Research Papers

A Framework for Control of Robots With Energy Regeneration

[+] Author and Article Information
Hanz Richter

Associate Professor
Mechanical Engineering Department,
Cleveland State University,
Cleveland, OH 44115
e-mail: h.richter@csuohio.edu

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received February 24, 2014; final manuscript received April 6, 2015; published online June 2, 2015. Assoc. Editor: Heikki Handroos.

J. Dyn. Sys., Meas., Control 137(9), 091004 (Sep 01, 2015) (11 pages) Paper No: DS-14-1090; doi: 10.1115/1.4030391 History: Received February 24, 2014; Revised April 06, 2015; Online June 02, 2015

This paper focuses on robot control problems where energy regeneration is an explicit consideration, and it proposes a methodology for modeling and control design of regenerative motion control systems. The generic model consists of a robotic manipulator where some joints are actively controlled and the remaining joints are energetically self-contained and semi-actively controlled. The model can capture various electromechanical and hydraulic actuator configurations for industrial robots and powered human-assist devices. The basic control approach consists of three steps. First, a virtual control design is conducted by any suitable means. Then, virtual control inputs are enacted by a matching law for the adjustable parameters of the semi-active joints. Finally, the energy storage dynamics are adjusted using design parameters and an optional outer supervisory loop. The method has several attractive features: design simplicity, amenability to simultaneous plant and control design optimization, explicit treatment of energy regeneration, and applicability to multiple domains. This paper emphasizes electromechanical robots whose semi-active joints use ultracapacitors as the single energy storage medium. An internal energy balance equation and associated ideal self-powered operation (ISPO) condition are given for the semi-active joints. This condition is a structural characteristic of the system and independent of the control law. Extensions to handle higher-order dynamics are presented. Also, it is shown that discrepancies between virtual and actual controls can be mapped to parametric uncertainty in the virtual design. Experimental results confirm the validity of the approach.

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Fig. 1

Robotic manipulator configuration assumed throughout this work. There are n joints, of which the first n − m are fully actuated and the remaining m are semi-actuated.

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Fig. 2

Schematic of active and semi-active joints. Half-arrows denote bidirectional power flow, with power following the direction of the arrow when positive.

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Fig. 3

Schematic of inline (electromechanical example) and crank–slider (hydraulic example) joints. The bond graph captures the mechanical input stage of either design.

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Fig. 4

Schematic and bond graph of conversion, modulation, and storage elements in the electromechanical semi-active JM

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Fig. 5

Bond graph of conversion, modulation, and storage elements in the hydraulic semi-active JM

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Fig. 7

Sinewave tracking experiments: fully active and semi-active virtual control results

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Fig. 8

Sinewave tracking experiments: source power in active and semi-active approaches

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Fig. 9

Semi-active control with manually applied disturbance torque estimated by dynamic model inversion

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Fig. 10

Semi-active control with manually applied disturbance torque: ultracapacitor power

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Fig. 6

PUMA 560 robot used in simulation studies and experiments



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