Using a Combination of PID Control and Kalman Filter to Design of IoT-based Telepresence Self-balancing Robots during COVID-19 Pandemic

Iswanto Suwarno, Alfian Ma'arif, Nia Maharani Raharja, Tony Khristanto Hariadi, Muhammad Abdus Shomad

Abstract


COVID-19 is a very dangerous respiratory disease that can spread quickly through the air. Doctors, nurses, and medical personnel need protective clothing and are very careful in treating COVID-19 patients to avoid getting infected with the COVID-19 virus. Hence, a medical telepresence robot, which resembles a humanoid robot, is necessary to treat COVID-19 patients. The proposed self-balancing COVID-19 medical telepresence robot is a medical robot that handles COVID-19 patients, which resembles a stand-alone humanoid soccer robot with two wheels that can maneuver freely in hospital hallways. The proposed robot design has some control problems; it requires steady body positioning and is subjected to disturbance. A control method that functions to find the stability value such that the system response can reach the set-point is required to control the robot's stability and repel disturbances; this is known as disturbance rejection control. This study aimed to control the robot using a combination of Proportional-Integral-Derivative (PID) control and a Kalman filter. Mathematical equations were required to obtain a model of the robot's characteristics. The state-space model was derived from the self-balancing robot's mathematical equation. Since a PID control technique was used to keep the robot balanced, this state-space model was converted into a transfer function model. The second Ziegler-Nichols's rule oscillation method was used to tune the PID parameters. The values of the amplifier constants obtained were Kp=31.002, Ki=5.167, and Kd=125.992128. The robot was designed to be able to maintain its balance for more than one hour by using constant tuning, even when an external disturbance is applied to it.

 

Doi: 10.28991/esj-2021-SP1-016

Full Text: PDF


Keywords


Self-Balancing Robot; Telepresence Robot; Kalman Filter; COVID-19: Mathematical Modeling; PID; Zigler-Nichols.

References


Jones, D. L., Baluja, M. Q., Graham, D. W., Corbishley, A., McDonald, J. E., Malham, S. K., Hillary, L. S., Connor, T. R., Gaze, W. H., Moura, I. B., Wilcox, M. H., & Farkas, K. (2020). Shedding of SARS-CoV-2 in feces and urine and its potential role in person-to-person transmission and the environment-based spread of COVID-19. Science of the Total Environment, 749, 141364. doi:10.1016/j.scitotenv.2020.141364.

Widyasmoro, W., Suwarno, I., Surahmat, I., Nugraha, T. A., & Al_barazanchi, I. (2022). Dissemination of technology utilization of FM community radio as a means to support teaching learning activities for students during the covid-19 pandemic at Muhammadiyah Elementary School Tlogolelo, Hargomulyo, Kokap District, Kulon Progo, DIY. Jurnal Pengabdian Dan Pemberdayaan Masyarakat Indonesia, 2(1), 34–42.

Suwarno, I., Ma’arif, A., Maharani Raharja, N., Nurjanah, A., Ikhsan, J., & Mutiarin, D. (2021). IoT-based Lava Flood Early Warning System with Rainfall Intensity Monitoring and Disaster Communication Technology. Emerging Science Journal, 4, 154–166. doi:10.28991/esj-2021-sp1-011.

Ralph, R., Lew, J., Zeng, T., Francis, M., Xue, B., Roux, M., Ostadgavahi, A. T., Rubino, S., Dawe, N. J., Al-Ahdal, M. N., Kelvin, D. J., Richardson, C. D., Kindrachuk, J., Falzarano, D., & Kelvin, A. A. (2020). 2019-nCoV (Wuhan virus), a novel Coronavirus: Human-to-human transmission, travel-related cases, and vaccine readiness. Journal of Infection in Developing Countries, 14(1), 3–17. doi:10.3855/jidc.12425.

Iswanto, I., Raharja, N. M., Maarif, A., Supangkat, G., Pandey, A., Deniz, C., Nurjanah, A., Rijalusalam, D. U., Sánchez-López, C., & Ahmad, I. (2021). Empowerment of mosque communities to increase body immune with aroma therapy robots. Jurnal Pengabdian Dan Pemberdayaan Masyarakat Indonesia, 1(4), 127–135.

