Metaheuristic optimization approach has become the new framework for control synthesis. The main purposed of the control design are input (command) tracking and load (disturbance) regulating. This research proposes an optimal proportional-derivative (PID) controller design for the brushless dc (BLDC) motor speed control system with input tracking and load regulating constrained optimization by using the cuckoo search (CuS) one of the most efficient population-based metaheuristic optimization techniques. The sum-squared error between population-based metaheuristic optimization techniques. The sum-squared error between the referent input and the controlled output is set as the objective function to be minimized. The rise time the maximum overshoot settling time and steady-state error are set as inequality constraints for tracking purpose while the regulating time and the maximum overshoot of load regulation are set as inequality constraints for regulating purpose. Results obtained by the CuS will be compared with those obtained by the particle swarm optimization (PSO) and genetic algorithm (GA). From simulation results it was found that the parameters of CuS were optimal than both PSO and GA for BLDC motor speed control system satisfying the preset input tracking and load regulating constraints. In addition the simulation results are confirmed by the experimental ones from the BLDC motor speed control system developed in the laboratory.

The objective of this paper is to construct the solar car prototype. The car uses flexible solar panels with the battery as a power source. Thereafter the performance of the solar car is tested in the actual condition. This solar car’s body was developed by fiberglass and the internal structure was made from the steel. This car uses the 2 kW brushless DC motor to be the prime mover and the motor is driven by the regenerative dc converter. The power sources are 480 watts of the flexible solar panel with a charger to charge power to four of 12V 33Ah battery. The total weight of the solar car is 173 kg. The solar car’s weight including driver is about 233.4 kg. The solar car test drive is on 10 km distance. The result found that the car has: (1) the average speed is equal to 45.98km/h by using only battery (2) the average speed is equal to 51 km/h when the battery is combined with solar panels. This knowledge should be applied to develop the next version of the solar racing car.

This thesis aims to study the optimization of the supply fuel system of pipeline by improving the pumps system from use pump size 1850 kW (2 pupms) and use only control valve. We design new system by use pump size 1850 kW (2 pumps) with variable speed motors (VSD). In this way we can control stability of opening and closing of the valve at 100% and use adjusting of the frequency of VSD as follow typing of fuel. To analysing of efficiency system we will use fuel 4 type that have different coefficient of density are JET A1 Disel B91 and B95. And then we compared the relationship between the quantity of each fuel per time and usage of power for the old system and new design that we found the new design as analyze the result and as follow the theory of Affinity Law have the value of efficacy more than. And it also can save energy cost to 52.13%

This research is to study and develop a DC motor speed control by using Visual Basic.Net 2008 in computer programming to use the computer and the microcontroller is processing from computer via the serial port. So that a signal to the motor driver circuit motor speed work as assigned. By the speed can be entered via the computer screen is measured in rpm. and motor control to control the PWM (Pulse Width Modulation) control circuit and the principles of the hardware by using the digital output signal of the microcontroller control Motor speed can be configured to be from 100 to 3000 rpm. And the motor starts to spin at maximum speed and then gradually reduce the speed down to the specified value. Control both the speed and the average error of 4.6% compared to the speed measurement using infrared light. And found that at speeds below 100 rpm. to a maximum error of 12% and the error decreases when the speed increases. The error value is at least 2000 rpm. and 3000 rpm the speed error is 0.5%