DC Motor Angular Speed Controller Using an Embedded Microcontroller-Based PID Controller
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This research presents the implementation of a Proportional Integral Derivative (PID) controller to control the angular speed of a Direct Current (DC) motor using an embedded system (microcontroller). The system’s hardware consists of an Arduino microcontroller, a DC motor with an encoder sensor, a driver motor, and a power supply. Proportional control regulates the response proportionally to the calculated error, while integral control manages the cumulative error over time, and derivative control responds to the rate of change of the error, preventing overshoot. With a proper combination, PID control achieves stability, speeds up response, and reduces overshoot, improving overall system performance. Based on experimental data, the DC motor angular speed control system using PID control achieves the best results, in which the parameter values are Kp=1; Ki=0.3; and Kd=0.6. The augmented system responded with 0.0890 seconds of the rise time, 11.772 seconds of settling time, and 0.12 seconds of the peak time, with an overshoot of less than 10% (7%).
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[1] Mohanraj, D., Aruldavid, R., Verma, R., Sathiyasekar, K., Barnawi, A. B., Chokkalingam, B., & Mihet-Popa, L. (2022). A Review of BLDC Motor: State of Art, Advanced Control Techniques, and Applications. IEEE Access, 10, 54833–54869. doi:10.1109/ACCESS.2022.3175011.
[2] Kuczmann, M. (2024). Review of DC Motor Modeling and Linear Control: Theory with Laboratory Tests. Electronics (Switzerland), 13(11), 2225. doi:10.3390/electronics13112225.
[3] Ylldlrlm, Ş., Bingol, M. S., & Savas, S. (2024). Tuning PID controller parameters of the DC motor with PSO algorithm. International Review of Applied Sciences and Engineering, 15(3), 281–286. doi:10.1556/1848.2023.00698.
[4] Natawangsa, H., Furizal, Ma’arif, A., & Salah, W. A. (2025). Solution Stirring Design Using Magnetic Stirrer on DC Motor with PLC-Based PID Method. Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika (JITEKI), 11(1), 42–52. doi:10.26555/JITEKI.V11I1.26534.
[5] Turan, A. (2025). Improved PID Control Design for Electric Power Steering DC Motor. IEEE Access, 13, 6080–6088. doi:10.1109/ACCESS.2024.3524303.
[6] Zarkasi, A., Ubaya, H., Exaudi, K., & Duri, A. H. (2024). Implementation of Fisherface Algorithm for Eye and Mouth Recognition in Face-Tracking Mobile Robot. Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika (JITEKI), 10(3), 556–565. doi:10.26555/jiteki.v10i3.29266.
[7] Khan, H., Khatoon, S., & Gaur, P. (2021). Comparison of various controller design for the speed control of DC motors used in two wheeled mobile robots. International Journal of Information Technology, 13(2), 713-720. doi:10.1007/s41870-020-00577-8.
[8] Hendriyanto, R. D., Puriyanto, R. D., Ma’arif, A., Vera, M. A. M., Nugroho, O. I. A., & Chivon, C. (2024). Control of Water Flow Rate in a Tank Using the Integral State Feedback Based on Arduino Uno. Control Systems and Optimization Letters, 2(3), 357–365. doi:10.59247/csol.v2i3.162.
[9] Molina-Santana, E., Iturralde Carrera, L. A., Álvarez-Alvarado, J. M., Aviles, M., & Rodríguez-Resendiz, J. (2025). Modeling and Control of a Permanent Magnet DC Motor: A Case Study for a Bidirectional Conveyor Belt’s Application. Eng, 6(3), 42. doi:10.3390/eng6030042.
[10] Kudra, G., Balthazar, J. M., Tusset, A. M., Wasilewski, G., Stańczyk, B., & Awrejcewicz, J. (2022). Dynamics analysis and control of a pendulum driven by a DC motor via a slider-crank mechanism. Mechanical Systems and Signal Processing, 166, 108415. doi:10.1016/j.ymssp.2021.108415.
[11] Prasad, B., Kumar, R., & Singh, M. (2024). Analysis of DC motor for process control application using neural network predictive controller. Engineering Research Express, 6(2), 25004. doi:10.1088/2631-8695/ad3b66.
[12] Fazdi, M. F., & Hsueh, P. W. (2023). Parameters Identification of a Permanent Magnet DC Motor: A Review. Electronics (Switzerland), 12(12), 2559. doi:10.3390/electronics12122559.