Wang, D., Hu, B., Hu, C., Zhu, F., Liu, X., Zhang, J., Wang, B., Xiang, H., Cheng, Z., Xiong, Y., Zhao, Y., Li, Y., Wang, X., & Peng, Z. (2020). Clinical Characteristics of 138 Hospitalized Patients with 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA - Journal of the American Medical Association, 323(11), 1061–1069. doi:10.1001/jama.2020.1585.

Ziafati Bagherzadeh, S. H., & Toosizadeh, S. (2022). Eye Tracking Algorithm Based on Multi Model Kalman Filter. HighTech and Innovation Journal, 3(1), 15–27. doi:10.28991/hij-2022-03-01-02.

Sofia, S., Ariani, M., & Sa, Z. (2021). Socialization of covid-19 prevention for children at kaye aceh village, southwest aceh regency, aceh province, indonesia. Jurnal Pengabdian Dan Pemberdayaan Masyarakat Indonesia, 1(4), 142–148.

Huang, L., Lin, G., Tang, L., Yu, L., & Zhou, Z. (2020). Special attention to nurses’ protection during the COVID-19 epidemic. Critical Care, 24(1), 1–3,. doi:10.1186/s13054-020-2841-7.

Hasan, N. A., Fauzi, R., Lestari, Y., Siti, F., & Alfiana, R. D. (2021). Technology Dissemination of Blood type Checking and Health Examination by the Thematic Community Service Program (KKN) of Alma Ata University in Hamlet of Kejambon Kidul. Jurnal Pengabdian Dan Pemberdayaan Masyarakat Indonesia, 1(9), 371–378.

Wang, M., Pan, C., & Ray, P. K. (2021). Technology Entrepreneurship in Developing Countries: Role of Telepresence Robots in Healthcare. IEEE Engineering Management Review, 49(1), 20–26. doi:10.1109/emr.2021.3053258.

Riduwan, & Ma’ruf, F. (2021). Dissemination of Sharia Cooperative Research, Solutions during a Pandemic. Jurnal Pengabdian Dan Pemberdayaan Masyarakat Indonesia, 1(11), 459–468.

Shamblaw, A. L., Rumas, R. L., & Best, M. W. (2021). Coping during the COVID-19 pandemic: Relations with mental health and quality of life. Canadian Psychology/Psychologie Canadienne, 62(1), 92–100. doi:10.1037/cap0000263.

Al Firdaus, A. A., Muafiah, E., Heriyudanta, M., & Al_barazanchi, I. (2021). Empowerment of Marketing Strategies of Angkringan Traders through Social Media during Covid-19 Time in Ponorogo. Jurnal Pengabdian Dan Pemberdayaan Masyarakat Indonesia, 1(3), 84–94.

Zhu, X., & He, B. (2021). Underactuated rehabilitation robotics for hand function. Journal of Robotics and Control (JRC), 2(5), 337–341. doi:10.18196/jrc.25103.

Shalal, N. S., & Aboud, W. S. (2021). Smart robotic exoskeleton: A 3-dof for wrist-forearm rehabilitation. Journal of Robotics and Control (JRC), 2(6), 476–483. doi:10.18196/jrc.26125.

Fitter, N. T., Raghunath, N., Cha, E., Sanchez, C. A., Takayama, L., & Mataric, M. J. (2020). Are We There Yet? Comparing Remote Learning Technologies in the University Classroom. IEEE Robotics and Automation Letters, 5(2), 2706–2713. doi:10.1109/LRA.2020.2970939.

Abibullaev, B., Zollanvari, A., Saduanov, B., & Alizadeh, T. (2019). Design and Optimization of a BCI-Driven Telepresence Robot through Programming by Demonstration. IEEE Access, 7, 111625–111636. doi:10.1109/ACCESS.2019.2933268.

Rhee, T., Thompson, S., Medeiros, D., Dos Anjos, R., & Chalmers, A. (2020). Augmented Virtual Teleportation for High-Fidelity Telecollaboration. IEEE Transactions on Visualization and Computer Graphics, 26(5), 1923–1933. doi:10.1109/TVCG.2020.2973065.

