Distributed event-triggered communication for angular speed synchronization of networked BLDC motors

[EN] This work presents the design and implementation of a collaborative and decentralized control for synchronizing the angular velocity of a group of spatially distributed brushless direct current (BLDC) motors. Via an Active Disturbance Rejection Control (ADRC), acting as an internal-loop, the dynamics of the BLDC can be assimilated to that of a first-order integrator, which is considered an agent. Then, a decentralized collaborative control strategy with event-triggered communication is proposed, which solves the problem of leader-follower consensus for the multi-agent system and thus speed synchronization. The communication topology between agents is modeled using an undirected and connected graph. The decentralized control law incorporates an event function, which indicates the instant at which the i-th agent transmits the angular velocity information to its neighbor. An experimental platform using two BLDC and a virtual leader was developed to validate the proposed approach. The experimental results show excellent performance for angular velocity consensus for regulation tasks, while the bandwidth usage is only 1.25 % regarding a periodic communication implementation.[ES] Este trabajo presenta el diseño e implementación de un control colaborativo descentralizado para la sincronización de velocidad angular de un conjunto de motores de corriente continua sin escobillas (BLDC) distribuidos espacialmente. Apoyándose de un control por rechazo activo de perturbaciones, actuando como un bucle interno, la dinámica del BLDC puede asimilarse a la de un integrador de primer orden y el cual será considerado un agente. Se propone entonces una estrategia de control colaborativo descentralizado con una comunicación activada por eventos, que resuelve el problema del consenso líder-seguidor del sistema multi-agente y, con ello, la sincronización de velocidades entre motores. La topología de comunicación entre agentes se modela usando un grafo conectado y no dirigido. La ley de control descentralizado incorpora una función de evento, que indica el instante en el que $i$-ésimo agente transmite la información de velocidad angular a su vecino. El intercambio asíncrono de información permite reducir el tráfico de datos en la red de comunicaciones, lo que permite aprovechar el ancho de banda. Al analizar la dinámica de la trayectoria del error del sistema, se establece que el vector de error del sistema multi-agente tiende de forma exponencial y permanece confinado a una vecindad del origen del espacio de estados de error. Aunque la estrategia está diseñada para n-agentes, se desarrolló una plataforma experimental compuesta por dos motores y un líder virtual, permitiendo validar la estrategia. Los resultados experimentales muestran un excelente desempeño del consenso de velocidad angular de ambos motores BLDC para tareas de regulación, mientras que el uso del ancho de banda es de solamente 1.25 % con respecto a una implementación de comunicación periódica.Hernández-Méndez, A.; Guerrero-Castellanos, J.; Orozco-Urbieta, T.; Linares-Flores, J.; Mino-Aguilar, G.; Curiel, G. (2021). Comunicación distribuida activada por eventos para la sincronización de velocidad angular de motores BLDC en red. Revista Iberoamericana de Automática e Informática industrial. 18(4):360-370. https://doi.org/10.4995/riai.2021.14989OJS360370184Ahmed, N., Cortes, J., Martinez, S., 2016. Distributed control and estimation of robotic vehicle networks: Overview of the special issue-part II. IEEE Control Systems 36 (4), 18-21. https://doi.org/10.1109/MCS.2016.2558398Aranda-Escolástico, E., Guinaldo, M., Heradio, R., Chacon, J., Vargas, H., Sánchez, J., Dormido, S., 2020. Event-based control: A bibliometric analysis of twenty years of research. IEEE Access 8, 47188-47208. https://doi.org/10.1109/ACCESS.2020.2978174Bullo, F., Cortés, J., Martinez, S., 2009. Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms: A Mathematical Approach to Motion Coordination Algorithms. Princeton University Press.https://doi.org/10.1515/9781400831470Chaari, R., Ellouze, F., Koubaa, A., Qureshi, B., Pereira, N., Youssef, H., Tovar, E., 2016. Cyber-physical systems clouds: A survey. Computer Networks 108, 260 - 278. https://doi.org/10.1016/j.comnet.2016.08.017Dimarogonas, D. V., Frazzoli, E., 2009. Distributed event-triggered control strategies for multi-agent systems. In: Communication, Control, and Computing, 2009. Allerton 2009. 47th Annual Allerton Conference on. IEEE, pp. 906-910. https://doi.org/10.1109/ALLERTON.2009.5394897Fuentes, G. A. R., Cortés-Romero, J. A., Zou, Z., Costa-Castelló, R., Zhou, K., 2015. Power active filter control based on a resonant disturbance observer. IET Power Electronics 8 (4), 554-564. https://doi.org/10.1049/iet-pel.2014.0032Garcia, E., Cao, Y., Wang, X., Casbeer, D. W., July 2015. Decentralized eventtriggered consensus of linear multi-agent systems under directed graphs. In: 2015 American Control Conference (ACC). pp. 5764-5769. https://doi.org/10.1109/ACC.2015.7172242Guerrero-Castellanos, J., Rifaï, H., Arnez-Paniagua, V., Linares-Flores, J., Saynes-Torres, L., Mohammed, S., 2018. Robust active disturbance rejection control via control lyapunov functions: Application to actuated-ankle-footorthosis. Control Engineering Practice 80, 49 - 60. https://doi.org/10.1016/j.conengprac.2018.08.008Guerrero-Castellanos, J., Vega-Alonzo, A., Durand, S., Marchand, N., Gonzalez-Diaz, V., Casta˜neda-Camacho, J., Guerrero-Sánchez, W., 2019. Leader-following consensus and formation control of vtol-uavs with eventtriggered communications. Sensors 19 (24), 1-26. https://doi.org/10.3390/s19245498Guinaldo, M., Dimarogonas, D. V., Johansson, K. H., S'anchez, J., Dormido, S., 2013. Distributed event-based control strategies for interconnected linear systems. Control Theory & Applications, IET 7 (6), 877-886. https://doi.org/10.1049/iet-cta.2012.0525Guzey, H. M., Dumlu, A., Guzey, N., Alpay, A., April 2018. Optimal synchronizing speed control of multiple dc motors. In: 2018 4th International Conference on Optimization and Applications (ICOA). pp. 1-5. https://doi.org/10.1109/ICOA.2018.8370508Han, J., 2009. From pid to active disturbance rejection control. Transactions on Industry Electronics 56 (3), 900-906. https://doi.org/10.1109/TIE.2008.2011621Hebertt Sira-Ramírez, Alberto Luviano-Juárez, M. R.-N. E.-W. Z.-B., 2017. Active Disturbance Rejection Control of Dynamic Systems. Butterworth- Heinemann.Hernandez-Méndez, A., Linares-Flores, J., Sira-Ramírez, H., Guerrero-Castellanos, J., Mino-Aguilar, G., 2017. A backstepping approach to decentralized active disturbance rejection control of interacting boost converters. Transactions on Industry Applications 53 (4), 4063-4072. https://doi.org/10.1109/TIA.2017.2683441Lee, J., Bagheri, B., Kao, H.-A., 2015. A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufacturing Letters 3, 18- 23. https://doi.org/10.1016/j.mfglet.2014.12.001Lewis, F. L., Zhang, H., Hengster-Movric, K., Das, A., 2013. Cooperative control of multi-agent systems: optimal and adaptive design approaches. Springer Science & Business Media. https://doi.org/10.1007/978-1-4471-5574-4Marchand, N., Durand, S., Guerrero-Castellanos, J. F., 2013. A general formula for event-based stabilization of nonlinear systems. Automatic Control, IEEE Transactions on 58 (5), 1332-1337. https://doi.org/10.1109/TAC.2012.2225493Miskowicz, M., 2015. Event-Based