency.

Positioning and Tracking Control of an XY table

Position tracking accuracy of XY table is important for precise operations in manufacturing field. On the basis of minimizing the tracking error, a linear digital tracking control system is considered. Error Filter Feedforward Zero Phase Error Tracking Control (ZPETC) is designed and used in this system. The controller is used as it has the ability to give good performance in high speed frequency. The system transfer function is obtained via system identification technique using Matlab Toolbox. The performance of the controller in reducing the tracking error using high frequency input is analyzed through simulation. The system is also tested by implementing conventional feedforward controller for comparison purposes. Both controller performances are compared and the result shows tremendous tracking performance.

Model identification and real-time linear position control of servomotor

Plant model identification using experimental data is easy to be obtained with modern tools software such as Matlab and LabView. This powerful software provides reliable and approximate model structure. This paper presents model identification using Matlab System Identification Toolbox from open-loop input-output experimental data that obtained from linear position of a DC servo motor. The effectiveness of the proposed model was tested by a closed loop controller using pole-placement method. Simulation and real time control were conducted to show the reliability of the obtained model. The result shows acceptable performances in both simulation and real time studies.

Optimal light power consumption using LDR sensor

High demand of electrical power receives challenging feedback due to the lack of natural resources and high impact of the global warming. This paper describes one applicable method to optimize the electrical power consumption using Light Dependent Resistor (LDR) sensor. A simple adjuster based on the sensor reading was developed and tested to one small room with two Light Emitting Diode (LED). Two LDR sensors to measure and analyze the surroundings light intensity were allocated for one LED bulb. The LDR sensors interface with each other, and the necessary intensity required by the bulb will be calculated and the bulbs will provide the required lumen for the surrounding/workspace. This system is tested during the day time. The output would affected by surroundings light sources. Hence, the LED bulbs light intensity will be reduced causing a directly proportional effect to the power consumption. This system can provide optimized light intensity for the surrounding and reduces the electrical power consumption during daytime.

Model reference input for an optimal PID tuning using PSO

Optimization of PID parameters had been a popular issue among academia and industrial players. This is because it is undoubtedly a simple and robust controller for most applications. Recently, many intelligent approaches using optimization techniques had emerged in trying to propose an efficient way of finding the optimal setting for the PID. Among all is using Particle Swarm Optimization (PSO). The PSO was utilized to search for optimum Kp, Ki and Kd that will minimized some objective functions typically IAE and ITSE. These objective functions will manage to find the optimal PID setting in terms of error elimination but yet they cannot guarantee satisfaction in transient response requirements in specific. This research proposed a new approach in PID optimization by introducing a model reference that represents the actual desired response of the controlled variable. This approach will satisfy not only error elimination, but specific transient requirements can be fulfilled perfectly. PSO was applied to find the PID setting by minimizing the error between model reference and process output signal. This paper presents simulation results using MATLAB Simulink to demonstrate the effectiveness of using model reference over step reference input alone. The proposed method was found to be superior in terms of accuracy and consistency in the results over using a step response reference signal alone.

Real-time application of self-tuning PID in electro-hydraulic actuator

Hydraulic actuators are characterized by their ability to impart large forces at high speeds and are used in many industrial motion systems. The nonlinear properties of hydraulic cylinder had challenged researchers to design a suitable controller for position control, motion control and tracking control. This paper presents the development and implementation of self-tuning fuzzy PID controller in controlling the position variation of electro-hydraulic actuator. The electro-hydraulic system was represented by an ARX model structure obtained through MATLAB System Identification Toolbox. Then, by experiment on a practical electro-hydraulic actuator test-bed, the effectiveness of this control scheme is verified through comparison with simulation using Matlab Simulink environment. The research results show that the self-tuning fuzzy PID controller has good performance based on RMSE index.

Adaptive feedforward zero phase error tracking control with model reference for high precision X-Y table

Position tracking accuracy of XY table is important for precise operations in manufacturing field. To achieve good performance for high speed and precision, adaptive feedforward using ZPETC is proposed. In this paper, the technique is improved by introducing Model Reference into the system. The reference model tells how the process output ideally should respond to the command signal. The system transfer functions of X and Y axis are obtained via system identification technique using Matlab Toolbox. The performance of the controller in reducing the tracking error using high frequency input is analyzed through simulation. The system is also tested by implementing the adaptive controller without model reference for comparison purposes. Both controller performances are compared and the result shows tremendous superior tracking performance.