Sun, D., Kiselev, A., Liao, Q., Stoyanov, T., & Loutfi, A. (2020). A New Mixed-Reality-Based Teleoperation System for Telepresence and Maneuverability Enhancement. IEEE Transactions on Human-Machine Systems, 50(1), 55–67. doi:10.1109/THMS.2019.2960676.

Becerra, I., Suomalainen, M., Lozano, E., Mimnaugh, K. J., Murrieta-Cid, R., & Lavalle, S. M. (2020). Human Perception-Optimized Planning for Comfortable VR-Based Telepresence. IEEE Robotics and Automation Letters, 5(4), 6489–6496. doi:10.1109/LRA.2020.3015191.

Zhong, M., Li, C., Liu, L., Wen, J., Ma, J., & Yu, X. (2020). Fuzzy Neighborhood Learning for Deep 3-D Segmentation of Point Cloud. IEEE Transactions on Fuzzy Systems, 28(12), 3181–3192. doi:10.1109/TFUZZ.2020.2992611.

Khenak, N., Vezien, J., & Bourdot, P. (2020). Spatial Presence, Performance, and Behavior between Real, Remote, and Virtual Immersive Environments. IEEE Transactions on Visualization and Computer Graphics, 26(12), 3467–3478. doi:10.1109/TVCG.2020.3023574.

Erat, O., Hoell, M., Haubenwallner, K., Pirchheim, C., & Schmalstieg, D. (2019). Real-Time View Planning for Unstructured Lumigraph Modeling. IEEE Transactions on Visualization and Computer Graphics, 25(11), 3063–3072. doi:10.1109/TVCG.2019.2932237.

Peng, X. (2019). New multiparametric similarity measure and distance measure for interval neutrosophic set with IoT industry evaluation. IEEE Access, 7(c), 28258–28280. doi:10.1109/ACCESS.2019.2902148.

Chen, H., Huang, P., & Liu, Z. (2019). Mode Switching-Based Symmetric Predictive Control Mechanism for Networked Teleoperation Space Robot System. IEEE/ASME Transactions on Mechatronics, 24(6), 2706–2717. doi:10.1109/TMECH.2019.2946197.

Albert, K., Phogat, K. S., Anhalt, F., Banavar, R. N., Chatterjee, D., & Lohmann, B. (2020). Structure-Preserving Constrained Optimal Trajectory Planning of a Wheeled Inverted Pendulum. IEEE Transactions on Robotics, 36(3), 910–923. doi:10.1109/TRO.2020.2985579.

Pathak, K., Franch, J., & Agrawal, S. K. (2005). Velocity and position control of a wheeled inverted pendulum by partial feedback linearization. IEEE Transactions on Robotics, 21(3), 505–513. doi:10.1109/TRO.2004.840905.

Rizal, Y., Wahyu, M., Noor, I., Riadi, J., Feriyadi, F., & Mantala, R. (2021). Design of an Adaptive Super-Twisting Control for the Cart-Pole Inverted Pendulum System. Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika, 7(1), 161. doi:10.26555/jiteki.v7i1.20420.

Park, M. S., & Chwa, D. (2009). Swing-up and stabilization control of inverted-pendulum systems via coupled sliding-mode control method. IEEE Transactions on Industrial Electronics, 56(9), 3541–3555. doi:10.1109/TIE.2009.2012452.

Motoi, N., Motoi, N., Suzuki, T., & Ohnishi, K. (2009). A Bipedal Locomotion Planning Based on Virtual Linear Inverted Pendulum Mode. IEEE Transactions on Industrial Electronics, 56(1), 54–61. doi:10.1109/TIE.2008.2004663.

Aoyama, T., Hasegawa, Y., Sekiyama, K., & Fukuda, T. (2009). Stabilizing and direction control of efficient 3-D biped walking based on PDAC. IEEE/ASME Transactions on Mechatronics, 14(6), 712–718. doi:10.1109/TMECH.2009.2032777.

Huang, J., Guan, Z. H., Matsuno, T., Fukuda, T., & Sekiyama, K. (2010). Sliding-mode velocity control of mobile-wheeled inverted-pendulum systems. IEEE Transactions on Robotics, 26(4), 750–758. doi:10.1109/TRO.2010.2053732.

