Experimental Benchmarking of Energy-saving Sub-Optimal Sliding Mode Control

The recently introduced energy-saving extension of the sub-optimal sliding mode control allows for control-off phases during the convergence to second-order equilibrium. This way, it enables for a lower energy consumption compared to the original sub-optimal sliding mode (SM) algorithm, both commutating a discontinuous control signal. In this paper, the energy-saving sub-optimal SM control is experimentally benchmarked against a standard second-order SM controller which also has a discontinuous control action. Here the so-called terminal second-order SM algorithm is used. The controlled plant is affected by the matched bounded disturbances which are unknown, and the output is additionally subject to the sensor noise. Moreover, a first-order actuator dynamics can lead to chattering, which is parasitic for SM applications. For a fair comparison, the same quadratic terminal surface is designed when benchmarking both SM controllers. Both experimentally compared SM algorithms have the same (bounded) control magnitude and states initial conditions.

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Published
2024-10-21
DOI
https://doi.org/10.1109/vss61690.2024.10753417
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
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Experimental Benchmarking of Energy-saving Sub-Optimal Sliding Mode Control

Michael Ruderman
Adaptive Control of Nonlinear Systems
article

Experimental Benchmarking of Energy-saving Sub-Optimal Sliding Mode Control

Michael Ruderman
article en

Abstract

The recently introduced energy-saving extension of the sub-optimal sliding mode control allows for control-off phases during the convergence to second-order equilibrium. This way, it enables for a lower energy consumption compared to the original sub-optimal sliding mode (SM) algorithm, both commutating a discontinuous control signal. In this paper, the energy-saving sub-optimal SM control is experimentally benchmarked against a standard second-order SM controller which also has a discontinuous control action. Here the so-called terminal second-order SM algorithm is used. The controlled plant is affected by the matched bounded disturbances which are unknown, and the output is additionally subject to the sensor noise. Moreover, a first-order actuator dynamics can lead to chattering, which is parasitic for SM applications. For a fair comparison, the same quadratic terminal surface is designed when benchmarking both SM controllers. Both experimentally compared SM algorithms have the same (bounded) control magnitude and states initial conditions.

University of Agder (NO)
Affordable and clean energy
Openalex Percentile: Top 75%
Adaptive Control of Nonlinear Systems
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