Adaptive collaborative speed control of PMDC motor using hyperbolic secant functions and particle swarm optimization

This paper presents an adaptive collaborative speed controller for a permanent magnet direct-current (PMDC) motor. The proposed scheme beneficially combines the control efforts of a proportional-integral (PI) controller and a linear-quadratic regulator (LQR) via a weighted summing module. Initially, the weightages of the summing module are kept fixed. They are optimally tuned and tested via the particle swarm optimization algorithm. In order to synergize the controller combination, these weightages are adaptively modulated as well, using hyperbolic secant functions of the error dynamics of the motor’s angular speed. The adaptive combination renders significant enhancement in the transient response, steady-state response, input-energy consumption, disturbance rejection, and variable load-torque handling capability of the motor. The adaptive-weighted controller is tested against the PI controller, the LQR, and a fixed-weighted collaborative controller via ‘hardware-in-the-loop’ experiments. The experimental results are presented to validate the robustness of the adaptive controller.

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Salawria P, Lodhi RS, Nema P. Implementation of PSO-based optimum controller for speed control of BLDC motor. International Journal of Electrical, Electronics & Computer Science Engineering 2017; 6: 104-109.
Isayed BM, Hawwa MA. A nonlinear PID control scheme for hard disk drive servosystems. In: 2007 15th Mediterranean Conference on Control & Automation; 27–29 July 2007; Athens, Greece. New York, NY, USA: IEEE. pp. 1-6.
Pedroso MD, Nascimento CB, Tusset AM, Kaster MS. Performance comparison between nonlinear and linear controllers with weighted adaptive control applied to a buck converter using poles placement design. In: IEEE International Symposium on Industrial Electronics; 28–31 May 2013; Taipei, Taiwan. New York, NY, USA: IEEE, pp. 1-6.
Saisudha V, Seeja G, Pillay RV, Manikutty G, Bhavani RR. Analysis of speed control of DC motor using LQR method. Int J Control Theory Appl 2016; 9: 7377-7385.
Ganzaroli CA, Carvalho DF, Dias RNHM, Reis MRC, Alves AJ, Domingos JL, Calixto WP. Heuristic and deterministic strategies applied on cascade PI controller tuning for speed control of a DC motor. In: 2015 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies; 28–30 October 2015; Santiago, Chile. New York, NY, USA: IEEE. pp. 101-106.
Ruderman M, Krettek J, Hoffmann F, Bertram T. Optimal state space control of DC motor. In: 2008 17th World Congress of the International Federation of Automatic Control; 6–11 July 2008; Seoul, Korea. New York, NY, USA: IEEE. pp. 5796-5801.
Abbas AN. Design and implementation of close loop DC motor speed control based on Labview. Int J Enhanc Res Eng Sci Technol 2014; 3: 354-361.
Engle BJ, Watkins JM. A software platform for implementing digital control experiments on the Quanser DC motor control trainer. In: 2008 17th International Conference on Control Applications; 3–5 September 2008; Texas, USA. New York, NY, USA: IEEE. pp. 510-515.
Guo B, Hu L, Bai Y. A nonlinear PID controller with tracking differentiator applying in BLDCM servo system. In: 2012 7th International Power Electronics and Motion Control Conference; 2–5 June 2012; Harbin, China. New York, NY, USA: IEEE. pp. 2467-2471.
Seraji H. A new class of non-linear PID controller with robotic applications. J Robot Syst 1998; 15: 161-181.
Zhou Y, Shang W, Liu M, Li X, Zeng Y. Simulation of PMSM vector control based on a self-tuning fuzzy PI controller. In: 8th International Conference on Biomedical Engineering and Informatics; 14–16 October 2015; Shenyang, China. New York, NY, USA: IEEE. pp. 609-613.
Pedroso MD, Nascimento CB, Tusset AM, Kaster MS. A hyperbolic tangent adaptive PID + LQR control applied to a step-down converter using poles placement design implemented in FPGA. Math Probl Eng 2013; 2013: 101650.