Irfan, S., Mehmood, A., Razzaq, M. T., & Iqbal, J. (2018). Advanced sliding mode control techniques for Inverted Pendulum: Modelling and simulation. Engineering Science and Technology, an International Journal, 21(4), 753–759. doi:10.1016/j.jestch.2018.06.010.

Kim, S., & Kwon, S. (2017). Nonlinear optimal control design for underactuated two-wheeled inverted pendulum mobile platform. IEEE/ASME Transactions on Mechatronics, 22(6), 2803–2808. doi:10.1109/TMECH.2017.2767085.

Ma’arif, A., Vera, M. A. M., Mahmoud, M. S., Ladaci, S., Çakan, A., & Parada, J. N. (2022). Backstepping Sliding Mode Control for Inverted Pendulum System with Disturbance and Parameter Uncertainty. Journal of Robotics and Control (JRC), 3(1), 86–92. doi:10.18196/jrc.v3i1.12739.

Huang, J., Zhang, M., Ri, S., Xiong, C., Li, Z., & Kang, Y. (2020). High-Order Disturbance-Observer-Based Sliding Mode Control for Mobile Wheeled Inverted Pendulum Systems. IEEE Transactions on Industrial Electronics, 67(3), 2030–2041. doi:10.1109/TIE.2019.2903778.

Islam1, M. R., Hossain2, M. R. T., & Banik, S. C. (2021). Synchronizing of stabilizing platform mounted on a two-wheeled robot. Journal of Robotics and Control (JRC), 2(6), 552–558. doi:10.18196/jrc.26136.

Van Lam, P., & Fujimoto, Y. (2019). A Robotic Cane for Balance Maintenance Assistance. IEEE Transactions on Industrial Informatics, 15(7), 3998–4009. doi:10.1109/TII.2019.2903893.

Sahnehsaraei, M. A., & Mahmoodabadi, M. J. (2021). Approximate feedback linearization based optimal robust control for an inverted pendulum system with time-varying uncertainties. International Journal of Dynamics and Control, 9(1), 160–172. doi:10.1007/s40435-020-00651-w.

Watson, M. T., Gladwin, D. T., Prescott, T. J., & Conran, S. O. (2019). Dual-Mode Model Predictive Control of an Omnidirectional Wheeled Inverted Pendulum. IEEE/ASME Transactions on Mechatronics, 24(6), 2964–2975. doi:10.1109/TMECH.2019.2943708.

Iwendi, C., Alqarni, M. A., Anajemba, J. H., Alfakeeh, A. S., Zhang, Z., & Bashir, A. K. (2019). Robust Navigational Control of a Two-Wheeled Self-Balancing Robot in a Sensed Environment. IEEE Access, 7, 82337–82348. doi:10.1109/ACCESS.2019.2923916.

Wu, L. F., & Li, T. H. S. (2020). Fuzzy dynamic gait pattern generation for real-time push recovery control of a teen-sized humanoid robot. IEEE Access, 8, 36441–36453. doi:10.1109/ACCESS.2020.2975041.

Mahmoud, M. S., & Nasir, M. T. (2017). Robust control design of wheeled inverted pendulum assistant robot. IEEE/CAA Journal of Automatica Sinica, 4(4), 628–638. doi:10.1109/JAS.2017.7510613.

Lin, L. G., & Xin, M. (2020). Nonlinear Control of Two-Wheeled Robot Based on Novel Analysis and Design of SDRE Scheme. IEEE Transactions on Control Systems Technology, 28(3), 1140–1148. doi:10.1109/TCST.2019.2899802.

Akhond, S., Herzig, N., Wegiriya, H., & Nanayakkara, T. (2019). A method to guide local physical adaptations in a robot based on phase portraits. IEEE Access, 7, 78830–78841. doi:10.1109/ACCESS.2019.2923144.

Ramos, J., & Kim, S. (2018). Dynamic bilateral teleoperation of the cart-pole: A study toward the synchronization of human operator and legged robot. IEEE Robotics and Automation Letters, 3(4), 3293–3299. doi:10.1109/LRA.2018.2852840.

