Abstract
In this paper, a control method for continuous time Direct Current (DC) servo motor, is presented based on adaptive dynamic programming. The core of this paper is the application of adaptive dynamic programming (ADP) to control the DC servo motor system. The program includes three main steps: (i) The mathematical model of DC servo motor system is established, and the feasibility of solving the problem with ADP is analyzed; (ii) On the basis of introducing the theory of ADP, we propose a solution to the problem; (iii) The simulation of the DC servo motor system is carried out. The contribution of this paper is that ADP, which is one of the most important methods in the field of optimal control, is used to solve the traditional problem. Finally, simulation study is conducted to verify the effectiveness of the presented algorithm.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bellman, R.: Dynamic Programming. Princeton University Press, Princeton (1957)
Zhang, H., Wei, Q., Luo, Y.: A novel infinite-time optimal tracking control scheme for a class of discrete-time nonlinear systems via the greedy HDP iteration algorithm. IEEE Trans. Syst. Man Cybern. Part B Cybern. 38(4), 937–942 (2008)
Zhang, H., Luo, Y., Liu, D.: Neural-network-based near-optimal control for a class of discrete-time affine nonlinear systems with control constraints. IEEE Trans. Neural Netw. 20(9), 1490–1503 (2009)
Zhang, H., Zhang, X., Luo, Y., Yang, J.: An overview of research on adaptive dynamic programming. Acta Autom. Sin. 39(4), 303–311 (2013)
Bertsekas, D.: Dynamic Programming and Optimal Control. Athena Scientific, Belmont (2015)
Lewis, F., Syrmos, V.: Optimal Control. Wiley, New York (1995)
Dreyfus, S., Law, A.: The Art and Theory of Dynamic Programming. Academic Press, New York (1977)
White, D., Sofge, A.: Handbook of Intelligent Control: Neural, Fuzzy, and Adaptive Approaches. Van Nostrand Reinhold, New York (1992)
Sozer, Y.: Direct Adaptive Control of Permanent Magnet Motors. Rensselaer Polytechnic Institute, The Office of Uraduate Studies of Rensselaer Polytechnic Institute (2000)
Zhu, Z.: Direct torque control of brushless DC drives with reduced torque ripple. IEEE Trans. Ind. Appl. 41(2), 599–605 (2005)
Zhou, L., Xie, Y.: The Present Situation and Prospect of Fuzzy Control in Speed Regulation System in AC Motor (2000)
Li, H., Tan, C., He, B.: Fuzzy control simulation of DC motor variable speed control system. S & M Electr. Mach. 30(1), 47–50 (2003)
Zeng, W., Zhu, P.: The Design of Speed Adjustment of a Mature Control DC Motor Using Pseudo-Derivative Feedback Algorithm (2005)
Gong, J., Ren, H., Liu, D.: Speed control of brushless DC motor drivers by load torque estimation. Electr. Mach. Control 9, 550 (2005)
Zhang, Y., Liang, G., Teng, F., Qiang, Z.: A Quick Load Estimation Design Based on an Adaptive Neural Network Observer for Direct Current Machine (2015)
Wei, Q., Liu, D., Lin, H.: Value iteration adaptive dynamic programming for optimal control of discrete-time nonlinear systems. IEEE Trans. Cybern. 46(3), 840–853 (2016)
Wei, Q., Liu, D., Lewis, F.L., Liu, Y.: Mixed iterative adaptive dynamic programming for optimal battery energy control in smart residential microgrids. IEEE Trans. Ind. Electr. 64(5), 4110–4120 (2017)
Wei, Q., Lewis, F.L., Liu, D., Song, R., Lin, H.: Discrete-time local value iteration adaptive dynamic programming: convergence analysis. IEEE Trans. Syst. Man Cybern. Syst. (2016, in press). doi:10.1109/TSMC.2016.2623766
Wei, Q., Liu, D., Lin, Q., Song, R.: Discrete-time optimal control via local policy iteration adaptive dynamic programming. IEEE Trans. Cybern. (2016, in press). doi:10.1109/TCYB.2016.2586082
Asma, A., Lewis, F., Abu-Khalaf, M.: Discrete-time nonlinear HJB solution using approximate dynamic programming: convergence proof. IEEE Trans. Syst. 38(4), 943–949 (2008)
Song, R., Xiao, W., Zhang, H., Sun, C.: Adaptive dynamic programming for a class of complex-valued nonlinear systems. IEEE Trans. Neural Netw. Learn. Syst. 25(9), 1733–1739 (2014)
Song, R., Lewis, F., Wei, Q., Zhang, H., Jiang, Z., Levine, D.: Multiple actor-critic structures for continuous-time optimal control using input-output data. IEEE Trans. Neural Netw. Learn. Syst. 26(4), 851–865 (2015)
Song, R., Lewis, F., Wei, Q., Zhang, H.: Off-policy actor-critic structure for optimal control of unknown systems with disturbances. IEEE Trans. Cybern. 46(5), 1041–1050 (2016)
Song, R., Lewis, F., Wei, Q.: Off-policy integral reinforcement learning method to solve nonlinear continuous-time multi-player non-zero-sum games. IEEE Trans. Neural Netw. Learn. Syst. 28(3), 704–713 (2017)
Acknowledgments
This research was supported in part by the National Natural Science Foundation of China under Grant 61673054, and in part by the Open Research Project from SKLMCCS under Grant 20150104.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Zhu, L., Song, R., Xie, Y., Li, J. (2017). Adaptive Dynamic Programming for Direct Current Servo Motor. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10634. Springer, Cham. https://doi.org/10.1007/978-3-319-70087-8_75
Download citation
DOI: https://doi.org/10.1007/978-3-319-70087-8_75
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-70086-1
Online ISBN: 978-3-319-70087-8
eBook Packages: Computer ScienceComputer Science (R0)