Research Papers

Nonlinear Model Predictive Control of Axial Piston Pumps

[+] Author and Article Information
Paul Zeman

Automation and Control Institute,
TU Wien,
Gußhausstraße 27-29/376,
Vienna 1040, Austria
e-mail: zeman@acin.tuwien.ac.at

Wolfgang Kemmetmüller

Automation and Control Institute,
TU Wien,
Gußhausstraße 27-29/376,
Vienna 1040, Austria
e-mail: kemmetmueller@acin.tuwien.ac.at

Andreas Kugi

Automation and Control Institute,
TU Wien,
Gußhausstraße 27-29/376,
Vienna 1040, Austria
e-mail: kugi@acin.tuwien.ac.at

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received September 27, 2016; final manuscript received December 13, 2016; published online May 24, 2017. Assoc. Editor: Shankar Coimbatore Subramanian.

J. Dyn. Sys., Meas., Control 139(8), 081008 (May 24, 2017) (11 pages) Paper No: DS-16-1465; doi: 10.1115/1.4035608 History: Received September 27, 2016; Revised December 13, 2016

Variable displacement axial piston units are the core components of many hydrostatic and hydraulic hybrid drive trains. Therein, the fast and accurate control of the swash plate angle, utilizing the full possible dynamics of the displacement system, is essential for a good performance of the overall drive train. This paper describes the development, implementation, and the experimental validation of a control strategy for the swash plate angle based on nonlinear model predictive control (NMPC). A tailored mathematical model, which serves as the basis for the NMPC, is described in the first part of the paper. Two versions of NMPC, an indirect and a direct method, are compared with respect to their numerical complexity and their capability of handling input and state constraints. An observer strategy, which is designed to obtain the nonmeasurable states and varying parameters of the system, completes the overall control strategy. To reduce the negative influence of stick–slip friction, the concept of dithering is applied in the experimental implementation. The differences of the NMPC methods are analyzed by simulation studies and experiments. Finally, the experimental results, using an industrial electronic control unit (ECU), prove the practical feasibility and the improved control accuracy and robustness in comparison to classical (nonlinear) control strategies.

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Fig. 1

Sketch of the APU with the electro-hydraulic displacement system [9]

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Fig. 2

Electric and hydro-mechanical subsystem for the observer design

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Fig. 3

Structure of the overall control strategy

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Fig. 4

Simulation of I-NMPC for the unconstrained case x∞+ (N = 1) and the constrained case x1+ (N ∈ {1, 2, 5}) with ph = 150 bar

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Fig. 5

Simulation of D-NMPC (N = 1) for the unconstrained case x∞+ and the constrained cases x1+, x2+ with ph = 150 bar (left) and ph = 350 bar (right)

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Fig. 6

I-NMPC: influence of parameter uncertainties on the control accuracy and on the state estimates of Σ̂h (left) and Σ̂e (right)

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Fig. 7

Sketch of the test stand including the control strategy implemented on the electronic control unit (ECU) and the APU with the electro-hydraulic displacement system (EHDS)

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Fig. 8

Experimental results of I-NMPC for the case without state constraints using step-like and triangular reference signals

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Fig. 9

I-NMPC: influence of the input constraint |um|≤u+

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Fig. 10

D-NMPC: influence of the current constraint |im|≤i¯m

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Fig. 11

Experimental results of a classical nonlinear control strategy



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