Iacob, C. G. (2020). Linear and angular position control of a custom built stepper motor driven self-balancing robot. 24th International Conference on System Theory, Control and Computing, ICSTCC 2020, Sinaia, Romania, 648–653. doi:10.1109/ICSTCC50638.2020.9259706.

Yuan, Y., Li, Z., Zhao, T., & Gan, D. (2020). DMP-Based Motion Generation for a Walking Exoskeleton Robot Using Reinforcement Learning. IEEE Transactions on Industrial Electronics, 67(5), 3830–3839. doi:10.1109/TIE.2019.2916396.

Carpentier, J., & Mansard, N. (2018). Multicontact Locomotion of Legged Robots. IEEE Transactions on Robotics, 34(6), 1441–1460. doi:10.1109/TRO.2018.2862902.

Li, Z., Ren, Z., Zhao, K., Deng, C., & Feng, Y. (2020). Human-Cooperative Control Design of a Walking Exoskeleton for Body Weight Support. IEEE Transactions on Industrial Informatics, 16(5), 2985–2996. doi:10.1109/TII.2019.2900121.

Puriel Gil, G., Yu, W., & Sossa, H. (2019). Reinforcement Learning Compensation based PD Control for a Double Inverted Pendulum. IEEE Latin America Transactions, 17(2), 323–329. doi:10.1109/TLA.2019.8863179.

Huang, J., Ri, M., Wu, D., & Ri, S. (2018). Interval type-2 fuzzy logic modeling and control of a mobile two-wheeled inverted pendulum. IEEE Transactions on Fuzzy Systems, 26(4), 2030–2038. doi:10.1109/TFUZZ.2017.2760283.

Bounemeur, A., & Chemachema, M. (2021). Adaptive Fuzzy Fault-Tolerant Control for a Class of Nonlinear Systems under Actuator Faults: Application to an Inverted Pendulum. International Journal of Robotics and Control Systems, 1(2), 102–115. doi:10.31763/ijrcs.v1i2.306.

Gong, D., Wang, P., Zhao, S., Du, L., & Duan, Y. (2018). Bionic quadruped robot dynamic gait control strategy based on twenty degrees of freedom. IEEE/CAA Journal of Automatica Sinica, 5(1), 382–388. doi:10.1109/JAS.2017.7510790.

Saad, M., Amhedb, A. H., & Al Sharqawi, M. (2021). Real time DC motor position control using PID controller in LabVIEW. Journal of Robotics and Control (JRC), 2(5), 342–348. doi:10.18196/jrc.25104.

Handaya, D., & Fauziah, R. (2021). Proportional-integral-derivative and linear quadratic regulator control of direct current motor position using multi-turn based on LabView. Journal of Robotics and Control (JRC), 2(4), 332–336. doi:10.18196/jrc.24102.

Kadry, S., & Rajinikanth, V. (2021). Design of PID Controller for Magnetic Levitation System using Harris Hawks Optimization. Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika, 6(2), 70. doi:10.26555/jiteki.v6i2.19167.

Syafeeq Lone, S., Zainul Azlan, N., & Kamarudzaman, N. (2021). Soft Pneumatic Exoskeleton for Wrist and Thumb Rehabilitation. International Journal of Robotics and Control Systems, 1(4), 440–452. doi:10.31763/ijrcs.v1i4.447.

Hussein Mohammed Al-Almoodi, H., Zainul Azlan, N., Shahdad, I., & Kamarudzaman, N. (2021). Continuous Passive Motion Machine for Elbow Rehabilitation. International Journal of Robotics and Control Systems, 1(3), 402–415. doi:10.31763/ijrcs.v1i3.446.

Jabeur, C. Ben, & Seddik, H. (2022). Optimized Neural Networks-PID Controller with Wind Rejection Strategy for a Quad-Rotor. Journal of Robotics and Control (JRC), 3(1), 62–72. doi:10.18196/jrc.v3i1.11660.

Rodriguez-Abreo, O., Rodriguez-Resendiz, J., Fuentes-Silva, C., Hernandez-Alvarado, R., & Falcon, M. D. C. P. T. (2021). Self-Tuning Neural Network PID with Dynamic Response Control. IEEE Access, 9, 65206–65215. doi:10.1109/ACCESS.2021.3075452.

