## Speed control of dc motor using fuzzy logic thesis - 2237810

Mohamad, “Speed Control of Separately Excited DC Motor using Fuzzy Neural Model Reference Controller”, International Journal of Instrumentation and Control Systems (IJICS), vol.

competing with DC motor system due to their In developing this project, Programmable Logic Controller (PLC) ladder .Pang-Pang control method is used for switching on or off power to dc motor (armature Fuzzy logic microcontroller implementation for DC motor speed control of a separately excited DC motor using programmable logic controller (PLC) is presented.

## Neuro-Fuzzy DC Motor Speed Control Using Particle …

Faculty of Electrical .Speed Control of DC Motor by Programmable Logic Control with High Accuracy the PID controller is designed to control Motor Speed speed of DC motor by using.

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The controllersof the speed that are conceived for goal to control the speed of DC motor toexecute one variety of tasks, is of several conventional and numeric controllertypes, the controllers can be: PID Controller, Fuzzy Logic Controller; or thecombination between them Fuzzy-Genetic Algorithm, Fuzzy-Neural Networks,Fuzzy-Ants Colony, Fuzzy-Swarm (Swarm).

## Modeling and control of a brushless DC motor - ethesis

Secondly, anadaptive Neuro-Fuzzy controller of the DC motor speed is then designed andsimulated; the ANFIS has the advantage of expert knowledge of the Fuzzyinference system and the learning capability of neural networks.

## PMBLDC motor drive simulated using ..

The rising time of DCmotor speed step is less important in using neural networks (ANFIS) compared with FLC alone and it’s have the minimalvalue in The ANFIS controller with PSO (ANFIS-Swarm).

## control of a brushless DC motor

Fuzzy Logic Control (FLC) is suitable for a controller design when the system is difficult to model mathematically due to its complexity, nonlinearity and imprecision. It is widely used in high performance drives to obtain precise speed control irrespective of load disturbances and parameter variations. The purpose of this project is to investigate and evaluate speed performance of the FLC in vector controlled Sinusoidal Permanent Magnet Synchronous Motor (SPMSM) drives. The SPMSM is controlled by a vector control technique operating like a separately excited DC motor. The mathematical model of SPMSM drives is simulated using the MATLAB Simulink program. The standard FLC which comprise of 49 rules is initially designed based on common criteria. From investigation on the FLC tuning, two simplified FLCs are designed based on fuzzy rules reduction with systematic and reasonable approaches. The efficacies of the FLC simplification are determined by conducting a comparative analysis between standard FLC and simplified FLCs over a wide range of operating conditions. This is based on simulation approach including various initial step speed commands, load disturbance, step reduction in speed command, inertia variations, and speed reversal operation. The FLCs are developed using the Fuzzy Logic Toolbox in MATLAB. The simulation results show that the simplified FLCs obtain comparable performance with the standard FLC in some cases while in others, they perform better than the standard FLC. The simulation results are further evaluated by an experimental investigation. The FLC, co-ordinate transformation and hysteresis current controllers are implemented in the software using Simulink, Fuzzy logic Toolbox and Real-time interface. The hardware implementation consisting of digital signal processor, voltage source inverter, resolver-to-linear DC converter, current sensors and SPMSM are equipped with a speed resolver. As a result, the simplified FLCs are capable to obtain high performance standards with simple rules, less complex structure, less computation time besides solving the limitation of processor and memory resources.

## Whereas speed can be varied using ..

In the fuzzy logic DC motor control, the optimization ofmembership functions and rules became very necessary, it’s important shown inthe minimal rising time of speed response, so the membership functions areadjusted in optimal values to give a steady state error speed value equal zero.