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Research Papers

Adaptive and Nonlinear Control of Discharge Pressure for Variable Displacement Axial Piston Pumps

[+] Author and Article Information
Janne Koivumäki

Laboratory of Automation and Hydraulics (AUT),
Tampere University of Technology (TUT),
Korkeakoulunkatu 6,
Tampere 33720, Finland
e-mail: janne.koivumaki@tut.fi

Jouni Mattila

Laboratory of Automation and Hydraulics (AUT),
Tampere University of Technology (TUT),
Korkeakoulunkatu 6,
Tampere 33720, Finland
e-mail: jouni.mattila@tut.fi

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received April 14, 2016; final manuscript received March 9, 2017; published online June 28, 2017. Assoc. Editor: Yongchun Fang.

J. Dyn. Sys., Meas., Control 139(10), 101008 (Jun 28, 2017) (16 pages) Paper No: DS-16-1188; doi: 10.1115/1.4036537 History: Received June 11, 2016; Revised March 23, 2017

This paper proposes, for the first time without using any linearization or order reduction, an adaptive and model-based discharge pressure control design for the variable displacement axial piston pumps (VDAPPs), whose dynamical behaviors are highly nonlinear and can be described by a fourth-order differential equation. The rigorous stability proof, with an asymptotic convergence, is given for the entire system. In the proposed novel controller design method, the specifically designed stabilizing terms constitute an essential core to cancel out all the stability-preventing terms. The experimental results reveal that rapid parameter adaptation significantly improves the feedback signal tracking precision compared to a known-parameter controller design. In the comparative experiments, the adaptive controller design demonstrates the state-of-the-art discharge pressure control performance, enabling a possibility for energy consumption reductions in hydraulic systems driven with VDAPP.

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Figures

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Fig. 1

Decomposed subsystems and system control setup

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Fig. 2

Operating principle of the variable displacement axial piston pump

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Fig. 3

The mapping between the controlling variable uc and the controlled variable ps

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Fig. 4

The diagram of the designed adaptive control system for the VDAPP controlling the discharge pressure. The error signals are highlighted in bold and the feedback variables are highlighted with the dashed line.

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Fig. 5

Experimental installation for the experiments. The auxiliary supply line is highlighted in blue, the fluid return line is highlighted in green, the line between the control valve and the VDAPP is highlighted in red, and the line for an additional fluid flow rate Qadd is highlighted in yellow.

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Fig. 6

The inherent oscillatory behavior of the VDAPP's discharge pressure and control piston chamber pressure

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Fig. 7

The known-parameter control design. The system discharge pressure tracking performance is shown in plots 1 and 2. The measured (normalized) swash plate angle is shown in plot 3. The control valve voltage (the controller output) is shown in plot 4.

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Fig. 8

The tracking performance of the system's subsidiary feedback variables p˙s, α˙, and pcp with the known-parameter control design. The reference trajectories are given in black (—) and their feedback variables are given in red ().

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Fig. 9

The adaptive control design. The system discharge pressure tracking performance is shown in plots 1 and 2. The measured (normalized) swash plate angle is shown in plot 3. The control valve voltage (the controller output) is shown in plot 4.

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Fig. 10

The tracking performance of the system's subsidiary feedback variables p˙s, α˙, and pcp with the adaptive control design. The reference trajectories are given in black (—) and their feedback variables are given in red ().

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Fig. 11

Experiment with three fluid flow rate conditions through the system load. The first plot shows the discharge pressure trajectory, which is the same trajectory as used in Ref. [24]. The second plot shows the normalized swash plate angles αnlow, αnmed, and αnhigh in the low-, medium- and high-fluid flow rate conditions, respectively. The last plot shows the discharge pressure tracking errors eplow, epmed, and ephigh in the low-, medium- and high-flow rate conditions, respectively.

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Fig. 12

The flow map for the boundedness of the control system variables. Each bounded signal in the flow map is named with a two-part number, where the first number denotes the row number and the second number is a signal identifier (for instance, α˙∈L∞ is named with 3.1, because it lies in the third line and is the first signal in it). The main flow is highlighted in bold. In the flow map, the boundedness of a certain signal is formed from Eqs. (I1)(I5) and from the earlier bounded signals (see entries to the equations). The controller main signals are grouped with a column-based presentation (for instance, ps, p˙s, p¨s, and ps(3) lie in the same column), whereas subsidiary signals are delimited with a dashed line. Finally, the boundedness of (p˙sd−p˙s), (p¨sr−p¨s), (α¨d−α¨), and (p˙cpd−p˙cp) in Eqs. (70)(73) is delimited with a rectangle. The boundedness of the system input (uc∈L∞) is highlighted with a circle.

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