Analisis Bibliometrik Riset PID Speed Control pada Rentang 2013-2022

Penelitian ini bertujuan untuk memberikan gambaran terkait perkembangan riset PID speed control dalam satu dekade terakhir (2013-2022). Metode yang digunakan dalam artikel ini adalah analisis bibliometrik dengan menggunakan VOSviewer, Tableau Public dan Rstudio Biblioshiny. Database yang digunakan adalah Scopus. Dengan kata kunci pencarian “PI* speed control*”, diperoleh 258 dokumen publikasi yang terdiri dari 105 artikel jurnal dan 153 artikel prosiding yang menjadi dataset utama yang digunakan dalam artikel ini. Dari hasil analisis terlihat bahwa jumlah publikasi riset PID speed control berfluktuasi setiap tahunnya. Top 10 dokumen dengan jumlah sitasi terbanyak juga dibahas dalam artikel ini. Author paling produktif dan author paling berpengaruh dalam riset PID speed control terungkap yaitu Verma, A dan Choi, H.H. Topik yang sedang tren dan menjadi hotspot dalam riset PID speed control adalah particle swarm optimization, direct torque control, extended Kalman filter, current predictive control, sliding mode control, model predictive control dan disturbance observer. Akhirnya, artikel ini dapat memberikan informasi yang bermanfaat bagi para peneliti empiris untuk menentukan kebaruan dan research gap untuk penelitian selanjutnya dalam tema utama PID speed control

Optimal tuning proportional integral derivative controller on direct current motor using reptile search algorithm

This paper presents the reptile search algorithm (RSA) method to optimize the proportional integral derivative (PID) parameters on direct current (DC) motors. RSA was adopted from crocodile hunting behavior. Crocodile behavior is modeled in two important steps: surrounding and attacking prey. The RSA method was applied using twenty-three classical test functions. The search method of the proposed RSA method with other existing algorithms such as particle swarm optimization (PSO), and differential evolution (DE). Integral multiplied by absolute error (ITAE) and integral of time multiplied squared error (ITSE) were used as comparisons in measuring the performance of the RSA method. The results show that the proposed method, namely RSA, has better efficiency. Optimization of PID parameters with RSA on DC motor control shows superior performance. From the experiment, the ITSE average value of the RSA method is 4.17% better than the conventional PID method

A comparative real-time speed control of PMSM with Fuzzy Logic and ANN based vector controller

This paper presents, analyzed real-time speed control of Permanent Magnet Synchronous Motor (PMSM) under constant load by using Fuzzy Logic (FL) controller and recurrent Artificial Neural Network (ANN) controller. A closed loop PMSM drive system is improved using the mathematical model of the PMSM in Matlab / Simulink. Two types of controllers are used; the first controller is the real-time FL controller and the second controller is a real-time recurrent ANN controller in terms of smoother speed response. Whole drive systems is simulated in Matlab/Simulink program. The simulation results show that the focused ANN controller produce considerable control performance compare to the FL controller on controlling speed reference variation

Modeling and fuzzy FOPID controller tuned by PSO for pneumatic positioning system

A pneumatic cylinder system is believed to be extremely nonlinear and sensitive to nonlinearities, which makes it challenging to establish precise position control of the actuator. The current research is aimed at reducing the overshoot in the response of a double-acting pneumatic actuator, namely, the IPA positioning system’s reaction time. The pneumatic system was modeled using an autoregressive with exogenous input (ARX) model structure, and the control strategy was implemented using a fuzzy fractional order proportional integral derivative (fuzzy FOPID) employing the particle swarm optimization (PSO) algorithm. This approach was used to determine the optimal controller parameters. A comparison study has been conducted to prove the advantages of utilizing a PSO fuzzy FOPID controller over PSO fuzzy PID. The controller tuning algorithm was validated and tested using a pneumatic actuator system in both simulation and real environments. From the standpoint of time-domain performance metrics, such as rising time (tr), settling time (ts), and overshoot (OS%), the PSO fuzzy FOPID controller outperforms the PSO Fuzzy PID controller in terms of dynamic performance

Evolutionary swarm algorithm for modelling and control of horizontal flexible plate structures

Numerous advantages offered by the horizontal flexible structure have attracted increasing industrial applications in many engineering fields particularly in the airport baggage conveyor system, micro hand surgery and semiconductor manufacturing industry. Nevertheless, the horizontal flexible structure is often subjected to disturbance forces as vibration is easily induced in the system. The vibration reduces the performance of the system, thus leading to the structure failure when excessive stress and noise prevail. Following this, it is crucial to minimize unwanted vibration so that the effectiveness and the lifetime of the structure can be preserved. In this thesis, an intelligent proportional-integral-derivative (PID) controller has been developed for vibration suppression of a horizontal flexible plate structure. Initially, a flexible plate experimental rig was designed and fabricated with all clamped edges boundary conditions at horizontal position. Then, the data acquisition and instrumentation systems were integrated into the experimental rig. Several experimental procedures were conducted to acquire the input-output vibration data of the system. Next, the dynamics of the system was modeled using linear auto regressive with exogenous, which is optimized with three types of evolutionary swarm algorithm, namely, the particle swarm optimization (PSO), artificial bee colony (ABC) and bat algorithm (BAT) model structure. Their effectiveness was then validated using mean squared error, correlation tests and pole zero diagram stability. Results showed that the PSO algorithm has superior performance compared to the other algorithms in modeling the system by achieving lowest mean squared error of 6103947.4 , correlation of up to 95 % confidence level and good stability. Next, five types of PID based controllers were chosen to suppress the unwanted vibration, namely, PID-Ziegler Nichols (ZN), PID-PSO, PID-ABC, Fuzzy-PID and PID-Iterative Learning Algorithm (ILA). The robustness of the controllers was validated by exerting different types of disturbances on the system. Amongst all controllers, the simulation results showed that PID tuned by ABC outperformed other controllers with 47.60 dB of attenuation level at the first mode (the dominant mode) of vibration, which is equivalent to 45.99 % of reduction in vibration amplitude. By implementing the controllers experimentally, the superiority of PID-ABC based controller was further verified by achieving an attenuation of 23.83 dB at the first mode of vibration and 21.62 % of reduction in vibration amplitude. This research proved that the PID controller tuned by ABC is superior compared to other tuning algorithms for vibration suppression of the horizontal flexible plate structure