[13] Jabari, M., Ekinci, S., Izci, D., Bajaj, M., & Zaitsev, I. (2024). Efficient DC motor speed control using a novel multi-stage FOPD(1 + PI) controller optimized by the Pelican optimization algorithm. Scientific Reports, 14(1), 22442. doi:10.1038/s41598-024-73409-5.
[14] Gopi, P., Srinivasan, S., & Krishnamoorthy, M. (2022). Disk margin based robust stability analysis of a DC motor drive. Engineering Science and Technology, an International Journal, 32, 101074. doi:10.1016/j.jestch.2021.10.006.
[15] Sonugür, G. (2025). Efficient speed control of DC motors: imitation learning with fuzzy logic expert systems. Automatika, 66(2), 306–320. doi:10.1080/00051144.2025.2480425.
[16] Shneen, S. W., Dakheel, H. S., & Abdullah, Z. B. (2023). Design and implementation of no load, constant and variable load for DC servo motor. Journal of Robotics and Control (JRC), 4(3), 323-329. doi:10.18196/jrc.v4i3.17387.
[17] Ekinci, S., Izci, D., & Hekimoğlu, B. (2021). Optimal FOPID Speed Control of DC Motor via Opposition-Based Hybrid Manta Ray Foraging Optimization and Simulated Annealing Algorithm. Arabian Journal for Science and Engineering, 46(2), 1395–1409. doi:10.1007/s13369-020-05050-z.
[18] Yang, X., Deng, W., & Yao, J. (2022). Neural network based output feedback control for DC motors with asymptotic stability. Mechanical Systems and Signal Processing, 164, 108288. doi:10.1016/j.ymssp.2021.108288.
[19] Zhi, Y., Weiqing, W., Jing, C., & Razmjooy, N. (2022). Interval linear quadratic regulator and its application for speed control of DC motor in the presence of uncertainties. ISA Transactions, 125, 252–259. doi:10.1016/j.isatra.2021.07.004.
[20] Almawla, A. M., Hussein, M. J., & Abdullah, A. T. (2024). A comparative study of DC motor speed control techniques using fuzzy, SMC and PID. Journal Européen des Systèmes Automatisés, 57(2), 397. doi:10.18280/jesa.570209.
[21] Suwarno, I., Finayani, Y., Rahim, R., Alhamid, J., & Al-Obaidi, A. R. (2022). Controllability and Observability Analysis of DC Motor System and a Design of FLC-Based Speed Control Algorithm. Journal of Robotics and Control (JRC), 3(2), 227–235. doi:10.18196/jrc.v3i2.10741.
[22] Manuel, N. L., İnanç, N., & Lüy, M. (2023). Control and performance analyses of a DC motor using optimized PIDs and fuzzy logic controller. Results in Control and Optimization, 13, 100306. doi:10.1016/j.rico.2023.100306.
[23] Eker, E., Kayri, M., Ekinci, S., & Izci, D. (2021). A New Fusion of ASO with SA Algorithm and Its Applications to MLP Training and DC Motor Speed Control. Arabian Journal for Science and Engineering, 46(4), 3889–3911. doi:10.1007/s13369-020-05228-5.
[24] Ekinci, S., Hekimoğlu, B., & Izci, D. (2021). Opposition based Henry gas solubility optimization as a novel algorithm for PID control of DC motor. Engineering Science and Technology, an International Journal, 24(2), 331–342. doi:10.1016/j.jestch.2020.08.011.
[25] Izci, D. (2021). Design and application of an optimally tuned PID controller for DC motor speed regulation via a novel hybrid Lévy flight distribution and Nelder–Mead algorithm. Transactions of the Institute of Measurement and Control, 43(14), 3195–3211. doi:10.1177/01423312211019633.
[26] Kamarudin, M. N., Rozali, S. M., Azam, S. N. M., Hairi, M. H., & Zakaria, M. I. (2025). Formulation of a Lyapunov-Based PID Controller for Level Control of a Coupled-Tank System. International Journal of Robotics and Control Systems, 5(3), 1758-1769. doi:10.31763/ijrcs.v5i3.1947.
[27] Al-Dabbagh, Z. A., & Shneen, S. W. (2025). Design of a PID Speed Controller for BLDC Motor with Cascaded Boost Converter for High-Efficiency Industrial Applications. International Journal of Robotics and Control Systems, 5(1), 22-46. doi:10.31763/ijrcs.v5i1.1601.
[28] Qi, Z., Shi, Q., & Zhang, H. (2020). Tuning of digital PID controllers using particle swarm optimization algorithm for a CAN-Based DC motor subject to stochastic delays. IEEE Transactions on Industrial Electronics, 67(7), 5637–5646. doi:10.1109/TIE.2019.2934030.