Control and Signal Processing. CRC Press.Neenu, T., Poongodi, P., 07 2009. Position control of dc motor using genetic algorithm based pid controller. Lecture Notes in Engineering and Computer Science 2177.Olfati-Saber, R., Murray, R. M., 2004a. Consensus problems in networks of agents with switching topology and time-delays. Automatic Control, IEEE Transactions on 49 (9), 1520-1533. https://doi.org/10.1109/TAC.2004.834113Olfati-Saber, R., Murray, R. M., Sep. 2004b. Consensus problems in networks of agents with switching topology and time-delays. IEEE Transactions on Automatic Control 49 (9), 1520-1533. https://doi.org/10.1109/TAC.2004.834113Ren, W., Beard, R. W., 2008. Distributed consensus in multi-vehicle cooperative control. Springer. https://doi.org/10.1007/978-1-84800-015-5Sánchez-Santana, J., Guerrero-Castellanos, J., Villarreal-Cervantes, M., Ramırez-Martınez, S., 2018. Control distribuido y disparado por eventos para la formación de robots m'oviles tipo (3, 0)?. In: Congreso Nacional de Control Automático.Seyboth, G. S., Dimarogonas, D. V., Johansson, K. H., 2013. Event-based broadcasting for multi-agent average consensus. Automatica 49 (1), 245-252. https://doi.org/10.1016/j.automatica.2012.08.042Shi, T., Liu, H., Geng, Q., Xia, C., 2016. Improved relative coupling control structure for multi-motor speed synchronous driving system. IET Electric Power Applications 10 (6), 451-457. https://doi.org/10.1049/iet-epa.2015.0515Sira-Ramírez, H., Hernández-Méndez, A., Linares-Flores, J., Luviano-Juarez, A., 2016. Robust flat filtering dsp based control of the boost converter. Control Theory and Technology 14 (3), 224-236. https://doi.org/10.1007/s11768-016-6025-6Sira-Ramírez, H., Linares-Flores, J., Luviano-Juárez, A., Cortés-Romero, J., 2015. Ultramodelos globales y el control por rechazo activo de perturbaciones en sistemas no lineales diferencialmente planos. Revista Iberoamericanade Automática e Informática Industrial RIAIg 12 (2), 133 - 144. https://doi.org/10.1016/j.riai.2015.02.001Song, H., Rawat, D. B., Jeschke, S., Brecher, C., 2017. Front matter. In: Cyber- Physical Systems. Intelligent Data-Centric Systems. Academic Press, Boston, pp. i - ii.Sun, J., Liu, R., Luo, Y., Sun, W., 2009. Research on multi-motor synchronization control for cutter head of shield machine based on the ring coupled control strategy. In: Xie, M., Xiong, Y., Xiong, C., Liu, H., Hu, Z. (Eds.), Intelligent Robotics and Applications. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 345-354. https://doi.org/10.1007/978-3-642-10817-4_34Tao, L., Chen, Q., Nan, Y., Dong, F., Jin, Y., 09 2018. Speed tracking and synchronization of a multimotor system based on fuzzy adrc and enhanced adjacent coupling scheme. Complexity 2018, 1-16. https://doi.org/10.1155/2018/5632939Torres, F. J., Guerrero, G. V., García, C. D., Gomez, J. F., Adam, M., Escobar, R. F., Sep. 2016. Master-slave synchronization of robot manipulators driven by induction motors. IEEE Latin America Transactions 14 (9), 3986-3991. https://doi.org/10.1109/TLA.2016.7785923Valenzuela, A., Lorenz, R., 02 2001. Electronic line-shafting control for paper machine drives. Industry Applications, IEEE Transactions on 37, 158 - 164. https://doi.org/10.1109/28.903141Xia, C. L., 2012. Permanent magnet brushless DC motor drives and controls. John Wiley & Sons. https://doi.org/10.1002/9781118188347Xie, D., Xu, S., Zhang, B., Li, Y., Chu, Y., 2016. Consensus for multi-agent systems with distributed adaptive control and an event-triggered communication strategy. IET Control Theory Applications 10 (13), 1547-1555. https://doi.org/10.1049/iet-cta.2015.1221Yang, D., Ren,W., Liu, X., Dec 2014. Decentralized consensus for linear multiagent systems under general directed graphs based on event-triggered/selftriggered strategy. In: 53rd IEEE Conference on Decision and Control. pp. 1983-1988. https://doi.org/10.1109/CDC.2014.7039689Yu, H., Xi, J.