Widya Suseno, E., & 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.

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.

Kristiyono, R., & Wiyono. (2021). Autotuning fuzzy PID controller for speed control of BLDC motor. Journal of Robotics and Control (JRC), 2(5), 400–407. doi:10.18196/jrc.25114.

Maghfiroh, H., Ahmad, M., Ramelan, A., & Adriyanto, F. (2022). Fuzzy-PID in BLDC Motor Speed Control Using MATLAB/Simulink. Journal of Robotics and Control (JRC), 3(1), 8–13. doi:10.18196/jrc.v3i1.10964.

Ekinci, S., & Hekimoglu, B. (2019). Improved Kidney-Inspired Algorithm Approach for Tuning of PID Controller in AVR System. IEEE Access, 7, 39935–39947. doi:10.1109/ACCESS.2019.2906980.

Kashyap, A. K., & Parhi, D. R. (2021). Particle Swarm Optimization aided PID gait controller design for a humanoid robot. ISA Transactions, 114, 306–330. doi:10.1016/j.isatra.2020.12.033.

Patel, V. V. (2020). Ziegler-Nichols Tuning Method: Understanding the PID Controller. Resonance, 25(10), 1385–1397. doi:10.1007/s12045-020-1058-z.

Ogata, K. (2010). Modern control engineering (5th Ed.). Upper Saddle River, NJ: Prentice-Hall, New Jersey, United States.

Ma’arif, A., Iswanto, I., Nuryono, A. A., & Alfian, R. I. (2019). Kalman Filter for Noise Reducer on Sensor Readings. Signal and Image Processing Letters, 1(2), 11–22. doi:10.31763/simple.v1i2.2.

Alfian, R. I., Ma’Arif, A., & Sunardi, S. (2021). Noise reduction in the accelerometer and gyroscope sensor with the Kalman filter algorithm. Journal of Robotics and Control (JRC), 2(3), 180–189. doi:10.18196/jrc.2375.

Qu, D., Zheng, Y., Guo, J., & Song, R. (2020). A Control Scheme for Single Legged Hopping Robot Based on Fuzzy PD Algorithm. Proceedings of 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2020, Itnec, 384–388. doi:10.1109/ITNEC48623.2020.9084676.

Lakatos, D., Ploeger, K., Loeffl, F., Seidel, D., Schmidt, F., Gumpert, T., John, F., Bertram, T., & Albu-Schaffer, A. (2018). Dynamic Locomotion Gaits of a Compliantly Actuated Quadruped with SLIP-Like Articulated Legs Embodied in the Mechanical Design. IEEE Robotics and Automation Letters, 3(4), 3908–3915. doi:10.1109/LRA.2018.2857511.

Tzorakoleftherakis, E., Ansari, A., Wilson, A., Schultz, J., & Murphey, T. D. (2016). Model-Based Reactive Control for Hybrid and High-Dimensional Robotic Systems. IEEE Robotics and Automation Letters, 1(1), 431–438. doi:10.1109/LRA.2016.2522078.

Erkol, H. O. (2018). Optimal PIλ Dμ controller design for two wheeled inverted pendulum. IEEE Access, 6, 75709–75717. doi:10.1109/ACCESS.2018.2883504.

Zaytsev, P., Wolfslag, W., & Ruina, A. (2018). The Boundaries of Walking Stability: Viability and Controllability of Simple Models. IEEE Transactions on Robotics, 34(2), 336–352. doi:10.1109/TRO.2017.2782818.

Zhang, L., Ren, X., & Guo, Q. (2020). Balance Control of a Wheeled Hopping Robot. Chinese Control Conference, CCC, 2020-July, 3801–3805. doi:10.23919/CCC50068.2020.9189592.

Dong, S., Yuan, Z., Yu, X., Zhang, J., Sadiq, M. T., & Zhang, F. (2019). On-Line Gait Adjustment for Humanoid Robot Robust Walking Based on Divergence Component of Motion. IEEE Access, 7, 159507–159518. doi:10.1109/ACCESS.2019.2949747.

Mohan, A., Sivaprakasam, M., George, B., & Kumar, V. J. (2018). Self-balancing signal conditioning circuit for a floating-wiper resistive displacement sensor. IEEE Sensors Journal, 18(18), 7544–7550. doi:10.1109/JSEN.2018.2858824.