[29] Ekinci, S., Izci, D., & Yilmaz, M. (2023). Efficient Speed Control for DC Motors Using Novel Gazelle Simplex Optimizer. IEEE Access, 11, 105830–105842. doi:10.1109/ACCESS.2023.3319596.
[30] Supriadi, S., Wajiansyah, A., Zainuddin, M., & Putra, A. B. W. (2024). Optimization of Proportional Integral Derivative Controller for Omni Robot Wheel Drive by Using Integrator Wind-up Reduction Based on Arduino Nano. Journal of Robotics and Control (JRC), 5(6), 1690-1701. doi:10.18196/jrc.v5i6.21807.
[31] Baidya, D., Dhopte, S., & Bhattacharjee, M. (2023). Sensing System Assisted Novel PID Controller for Efficient Speed Control of DC Motors in Electric Vehicles. IEEE Sensors Letters, 7(1), 1-4. doi:10.1109/LSENS.2023.3234400.
[32] Abdullah, Z. B., Shneen, S. W., & Dakheel, H. S. (2023). Simulation Model of PID Controller for DC Servo Motor at Variable and Constant Speed by Using MATLAB. Journal of Robotics and Control (JRC), 4(1), 54–59. doi:10.18196/jrc.v4i1.15866.
[33] Ekinci, S., Izci, D., Almomani, M. H., Saleem, K., Zitar, R. A., Smerat, A., Snasel, V., Ezugwu, A. E., & Abualigah, L. (2025). Advanced control parameter optimization in DC motors and liquid level systems. Scientific Reports, 15(1), 1–16. doi:10.1038/s41598-025-85273-y.
[34] Abdelghany, M. A., Elnady, A. O., & Ibrahim, S. O. (2023). Optimum PID Controller with Fuzzy Self-Tuning for DC Servo Motor. Journal of Robotics and Control (JRC), 4(4), 500–508. doi:10.18196/jrc.v4i4.18676.
[35] Tufenkci, S., Baykant Alagoz, B., Kavuran, G., Yeroglu, C., Herencsar, N., & Mahata, S. (2023). A theoretical demonstration for reinforcement learning of PI control dynamics for optimal speed control of DC motors by using Twin Delay Deep Deterministic Policy Gradient Algorithm. Expert Systems with Applications, 213, 119192. doi:10.1016/j.eswa.2022.119192.
[36] Martins, O. O., Adekunle, A. A., Arowolo, M. O., Uguru-Okorie, D. C., & Bolaji, B. O. (2022). The effect of an evolutionary algorithm’s rapid convergence on improving DC motor response using a PID controller. Scientific African, 17, 1327. doi:10.1016/j.sciaf.2022.e01327.
[37] Nethaji, G., & Kathirvelan, J. (2024). Performance comparison between PID and Fuzzy logic controllers for the hardware implementation of traditional high voltage DC-DC boost converter. Heliyon, 10(17), e36750. doi:10.1016/j.heliyon.2024.e36750.
[38] Cabré, T. P., Vela, A. S., Ribes, M. T., Blanc, J. M., Pablo, J. R., & Sancho, F. C. (2021). Didactic platform for DC motor speed and position control in Z-plane. ISA Transactions, 118, 116–132. doi:10.1016/j.isatra.2021.02.020.
[39] Thangavel, S., Mohanraj, D., Girijaprasanna, T., Raju, S., Dhanamjayulu, C., & Muyeen, S. M. (2023). A Comprehensive Review on Electric Vehicle: Battery Management System, Charging Station, Traction Motors. IEEE Access, 11, 20994–21019. doi:10.1109/ACCESS.2023.3250221.
[40] Migliazza, G., Buticchi, G., Carfagna, E., Lorenzani, E., Madonna, V., Giangrande, P., & Galea, M. (2021). DC Current Control for a Single-Stage Current Source Inverter in Motor Drive Application. IEEE Transactions on Power Electronics, 36(3), 3367–3376. doi:10.1109/TPEL.2020.3013301.
[41] Barkas, D. A., Ioannidis, G. C., Psomopoulos, C. S., Kaminaris, S. D., & Vokas, G. A. (2020). Brushed dc motor drives for industrial and automobile applications with emphasis on control techniques: A comprehensive review. Electronics (Switzerland), 9(6), 887. doi:10.3390/electronics9060887.
