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All Journal Prosiding KOMMIT Buletin Ilmiah Sarjana Teknik Elektro Journal of Soft Computing Exploration
Nia Maharani Raharja
Diploma Teknik Elektro Universitas Gadjah Mada
Computer Science & IT Education Electrical & Electronics Engineering

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MONITORING SISTEM PENGENDALIAN SUHU DAN SALURAN IRIGASI HYDROPONIKPADA GREENHOUSEBERBASISWEB Raharja, Nia Maharani
Prosiding KOMMIT 2012
Publisher : Prosiding KOMMIT

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Abstract

Akhir-akhir ini perkembangan teknologibegitucepat di lapangan. Perkembangan semuabidang salingmendukung.Lapangan yang sangat mendukung kemajuan teknologidanperkembangan mencolok adalah elektronik, terutamapenggunaan elektronik di bidang teknologi industri.Perkembangan mengeser ternyata banyak lahan pertanian, terutama didaerah perkotaan. Sebagai hasil dari lahan pertanian semakin sempit. Di sisi lain permintaan untuk output pertanian meningkat seiring dengan peningkatan populasi. Dengan pertimbangan di atas, kajian ini berupaya untukmenciptakan sebuahsistem yang digunakan untuk pemantauan suhudan kontrol irigasi di Hydroponik rumah kaca dengan PLCyang dapat dipantau dengan menggunakan Web. Hasil penelitian menunjukkan bahwa sistem ini memiliki kemampuan untuk memonitor suhu dan irigasi dan Hydroponik rumah kaca pada PLC bekerja sangat baik
Current trend in control of artificial intelligence for health robotic manipulator Suwarno, Iswanto; Cakan, Abdullah; Raharja, Nia Maharani; Baballe, Muhammad Ahmad; Mahmoud, Magdi S.
Journal of Soft Computing Exploration Vol. 4 No. 1 (2023): March 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v4i1.96

Abstract

The increasing utilization of artificial intelligence and robots in various services in healthcare makes robots as preferred intelligent agent model. Robotic evolution produces the optimal robotic innovation in the robotic system or its subsystems, morphology, kinematics, and control. An intelligent algorithm is programmed into the control of the robotic manipulator. This paper aims to identify the control of artificial intelligence and identify comparisons of artificial intelligence algorithms control for healthcare robotic manipulators. This study uses a systematic literature review using the Preferred Reporting Items for Systematic Review (PRISMA). The potential for further articles is explored related to the theme of the research carried out. The conclusion obtained many studies have been carried out to optimize the work and tasks of the robotic arm manipulator, specifically developing various types of manipulator control (algorithms) combined with neural networks to get the right and appropriate algorithm.
Induction Motor Speed Control Using PID Tuned by Particle Swarm Optimization Under Vector Control Maghfiroh, Hari; Sulistyo, Meiyanto Eko; Ma’arif, Alfian; Raharja, Nia Maharani; Suwarno, Iswanto; Wati, Dwi Ana Ratna; Baballe, Muhammad Ahmad
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 2 (2025): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i2.13112

Abstract

Induction motors (IMs) are widely used in industrial applications due to their cost-effectiveness, durability, and low maintenance requirements. This study investigates the speed control of an induction motor using vector control combined with a PID controller whose parameters are tuned via Particle Swarm Optimization (PID-PSO). A reduced-order small-signal state-space model is derived from a detailed nonlinear IM model to facilitate efficient controller tuning while maintaining fidelity to real-world behavior. The PID parameters are optimized using PSO, with the Integral of Absolute Error (IAE) selected as the objective function due to its ability to penalize long-duration deviations and reflect steady-state performance. The optimized PID controller is then validated on the full nonlinear IM model under speed and load variations. Simulation results demonstrate that PID-PSO significantly outperforms manually tuned PID control in terms of tracking accuracy, reducing IAE by 37.79% and 14.76% under speed and load variation conditions, respectively. However, this improvement comes at the cost of slightly slower settling time. These results highlight a trade-off between accuracy and transient response, motivating future research on multi-objective optimization to balance conflicting criteria such as robustness, energy efficiency, and response time.
Co-Authors Alfian Ma’arif Baballe, Muhammad Ahmad Cakan, Abdullah Dwi Ana Ratna Wati Maghfiroh, Hari Mahmoud, Magdi S. Meiyanto Eko Sulistyo Suwarno, Iswanto