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... time-domain specifications such as mean error, overshoot percentage, and steady-state error are analyzed and recorded. Table 5 shows the output performance for each case of the combination of weight values using the PID controller parameters in Table 4. ...Context 2
... Table 5, mean errors for all the cases do not show much difference. The mean error for case 1 to case 9 are in between 0.635 3 10 m and 0.908 3 10 m, which are only below 1 millimeter. ...Context 3
... the overshoot percentage, case 2 showed the highest overshoot percentage, which is 1.7057% while case 7 showed the lowest overshoot percentage, which is 0.0362%. Apart from that, case 7 showed a result of 1.081 5 10 m in steady-state error, which is the lowest among all the cases shown in Table 5. Among all the case with different combinations of weight factors in MOPSO, case 7 with the weight factors of 0.7 on a mean error and 0.3 on overshoot is found to be the best combination. ...Context 4
... time-domain specifications such as mean error, overshoot percentage, and steady-state error are analyzed and recorded. Table 5 shows the output performance for each case of the combination of weight values using the PID controller parameters in Table 4. ...Context 5
... Table 5, mean errors for all the cases do not show much difference. The mean error for case 1 to case 9 are in between 0.635 3 10 m and 0.908 3 10 m, which are only below 1 millimeter. ...Context 6
... the overshoot percentage, case 2 showed the highest overshoot percentage, which is 1.7057% while case 7 showed the lowest overshoot percentage, which is 0.0362%. Apart from that, case 7 showed a result of 1.081 5 10 m in steady-state error, which is the lowest among all the cases shown in Table 5. Among all the case with different combinations of weight factors in MOPSO, case 7 with the weight factors of 0.7 on a mean error and 0.3 on overshoot is found to be the best combination. ...Similar publications
Citations
... Simulation and experimental results in this work proves that selection of fractional order integration, α and order of fractional order differentiation, β plays an important role in determining the performance of the proposed FOSMC-PID controller in terms of speed tracking, disturbance rejection and chattering reduction abilities. In future work, optimization algorithm e.g., using PSO should be incorporated into the proposed FOSMC-PID speed controller of PMSM to tune the parameters α and β [26]. Although fractional order sliding mode controller is a promising enhancement, selection of order values is crucial to avoid not only insignificant result, but in worse case, causes deteriorative effects to the system. ...
Fractional order sliding mode control has been applied for speed control of PMSM. However, in many previous works, the effects of the controller's parameters have not been studied. This paper investigates the effects of fractional order on performance of FOSMC speed control of PMSM. In this work, fractional order, α and β of FOSMS-PID were varied, and their performances were compared. The simulation and experimental results show that variation of order of fractional order integration, α and order of fractional order differentiation, β can affect the performance of the FOSMC-PID controller. Selection of α and β values determines balancing strategies between integral and differentiation portion of the controller. Proper value selection and combination of these variables can further contribute to obtain optimum speed tracking, disturbance rejection and chattering reduction abilities.
... Not limited in temperature controlling, Mohd Nadzri Mamat et al., [9] also implement PID feedback control with modified Zeigler-Nichols tuning method in their SEPIC-Boost Converter. Besides, Chai Mau Shern et al., [10] had improved the Particle Swarm Optimization (PSO) by combining the PID controller into the system for positioning control in their proposed Electro-Hydraulic Actuator (EHA) system. ...
The topic of maintaining thermal comfort efficiency in the heating, ventilation and air conditioning (HVAC) sector has always been tricky due to numerous challenges. The study focused on the challenge of under-actuated zones in non – residential and commercial buildings. The active iris damper with the integration of thermal controller is proposed to control the indoor temperature. Besides, integration of PID control strategy will be a tempting control system in enhancing the thermal performance of the building. Again, the PID controller has proven good compatibility as a primary closed-loop mechanism to maintain a comfortable room temperature. The development of the control system is done through the Arduino platform with LabVIEW as the front panel and data logging platform. The Heuristic tuning method was employed to obtain optimal gains for P, PI and PID controllers. The performance of each controller was tested by observing their ability to maintain steadily at the desired temperature set point. These tests conveyed that the best controller for this application is the PID controller. It reached the desired temperature set point and maintained it even with a temperature disruption. This study indicates that an active iris damper can effectively maintain the thermal comfort performance of indoor environment with the implementation of PID strategy, thus remedying some of the problems faced by centralized air-conditioning systems.