[42] Valencia, D. F., Tarvirdilu-Asl, R., Garcia, C., Rodriguez, J., & Emadi, A. (2021). Vision, Challenges, and Future Trends of Model Predictive Control in Switched Reluctance Motor Drives. IEEE Access, 9, 69926–69937. doi:10.1109/ACCESS.2021.3078366.
[43] Swaminathan, R., Cai, C. J., Yuan, S., & Ren, H. (2021). Multiphysics Simulation of Magnetically Actuated Robotic Origami Worms. IEEE Robotics and Automation Letters, 6(3), 4923–4930. doi:10.1109/LRA.2021.3068707.
[44] Liu, W., Wang, J., & Lipo, T. A. (2023). A Consequent Pole Single Rotor Single Stator Vernier Design to Effectively Improve Torque Density of an Industrial PM Drive. IEEE Transactions on Industrial Electronics, 70(1), 255–264. doi:10.1109/TIE.2022.3153806.
[45] Yan, S., Yang, Y., Hui, S. Y., & Blaabjerg, F. (2021). A Review on Direct Power Control of Pulsewidth Modulation Converters. IEEE Transactions on Power Electronics, 36(10), 11984–12007. doi:10.1109/TPEL.2021.3070548.
[46] Arehpanahi, M., & Entekhabi, A. M. (2022). A New Technique for Online Open Switch Fault Detection and Location in Single-phase Pulse Width Modulation Rectifier. International Journal of Engineering, Transactions B: Applications, 35(9), 1759–1764. doi:10.5829/ije.2022.35.09c.12.
[47] Puentes, K., Morales, L., Pozo-Espin, D. F., & Moya, V. (2024). Enhancing Control Systems with Neural Network-Based Intelligent Controllers. Emerging Science Journal, 8(4), 1243–1261. doi:10.28991/ESJ-2024-08-04-01.
[48] Szczepankowski, P., Poliakov, N., Vertegel, D., Szwarc, K. J., & Strzelecki, R. (2020). A New Concept of PWM Duty Cycle Computation Using the Barycentric Coordinates in a Three-Dimensional Voltage Vectors Arrangement. IEEE Access, 8, 8019–8031. doi:10.1109/ACCESS.2019.2963743.
[49] Von Hoegen, A., Gotz, G. T., Mason, N. A., Hartgenbusch, N., Kojima, T., & De Doncker, R. W. (2024). Precise Volt-Second Measuring Instrument for PWM Voltage-Source Inverters. IEEE Transactions on Instrumentation and Measurement, 73, 1–15. doi:10.1109/TIM.2024.3381660.
[50] Thanoon, M. A., Almaged, M., & Abdulla, A. I. (2025). Boost Converter Control Using Proportional-Integral-Derivative Controller Optimized by Whale Optimization Algorithm. International Journal of Robotics & Control Systems, 5(3), 1850-1865. doi:10.31763/ijrcs.v5i3.1912.
[51] Mien, T. L., & Tu, T. N. (2024). Design and Quality Evaluation of the Position and Attitude Control System for 6-DOF UAV Quadcopter Using Heuristic PID Tuning Methods. International Journal of Robotics and Control Systems, 4(4), 1712–1730. doi:10.31763/ijrcs.v4i4.1594.
[52] Al-Samarraie, S. A., & Gorial, I. I. (2024). Assessment of FLC, PID, Nonlinear PID, and SMC Controllers for Level Stabilization in Mechatronic Systems. Journal of Robotics and Control (JRC), 5(6), 1845–1861. doi:10.18196/jrc.v5i6.23639.
[53] Bhookya, J., Vijaya Kumar, M., Ravi Kumar, J., & Seshagiri Rao, A. (2022). Implementation of PID controller for liquid level system using mGWO and integration of IoT application. Journal of Industrial Information Integration, 28, 100368. doi:10.1016/j.jii.2022.100368.
[54] Keppler, M., Raschel, C., Wandinger, D., Stemmer, A., & Ott, C. (2022). Robust Stabilization of Elastic Joint Robots by ESP and PID Control: Theory and Experiments. IEEE Robotics and Automation Letters, 7(3), 8283–8290. doi:10.1109/LRA.2022.3187277.
[55] Baghli, F. Z., Lakhal, Y., & El Kadi, Y. A. (2023). The Efficiency of an Optimized PID Controller Based on Ant Colony Algorithm (ACO-PID) for the Position Control of a Multi-articulated System. Journal of Robotics and Control (JRC), 4(3), 289–298. doi:10.18196/jrc.v4i3.17709.
