Minimum electrical energy use in a multi-actuator system

Many modern industrial systems include more than one electrical motor; for example, cutting tools and 3D printers include positioning systems of linear actuators driven by motors. Reducing energy consumption is an increasing priority for all sectors including manufacturing industries. Conventionally during the off-cut operation, positioning systems are controlled in either rapid positioning mode or linear interpolation mode. In both these modes, motors are controlled independently from each other, leading to increased energy consumption or a rise in operational time. In this paper, a novel method of energy use minimization by controlling drives with respect to each other is presented. It utilizes the Model Predictive Control (MPC) technique to identify the optimal state trajectory. This trajectory is used as feed-forward to the classical cascaded controller. For the particular case studied, experimental results show 13% and 8% efficiency rises compared to the rapid positioning and linear positioning modes respectively. The technique is validated on a dual brushed DC motor system.

[1]  Dan M. Ionel,et al.  Saliency ratio and power factor of IPM motors optimally designed for high efficiency and low cost objectives , 2014, 2014 IEEE Energy Conversion Congress and Exposition (ECCE).

[2]  Seung-Ki Sul,et al.  Position control for direct landing of elevator using time-based position pattern generation , 2002, Conference Record of the 2002 IEEE Industry Applications Conference. 37th IAS Annual Meeting (Cat. No.02CH37344).

[3]  Maria Carmela Di Piazza,et al.  Techniques for efficiency improvement in PWM motor drives , 2016 .

[4]  Timothy G. Gutowski,et al.  An Environmental Analysis of Machining , 2004 .

[5]  Johann W. Kolar.  Future Challenges for Research and Teaching in Power Electronics , 2014 .

[6]  Claudio Melchiorri,et al.  Trajectory Planning for Automatic Machines and Robots , 2010 .

[7]  Hans-Peter Nee,et al.  High-efficiency three-phase inverter with SiC MOSFET power modules for motor-drive applications , 2014, 2014 IEEE Energy Conversion Congress and Exposition (ECCE).

[8]  Jan Swevers,et al.  A model predictive control approach for time optimal point-to-point motion control , 2011 .

[9]  Paul Mativenga,et al.  Modelling of direct energy requirements in mechanical machining processes , 2013 .

[10]  Sebastien Mariethoz.  Optimal control of a high efficiency low distortion 6-level hybrid multilevel motor drive , 2010, 2010 IEEE Vehicle Power and Propulsion Conference.

[11]  Jon Rigelsford,et al.  Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design , 2004 .

[12]  Jan M. Maciejowski,et al.  Predictive control : with constraints , 2002 .

[13]  Rida T. Farouki,et al.  Algorithms for time-optimal control of CNC machines along curved tool paths , 2005 .

[14]  Yusuf Altintas,et al.  High speed CNC system design. Part I: jerk limited trajectory generation and quintic spline interpolation , 2001 .