Kanojiya GR, Meshram PM. Optimal tuning of PI controller for speed control of DC motor drive using particle swarm optimization. In: 2012 International Conference on Advances in Power Conversion and Energy Technologies; 2–4 August 2012; Andhra Pradesh, India. New York, NY, USA: IEEE. pp. 1-6.
Navidi N, Bavafa M, Hesami S. A new approach for designing of PID controller for a linear brushless DC motor with using ant colony search algorithm. In: 2009 Asia-Pacific Power and Energy Engineering Conference; 27–31 March 2009; Wuhan, China. New York, NY, USA: IEEE. pp. 1-5.
Youns MD, Abdulla AI, Attya SM. Optimization control of DC motor with linear quadratic regulator and genetic algorithm approach. Tikrit J Eng Sci 2013; 20: 35-42.
Bagheri S, Jafarov T, Freidovich L, Sepehri N. Beneficially combining LQR and PID to control longitudinal dynamics of a SmartFly UAV. In: 2016 7th Annual Information Technology, Electronics and Mobile Communication Conference; 13–15 October 2016; Vancouver, Canada. New York, NY, USA: IEEE. pp. 1-6.
Yassine B, Fatiha Z, Chrifi-Alaoui L. LQR-PI controller dedicated to the indirect vector control without speed sensor for an asynchronous motor. In: 2015 16th International Conference on Sciences and Techniques of Automatic Control & Computer Engineering; 21–23 December 2015; Monastir, Tunisia. New York, NY, USA: IEEE. pp. 634-640.
Ismail RMTR, Ahmad MA, Ramli MS. Speed control of buck-converter driven DC motor using LQR and PI: a comparative assessment. In: 2009 International Conference on Information Management and Engineering; 3–5 April 2009; Kuala Lumpur, Malaysia. New York, NY, USA: IEEE. pp. 651-656
Srivastaval S, Pandit VS. A scheme to control the speed of a DC motor with time delay using LQR-PID controller. In: 2015 International Conference on Industrial Instrumentation and Control; 28–30 May 2015; Pune, India. New York, NY, USA: IEEE. pp. 294-299.
Saleem O, Omer U. EKF-based self-regulation of an adaptive nonlinear PI speed controller for a DC motor. Turk J Elec Eng & Comp Sci 2017; 25: 4131-4141.
Swargiary M, Dey J, Saha TK. Optimal speed control of induction motor based on linear quadratic regulator theory. In: 2015 Annual IEEE India Conference; 17–20 December 2015; New Delhi, India. New York, NY, USA: IEEE. pp. 1-6.
Chebre M, Meroufel A, Bendaha Y. Speed control of induction motor using genetic algorithm-based PI controller. Acta Polytech Hungar 2011; 8: 141-153.
Inoan I, Abrudean M. Control of an induction motor using the relay method approach. Control Eng Appl Inform 2014; 16: 13-22.
Kahveci H, Okumu¸s HI, Ekici M. Improved brushless DC motor speed controller with digital signal processor. IET Electron Lett 2014; 50: 864-866.
Ahmed H, Rajoriya A. A hybrid of sliding mode control and fuzzy logic control using a fuzzy supervisory switched system for DC motor speed control. Turk J Elec Eng & Comp Sci 2017; 25: 1993-2004.
Dal M. Enhancing sliding mode control with proportional feedback and feedforward: an experimental investigation on speed sensorless control of PM DC motor drives. Turk J Elec Eng & Comp Sci 2015; 23: 126-148.
Khooban MH, Shasadeghi M, Niknam T, Blaabjerg F. Analysis, control and design of speed control of electric vehicles delayed model: multiobjective fuzzy fractional-order PI λ D µ controller. IET Sci Meas Technol 2017; 11: 249-261.
Rajesh D, Ravikumar D, Bharadwaj SK, Vastav BKS. Design and control of digital DC drives in steel rolling mills. In: 2016 International Conference on Inventive Computation Technologies; 26–27 August 2016; Coimbatore, India. New York, NY, USA: IEEE. pp. 1-5.