[56] Mohammed, I. K., & Khalaf, L. A. (2024). Design and Simulation of an Analog Robust Control for a Realistic Buck Converter Model. Journal of Robotics and Control (JRC), 5(5), 1336–1348. doi:10.18196/jrc.v5i5.22408.
[57] Borase, R. P., Maghade, D. K., Sondkar, S. Y., & Pawar, S. N. (2021). A review of PID control, tuning methods and applications. International Journal of Dynamics and Control, 9(2), 818–827. doi:10.1007/s40435-020-00665-4.
[58] Alshalalfah, A. L., Hamad, G. B., & Mohamed, O. A. (2021). Towards Safe and Robust Closed-Loop Artificial Pancreas Using Improved PID-Based Control Strategies. IEEE Transactions on Circuits and Systems I: Regular Papers, 68(8), 3147–3157. doi:10.1109/TCSI.2021.3058355.
[59] Zellouma, D., Bekakra, Y., & Benbouhenni, H. (2023). Field-oriented control based on parallel proportional–integral controllers of induction motor drive. Energy Reports, 9, 4846–4860. doi:10.1016/j.egyr.2023.04.008.
[60] Chotikunnan, P., Chotikunnan, R., Nirapai, A., Wongkamhang, A., Imura, P., & Sangworasil, M. (2023). Optimizing Membership Function Tuning for Fuzzy Control of Robotic Manipulators using PID-Driven Data Techniques. Journal of Robotics and Control (JRC), 4(2), 128–140. doi:10.18196/jrc.v4i2.18108.
[61] Euzebio, T. A. M., Silva, M. T. D., & Yamashita, A. S. (2021). Decentralized PID Controller Tuning Based on Nonlinear Optimization to Minimize the Disturbance Effects in Coupled Loops. IEEE Access, 9, 156857–156867. doi:10.1109/ACCESS.2021.3127795.
[62] Joseph, S. B., Dada, E. G., Abidemi, A., Oyewola, D. O., & Khammas, B. M. (2022). Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems. Heliyon, 8(5), 9399. doi:10.1016/j.heliyon.2022.e09399.
[63] Putra, A. M., Maradona, H., & Rohmah, R. A. (2025). Comparison of Proportional Integral Derivative and Fuzzy Logic Controllers: A Literature Review on the Best Method for Controlling Direct Current Motor Speed. International Journal of Robotics and Control Systems, 5(1), 240–265. doi:10.31763/ijrcs.v5i1.1701.
[64] Baharuddin, A., & Mohd Basri, M. A. (2023). Self-Tuning PID Controller for Quadcopter using Fuzzy Logic. International Journal of Robotics and Control Systems, 3(4), 728–748. doi:10.31763/ijrcs.v3i4.1127.
[65] Najem, A., Moutabir, A., & Ouchatti, A. (2024). Simulation and Arduino Hardware Implementation of ACO, PSO, and FPA Optimization Algorithms for Speed Control of a DC Motor. International Journal of Robotics and Control Systems, 4(3), 1186–1206. doi:10.31763/ijrcs.v4i3.1483.
[66] Kurniasari, I. D., & Ma’arif, A. (2024). Implementing PID-Kalman Algorithm to Reduce Noise in DC Motor Rotational Speed Control. International Journal of Robotics and Control Systems, 4(2), 958–978. doi:10.31763/ijrcs.v4i2.1309.
[67] Rahayu, E. S., Ma’arif, A., & Cakan, A. (2022). Particle Swarm Optimization (PSO) Tuning of PID Control on DC Motor. International Journal of Robotics and Control Systems, 2(2), 435–447. doi:10.31763/ijrcs.v2i2.476.
[68] Suseno, E. W., & Ma’Arif, A. (2021). Tuning of PID Controller Parameters with Genetic Algorithm Method on DC Motor. International Journal of Robotics and Control Systems, 1(1), 41–53. doi:10.31763/ijrcs.v1i1.249.
[69] Zheng, X., Yu, X., Jiang, J., & Yang, X. (2024). Practical Finite-Time Command Filtered Backstepping With its Application to DC Motor Control Systems. IEEE Transactions on Industrial Electronics, 71(3), 2955–2964. doi:10.1109/TIE.2023.3269478.
[70] Kong, W., Zhang, H., Yang, X., Yao, Z., Wang, R., Yang, W., & Zhang, J. (2024). PID control algorithm based on multistrategy enhanced dung beetle optimizer and back propagation neural network for DC motor control. Scientific Reports, 14(1), 1–26. doi:10.1038/s41598-024-79653-z.
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