The design of intelligent control systems has become an area of intense research interest. The development of an effective methodology for the design of such control systems undoubtedly requires the synthesis of many concepts from artificial intelligence. The most commonly used controller in the industry field is the proportional-plus-integral-plus-derivative (PID) controller. Fuzzy logic controller (FLC) provides an alternative to PID controller, especially when the available system models are inexact or unavailable. Also rapid advances in digital technologies have given designers the option of implementing controllers using Field Programmable Gate Array (FPGA) which depends on parallel programming. This method has many advantages over classical microprocessors. In this research, A model of the fuzzy PID control system is implemented in real time with a Xilinx FPGA (Spartan-3A, Xilinx Company, 2007). It is introduced to maintain a constant speed to when the load varies. The model of a DC motor is considered as a second order system with load variation as an example for complex model systems. For comparison purpose, two widely used controllers "PID and Fuzzy" have been implemented in the same FPGA card to examine the performance of the proposed system. These controllers have been tested using Matlab/Simulink program under speed and load variation conditions. The controllers were implemented to run the motor as real time application under speed and load variation conditions and showed the superiority of Fuzzy-PID.

The output power produced by high-concentration solar thermal and photovoltaic systems is directly related to the amount of solar energy acquired by the System, and it is therefore necessary to track the sun's position with a high degree of accuracy. This paper presents sun tracking generating power system designed and implemented in real time. A tracking mechanism composed of photovoltaic module, stepper motor ,sensors, input/output interface and expert FLC implemented on FPGA, that to track the sun and keep the solar cells always face the sun in most of the day time. The proposed sun tracking fuzzy controller has been tested using Matlab/Simulink program; the simulation results verify the effectiveness of the proposed controller and shows an excellent result.

Proper control for low energy buildings is more difficult than conventional buildings due to their complexity and sensitivity to operating conditions. In this paper, Adaptive Hierarchical Fuzzy control is used to control Heating, Ventilating and Air Conditioning (HVAC) System which is time varying nonlinear system. The proposed Controller is capable of maintaining comfort conditions under time varying thermal loads. Adaptive Hierarchical Fuzzy is consist of two levels; first fuzzy level is to control (Air temperature and Air quality); the second fuzzy level is to control the Error and Change of Error that comes from first level. A hierarchical structure is used to reduce the number of rules, trim redundant information and reduce the computing time required for the optimization. The controller is developed using a computer simulation of a virtual building contains most parameters of a real building. Fuzzy rules are learned from experts and system performance observations. Matlab program is used to simulate HVAC system and to see the results of the new controller.

Abstract-Virtual instrumentation is defined as the combination of measurement and control hardware and application software with industry-standard computer technology to create user-defined instrumentation systems. This paper presents a real-time application of Ball and Beam controlled by PID controller designed based on LabVIEW program and the real -time position control of the DC motor was realized by using DAQ device. Ball and Beam is a common feedback control system application, due mostly to its ease in construction and its use in learning. Using Labview makes the application very useful for teaching and training students in data conversion domain. The system includes a ball, a beam, a motor and several sensors. The basic idea is to use the torque generated from a motor to control the position of the ball on the beam. The mathematical model for this system is inherently nonlinear, so linearization was done in order to improve the controllability of the system. Data acquisition, signal processing and analyzing can be completed by virtual instrument based on LabVIEW.

this paper presents a fuzzy controller design for nonlinear system using FPGA. A magnetic levitation system is considered as a case study and the fuzzy controller is designed to keep a magnetic object suspended in the air counteracting the weight of the object. Fuzzy controller will be implemented using FPGA chip. The design will use a high-level programming language HDL for implementing the fuzzy logic controller using the Xfuzzy tools to implement the fuzzy logic controller into HDL code. This paper, advocates a novel approach to implement the fuzzy logic controller for magnetic ball levitation system by using FPGA.

No abstract

The new method of proportional-integral-derivative (PID) controller is proposed in this paper for a hybrid fuzzy PID controller for nonlinear system. The important feature of the proposed approach is that it combines the fuzzy gain scheduling method and a fuzzy fed PID controller to solve the nonlinear control problem. The resultant fuzzy rule base of the proposed controller contains one part. This single part of the rules uses the TakagiSugeno method for solving the nonlinear problem. The simulation results of a nonlinear system show that the performance of a fed PID Hybrid Takagi-Sugeno fuzzy controller is better than that of the conventional fuzzy PID controller or Hybrid Mamdani fuzzy FED PID controller.

No abstract