Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Fuzzy controller


Study the Robustness of Automatic Voltage Regulator for Synchronous Generator Based on Neuro-Fuzzy Network

Abdulrahim Thiab Humod; Yasir Thaier Haider

Engineering and Technology Journal, 2015, Volume 33, Issue 3, Pages 612-627

Modern power systems are complex and non-li¬near and their operating conditions can vary over a wide range, and since neuro - fuzzy networkcan be used as intelligent controllers to control non-li¬near dynamic systems through learning, which can easily accommodate the non-linearity, time dependencies, model uncertainty and external disturbances.ANeuro-Fuzzy model system is proposed as an effective neural network controller model to achieve the desired robust Automatic Voltage Regulator (AVR) for Synchronous Generator (SG) to maintain constant terminal voltage. TheconcernedNeuro-fuzzy controller for AVRis examined on different models of SG andloads. The results show that the Neuro-Fuzzy -controllers have excellent responses for all SG models and loads in the view point of transientresponse and system stability compared with optimal PID controllers tuned by practical swarm optimization.They also show that the margins of robustness for Neuro-Fuzzy -controller aregreater thanPID controller.

Fuzzy logic Control of Chemical Processes

Duraid Fadhil Ahmed

Engineering and Technology Journal, 2015, Volume 33, Issue 1, Pages 12-29

The objective of this study was to investigate the closed-loop control strategies for a batch reactor and batch distillation column by using two different control methods. In this paper, Fuzzy logic control is developed and compared with conventional proportional-/integral-derivative controller. In the design of fuzzy controller, the knowledge obtained from the process reaction curve procedure is employed to determine proper membership functions. Fine tuning is obtained alteration the output scaling factor. The forty nine rules are employed to regulate the manipulating variables to a variety of operating conditions and acquire a more flexible learning ability. The robustness of this control structure is studied in the case of set point changes and the fitness function for fuzzy controller is chosen as the integral of the absolute value of the error (IAE). The experimental results suggest that such fuzzy controllers can provide excellent set point-tracking and disturbance rejection. The results show that the fuzzy logic controller has a higher performance, in terms of robustness, response speed and the offset has a smaller average value than that of the conventional controller. According to experimental results, the fuzzy controller was considered more suitable and reliable for the batch reactor and distillation processes control with respect to the conventional controller.

Modeling and Force-Position Controller Design of Rehabilitation Robot for Human Arm Movements

Mohammed Y. Hassan; Zeyad A. Karam

Engineering and Technology Journal, 2014, Volume 32, Issue 8, Pages 2079-2095

Physical disabilities such as full or partial loss of function in the shoulder, elbow or wrist is a common impairment in the elderly, and can also be a secondary effect due to strokes, trauma, sports injuries, and occupational injuries. Rehabilitation programs are the main method to promote functional recovery in these subjects.
This work focuses on designing and nonlinear modeling of 3DOF non-wearable rehabilitation robot for rehabilitee the upper limbs in human body. The structure of this robot will eliminate singularity problem by depending on articulated configuration through adding shoulder offset to the robot base. The nonlinear modeling of a rehabilitation robot including kinematic and dynamic models is done for three degrees of freedom, with the effect of friction term in robot actuator.
Three Intelligent Force-Position controllers, PD-like Fuzzy logic controllers are designed for position control and P controllers for force control, for moving the shoulder and elbow joints of the rehabilitation robot at desired trajectories. These controllers were tuned in order to make the robot end effecter tracking the desired medical trajectories in a specific time with minimum overshoot, minimum settling time and minimum steady state error. Each controller is tested by applying different trajectories with the application of external disturbances on the robot body.
A comparison between the proposed intelligent controllers and conventional PD Force-Position controllers shows superior of the intelligent type of controller to make the end effecter follow the desired trajectory compared with the use of conventional controllers.