Su, Y., Wang, T., Zhang, K., Yao, C., & Wang, Z. (2020). Adaptive Nonlinear Control Algorithm for a Self-Balancing Robot. IEEE Access, 8, 3751–3760. doi:10.1109/ACCESS.2019.2963110.

Maghfiroh, H., & Santoso, H. P. (2021). Self-balancing robot navigation. Journal of Robotics and Control (JRC), 2(5), 408–412. doi:10.18196/jrc.25115.

Borase, R. P., Maghade, D. K., Sondkar, S. Y., & Pawar, S. N. (2020). 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.

Okelola, M. O., Aborisade, D. O., & Adewuyi, P. A. (2021). Performance and Configuration Analysis of Tracking Time Anti-Windup PID Controllers. Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika, 6(2), 20. doi:10.26555/jiteki.v6i2.18867.

Li, P., & Zhu, G. (2019). IMC-based PID control of servo motors with extended state observer. Mechatronics, 62(June), 102252. doi:10.1016/j.mechatronics.2019.102252.

Sun, X., & Yan, G. (2018). Multi-sensor optimal weighted fusion incremental Kalman smoother. Journal of Systems Engineering and Electronics, 29(2), 262–268. doi:10.21629/JSEE.2018.02.06.

Rong, H., Peng, C., Chen, Y., Zou, L., Zhu, Y., & Lv, J. (2018). Adaptive-Gain Regulation of Extended Kalman Filter for Use in Inertial and Magnetic Units Based on Hidden Markov Model. IEEE Sensors Journal, 18(7), 3016–3027. doi:10.1109/JSEN.2018.2806932.

Wang, H., Li, H., Fang, J., & Wang, H. (2018). Robust Gaussian Kalman filter with outlier detection. IEEE Signal Processing Letters, 25(8), 1236–1240. doi:10.1109/LSP.2018.2851156.

Zhang, Q., Yang, Y., Xiang, Q., He, Q., Zhou, Z., & Yao, Y. (2018). Noise Adaptive Kalman Filter for Joint Polarization Tracking and Channel Equalization Using Cascaded Covariance Matching. IEEE Photonics Journal, 10(1), 1–1. doi:10.1109/JPHOT.2018.2797050.

Zahraoui, Y., Akherraz, M., & Ma’arif, A. (2021). A Comparative Study of Nonlinear Control Schemes for Induction Motor Operation Improvement. International Journal of Robotics and Control Systems, 2(1), 1–17. doi:10.31763/ijrcs.v2i1.521.

Zhao, S., Shmaliy, Y. S., Ahn, C. K., & Liu, F. (2018). Adaptive-Horizon Iterative UFIR Filtering Algorithm with Applications. IEEE Transactions on Industrial Electronics, 65(8), 6393–6402. doi:10.1109/TIE.2017.2784405.

Dionelis, N., & Brookes, M. (2018). Phase-aware single-channel speech enhancement with modulation-domain Kalman filtering. IEEE/ACM Transactions on Audio Speech and Language Processing, 26(5), 937–950. doi:10.1109/TASLP.2018.2800525.

Luo, J., & Qin, S. (2018). A Fast Algorithm of SLAM Based on Combinatorial Interval Filters. IEEE Access, 6, 28174–28192. doi:10.1109/ACCESS.2018.2838112.

Rahmaniar, W., & Rakhmania, A. E. (2021). Online digital image stabilization for an unmanned aerial vehicle (UAV). Journal of Robotics and Control (JRC), 2(4), 234–239. doi:10.18196/jrc.2484.

Yin, L., Deng, Z., Huo, B., Xia, Y., & Li, C. (2018). Robust Derivative Unscented Kalman Filter under Non-Gaussian Noise. IEEE Access, 6, 33129–33136. doi:10.1109/ACCESS.2018.2846752.


Full Text: PDF

DOI: 10.28991/esj-2021-SP1-016

Refbacks

  • There are currently no refbacks.


Copyright (c) 2020 Iswanto Iswanto, Tony Khristanto Hariadi, Muhammad Abdus Shomad