Tuning cascade PI(D) controllers in PMDC motor drives: A performance comparison for different types of tuning methods

Gücin, Taha Nurettin; Biberoğlu, Muhammet; Fincan, Bekir; Gülbahçe, Mehmet Onur

doi:10.1109/eleco.2015.7394556

Cited by 16 publications

(12 citation statements)

References 8 publications

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“…Fig. 16 presents comparative results of a servo drive system with classical cascade control structure [24], [25] and MTSC. The cascade control consists of proportional controller in the position control loop and proportional-integral controllers in speed and current control loops.…”

Section: Comparison To the Classical Methodsmentioning

confidence: 99%

Imposing Constraints in a Full State Feedback System Using Multithreaded Controller

Michalczuk

Ufnalski

Grzesiak

2021

IEEE Trans. Ind. Electron.

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Section: Comparison To the Classical Methodsmentioning

confidence: 99%

Imposing Constraints in a Full State Feedback System Using Multithreaded Controller

Michalczuk

Ufnalski

Grzesiak

2021

IEEE Trans. Ind. Electron.

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“…Table 1 The PMDC Parameters [9] To simplify the system, it has been assumed that the input signal is the same for both motors, so the synchronization error becomes zero between them, and because the two motors have the same parameters, so the cascade control system can be simplified as follows: -…”

Section: The General Structure Of the Systemmentioning

confidence: 99%

“…This cascade controller consists of three controllers, the first for position control, the second for velocity control, and the third for current control where the current controller is designed as an inner loop, and both position and velocity are outer controllers [8] . P, PI, and PI controllers are used instead of a PID controller for the position, velocity, and current respectively [9] . The main reason for using the cascade controller is to reduce or reject disturbances to return the system to a steadystate [10 -12].…”

Section: Introductionmentioning

confidence: 99%

Position - Velocity Control for Two PMDC Motors Connected by a Cross-Coupling Technique with Butterflies Optimization Algorithm

Abdulhussein

Yasin

Hasan

2021

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In this paper, two contributions are presented. the first is to design two cascade controllers to control the velocity and position for two Permanent Magnet DC motors (PMDC) working together at the same time for use in many applications such as CNC machines, robotics, and others. Furthermore, the cross-coupling technique is used to connect these motors and adjust the precise synchronization of their movement on the axes. The second contribution is the use of the butterfly’s optimization algorithm (BOA) with the objective function Integral Time Absolute Error (ITAE) to extract the optimal parameter values for the two cascade controllers and the synchronization controller in order to obtain the best accurate results. The simulation results showed high accuracy to reach the desired position at a regular velocity of both the PMDC motors with accurate synchronization and tracking trajectory on the axes. In addition, a very small position deviation of 0.021 rad was observed, and the system returned to a steady-state after 2 seconds of applying the full load.

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“…The cascade P-PI controller used in this paper consists of three controllers: the current controller as an inner loop, the speed controller, and the position controller as outer loops [8]. P, PI, and PI controllers are used for position, speed, and current respectively [9].…”

Section: Introductionmentioning

confidence: 99%

Comparison of cascade P-PI controller tuning methods for PMDC motor based on intelligence techniques

Abdulhussein

Yasin

Hasan

2022

IJECE

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In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.

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Tuning cascade PI(D) controllers in PMDC motor drives: A performance comparison for different types of tuning methods

Cited by 16 publications

References 8 publications

Imposing Constraints in a Full State Feedback System Using Multithreaded Controller

Imposing Constraints in a Full State Feedback System Using Multithreaded Controller

Position - Velocity Control for Two PMDC Motors Connected by a Cross-Coupling Technique with Butterflies Optimization Algorithm

Comparison of cascade P-PI controller tuning methods for PMDC motor based on intelligence techniques

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