Abstract
Speed control and stability are the most important factors in the working of every motor. Several controlling strategies improve motor stability and increase efficiency. Some of the conventional control methods, which have disadvantages, make uncontrollable situations occur in the DC compound motor. The implementation of modern improvised techniques can fill those gaps of disadvantages occurred by conventional control methods. This paper explains how the proposed control mechanism can effectively control the speed of a DC compound motor, by using the concept of virtual inertia injection. Through this concept, the speed of the DC compound motor is going to be controlled by virtually injecting the inertia through the proposed controller design made using one of the artificial intelligence techniques called the fuzzy logic method. The proposed control technique is compared with conventional techniques, and conclusions are drawn based on the results acquired in the simulation. The whole simulation is done using MATLAB-Simulink®.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Moyer J, Chicago U (2010) Basics on electric motors
Kumar SB, Ali MH, Sinha A (2014) Design and simulation of speed control of DC motor by fuzzy logic technique with Matlab Simulink. Int J Sci Res Publ 4(7):2–5
Piuri V, Scotti F (2007) Implementations of computational intelligence techniques
Omara AM, Sleptsov M, Zaki Diab AA (2018) Cascaded fuzzy logic based direct torque control of interior permanent magnet synchronous motor for variable speed electric drive systems. In: 25th International workshop on electric drives: optimization in control of electric drives (IWED)
Togashi R, Inoue Y, Morimoto S, Sanada M (2014) Performance improvement of ultra-high-speed PMSM drive system based on DTC by using SiC inverter. In: International power electronics conference
Ciurys MP (2017) Brushless DC motor with a vane pump built in and with speed control using PWM method. In: 18th international symposium on electromagnetic fields in mechatronics, electrical and electronic engineering (ISEF)
Sree Vishnu Vardhan D, Raghava Sai Phanindra D, Pavan Kumar YV (2020) Effective speed control of DC compound motor using artificial neural network-based virtual inertia injection. Soft Comput Prob Solving
Rubaai A, Raj K (2000) Online identification and control of a DC motor using learning adaptation of neural networks. IEEE Trans Ind Appl 36(3)
Zhu M, Zhou G, Ma J, Song N, Mu Y, Gao J, Xu Y (2019) Research on moment of inertia identification and PI parameter self-tuning of speed control system for the permanent magnet synchronous motor. In: Chinese automation congress
Wang K, Wang Y (2010) Application of optimization technology to identify moments of inertia of body or high speed forklift. In: 3rd international conference on advanced computer theory and engineering
Fedor T, Vittel J, Sindler P (2014) Influence of variable moment of inertia in robot servo motor control. ELEKTRO conference
Krause P, Wasynczuk O, Sudhoff S, Pekarek S (2013) Analysis of electric machinery and drive systems, 3rd edn. IEEE Press
Gude JJ, Kahoraho E (2010) Modified Ziegler-Nichols method for fractional PI controllers. In: IEEE 15th conference on emerging technologies & factory automation
Khan AA, Rapal N (2006) Fuzzy PID controller: design, tuning and comparison with conventional PID controller. In: IEEE international conference on engineering of intelligent systems
Fahassa C, Sayouti Y, Akherraz M (2015) Improvement of the induction motor drive’s indirect field oriented control performance by substituting its speed and current controllers with fuzzy logic components. In: 3rd international renewable and sustainable energy conference
Devi K, Singh R, Gautamb S, Nagaria D (2015) Speed control of induction motor using fuzzy logic approach. Int J Adv Res Innov 3(4)
Rao KS, Praneeth VNS, Kumar YVP (2021) Fuzzy logic-based intelligent PID controller for speed control of linear internal combustion engine. In: Innovations in electrical and electronic engineering, pp 505–521
Sharma AK, Singh V, Verma NK, Liu J (2018) Condition based monitoring of machine using Mamdani fuzzy network. In: Prognostics and system health management conference
Kumar YVP, Bhimasingu R (2017) Fuzzy logic based adaptive virtual inertia in droop control operation of the microgrid for improved transient response. In: IEEE PES Asia-Pacific power and energy engineering conference
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Vardhan, D.S.V., Kumar, Y.V.P. (2024). Improved Speed Control of DC Compound Motor with Fuzzy Logic Control-Based Virtual Inertia Injection. In: Mahajan, V., Chowdhury, A., Singh, S.N., Shahidehpour, M. (eds) Emerging Technologies in Electrical Engineering for Reliable Green Intelligence. ICSTACE 2023. Lecture Notes in Electrical Engineering, vol 1117. Springer, Singapore. https://doi.org/10.1007/978-981-99-9235-5_8
Download citation
DOI: https://doi.org/10.1007/978-981-99-9235-5_8
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-9234-8
Online ISBN: 978-981-99-9235-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)