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.

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%