One of the modified versions of the PID controller is the I-PD controller. It was proposed for eliminating the proportional and derivative kick appeared during set point change. In this paper, the optimal I-PD controller design for DC motor speed control system by the adaptive tabu search (ATS), one of the most efficient metaheuristic optimization techniques, is proposed. In a control system, DC motor is the principle and it is widely used because of the power from existing direct-current lighting power distribution systems. It can be controlled over a wide range and a variable supply. In this research, TMS320F28335 DSP microcontroller is implemented for DC motor speed control. This processor consists of the several peripheral circuits for motor drive application such as analog to digital, encoder digital to analog and PWM input/output interface circuits. These interface circuits can be used in both of DC and AC motor controls. For the control algorithm development and the Code Composer Studio (CCS) compiler can be used together with TMS320F28335 DSP in MATLAB/SIMULINK. This proposed method is tested with the DC motor, 1260, 1400, 1540 rpm and 24 volts, consecutively to verify the performance of the I-PD controller designed for DC motor speed control system using the speed and control signal response to many load disturbances. The simulation of DC motor is based on MATLAB/SIMULINK. The implementation results are compared with the simulation results. The correlation in the experiment shows that they are high related. In this paper show the effectiveness of the proposed methods and discuss how they could generalize to other systems by the simulation and experimentation. The results show that the I-PD parameters can be optimized by the ATS. The controlled system with I-PD provides better responses once compared to that with a basic parallel PID controller.

The intelligent control system design has been changed from the conventional approach to the optimization framework solved by efficient metaheuristics. The intensified current search (ICS) has been recently proposed as one of the most powerful metaheuristics for solving optimization problems. The ICS, the latest modified version of the conventional current search (CS), possesses the memory list (ML) regarded as the exploration strategy and the adaptive radius (AR) and adaptive neighborhood (AN) mechanisms regarded as the exploitation strategy. The ML is used to escape from local entrapment caused by any local solution, while both AR and AN mechanisms are conducted to speed up the search process. In this paper, the application of the ICS to multiobjective PID controller design optimization for the three-phase induction motor (3-IM) speed control system is proposed. Algorithms of the ICS and its performance evaluation against multiobjective functions are presented. As simulation results, the ICS can provide very satisfactory solutions for all test functions and the 3-IM control application. Moreover, the simulation results of motor control application are confirmed by the experimental results based on dSPACE technology.

The multipath adaptive tabu search (MATS) has been proposed as one of the most powerful metaheuristic optimization search techniques for solving the combinatorial and continuous optimization problems. The MATS employing the adaptive tabu search (ATS) as the search core has been proved and applied to various real-world engineering problems in single objective optimization manner. However, many design problems in engineering are typically multiobjective under complex nonlinear constraints. In this paper, the multiobjective multipath adaptive tabu search (mMATS) is proposed. The mMATS is validated against a set of multiobjective test functions, and then applied to design an optimal PID controller of the automatic voltage regulator (AVR) system. As results, the mMATS can provide very satisfactory solutions for all test functions as well as the control application.