-Q., Zhang, F., Hu, Y.-h., 02 2014. Research on gear shifting process without disengaging clutch for a parallel hybrid electric vehicle equipped with amt. Mathematical Problems in Engineering 2014, 1-12. https://doi.org/10.1155/2014/985652Zhang, C., Wu, H., He, J., Xu, C., 2015. Consensus tracking for multi-motor system via observer based variable structure approach. Journal of the Franklin Institute 352 (8), 3366 - 3377, special Issue on Advances in Nonlinear Dynamics and Control. https://doi.org/10.1016/j.jfranklin.2015.01.035Zhang, C.-H., Shi, Q.-S., Cheng, J., 01 2007. Design of fuzzy neural network controller for synchronization drive in multi-motor systems 22, 30-34.Zhang, X., Zhang, J., 2014. Distributed event-triggered control of multiagent systems with general linear dynamics. Journal of Control Science and Engineering 2014, 7. https://doi.org/10.1155/2014/698546Zhao, D., Li, C., Ren, J., 12 2009a. Speed synchronization of multiple induction motors with adjacent cross coupling control. pp. 6805-6810.Zhao, D.-Z., wen LI, C., REN, J., 2009b. Speed synchronization of multiple induction motors with total sliding mode control. Systems Engineering - Theory & Practice 29 (10), 110 - 117. https://doi.org/10.1016/S1874-8651(10)60077-4Zhao, G., Zhuang, B., Zheng, G., Zhao, Y., 09 2017. Cross-coupling control method for five-axis computer numerical control machine with dual rotary tables. Advances in Mechanical Engineering 9. https://doi.org/10.1177/1687814017733689Zhou, F., Huang, Z., Yang, Y., Wang, J., Li, L., Peng, J., 2017. Decentralized event-triggered cooperative control for multi-agent systems with uncertain dynamics using local estimators. Neurocomputing 237, 388 - 396. https://doi.org/10.1016/j.neucom.2017.01.02

Industrial and Technological Applications of Power Electronics Systems

The Special Issue "Industrial and Technological Applications of Power Electronics Systems" focuses on: - new strategies of control for electric machines, including sensorless control and fault diagnosis; - existing and emerging industrial applications of GaN and SiC-based converters; - modern methods for electromagnetic compatibility. The book covers topics such as control systems, fault diagnosis, converters, inverters, and electromagnetic interference in power electronics systems. The Special Issue includes 19 scientific papers by industry experts and worldwide professors in the area of electrical engineering

Speed Tracking and Synchronization of a Multimotor System Based on Fuzzy ADRC and Enhanced Adjacent Coupling Scheme

In this paper, a speed tracking and synchronization control approach is proposed for a multimotor system based on fuzzy active disturbance rejection control (FADRC) and enhanced adjacent coupling scheme. By employing fuzzy logic rules to adjust the coefficients of the extended state observer (ESO), FADRC is presented to guarantee the speed tracking performance and enhance the system robustness against external disturbance and parametric variations. Moreover, an enhanced adjacent coupling synchronization control strategy is proposed to simplify the structure of the speed synchronization controller through introducing coupling coefficients into the conventional adjacent coupling approach. Based on the proposed synchronization control scheme, an adaptive integral sliding mode control (AISMC) is investigated such that the chattering problem in conventional sliding mode control can be weakened by designing an adaptive estimation law of the control gain. Comparative simulations are carried out to prove the superiorities of the proposed method