A Sliding-Mode Set-Point Position Controller for Hydraulic Excavators

Yamamoto, Yuki; Qiu, Jinjun; Munemasa, Yoshiki; Doi, Takayuki; Nanjo, Takao; Yamashita, Koji; Kikuuwe, Ryo

doi:10.1109/access.2021.3128215

Cited by 10 publications

(31 citation statements)

References 30 publications

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“…It should be noted that the proposed scheme heavily depends on the nominal model of the plant including the external force. This section analyzes the effect of modeling errors and unknown disturbance to the discrete-time controller (34) applied to the plant (12).…”

Section: Errors In Nominal Modelmentioning

confidence: 99%

“…The control input u k is assumed to be kept constant within every timestep. Next, by carefully tracing back the derivation in Section IV-B, one can rewrite the discrete-time controller (34) in the following form:…”

Section: Errors In Nominal Modelmentioning

confidence: 99%

“…Theorem 4 means that a subset of the subspace S approximately acts as a sliding surface, and that the state approximately converges to the origin as long as the disturbance is appropriately bounded. The theorem implies that the proposed discrete-time algorithm (34) implemented to the plant ( 12) well approximates the continuous-time closed-loop system (23) as long as the prediction errors σk+1 and ṽk+1 are small enough. One can also see that, from (38), the prediction errors σk+1 and ṽk+1 depend on the unknown component of the external force and the modeling error, but are of the order of the sampling interval T .…”

Section: Errors In Nominal Modelmentioning

confidence: 99%

“…4. The controller is the algorithm (34) with Γ η and Θ s being replaced by Γ η,ex in (30) and Θ s,ex in (15), respectively. The controller's sampling interval is set as T = 0.01 s unless otherwise noted, the time constant for the sliding surface is set as H = 1 s, and the desired position is fixed as p d ≡ 1 m. Here, notice that the sampling interval T of the controller is set much larger than the timestep size h of the plant simulation.…”

Section: Numerical Examplesmentioning

confidence: 99%

“…Fig. 8 shows results with the explicit implementation (u = sgn(−σ), i.e., (21)) and the proposed algorithm (34) with different values of the sampling interval T . It shows that the explicit implementation results in intense chattering, which would make it practically unusable.…”

Section: Numerical Examplesmentioning

confidence: 99%

See 4 more Smart Citations

Implicit Implementation of Nonsmooth Controllers to Nonsmooth Actuators

Kikuuwe

Yamamoto

Brogliato

2022

IEEE Trans. Automat. Contr.

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This paper presents an approach to implement a sliding-mode position controller to a plant equipped with a nonsmooth actuator. The actuator is modeled as a set-valued function from the control input and the velocity to the actuator force, which is motivated by quasistatic characteristics of hydraulic actuators shown in a previous study. The implementation of the sliding-mode controller is performed with the implicit discretization of the nominal plant model and the controller, which copes with the difficulties caused by set-valuedness, such as numerical chattering. Stability analyses both in the continuous-time and discrete-time domains are presented. Simulation results illustrate the theoretical findings.

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Section: Errors In Nominal Modelmentioning

confidence: 99%

Section: Errors In Nominal Modelmentioning

confidence: 99%

Section: Errors In Nominal Modelmentioning

confidence: 99%

Section: Numerical Examplesmentioning

confidence: 99%

Section: Numerical Examplesmentioning

confidence: 99%

See 3 more Smart Citations

Implicit Implementation of Nonsmooth Controllers to Nonsmooth Actuators

Kikuuwe

Yamamoto

Brogliato

2022

IEEE Trans. Automat. Contr.

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Extended sliding mode observer‐based high‐accuracy motion control for uncertain electro‐hydraulic systems

Nguyen

Dao

Ahn

2022

Intl J Robust & Nonlinear

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In this paper, a novel robust backstepping control strategy is introduced to achieve high‐accuracy tracking performance for electro‐hydraulic servo systems (EHSSs) without velocity information in the presence of uncertainties and disturbances. Firstly, system dynamics of the studied EHSS considering parameter deviations, modeling errors, and unknown external loads which are grouped into lumped mismatched and matched disturbances in the mechanical system and pressure dynamics, respectively, are developed. On the basis of the sliding mode theory, two extended sliding mode observers (ESMOs) are originally established to simultaneously estimate the immeasurable angular velocity of the actuator, and lumped mismatched and matched uncertainties. As a consequence, an observer‐based controller is designed using the conventional backstepping technique to ensure a highly accurate tracking position control. In addition, the stability of the observer and overall closed‐loop control system is conclusively proven through the Lyapunov theory. Finally, several numerical simulations for an EHSS with a hydraulic rotary actuator are conducted to demonstrate the advantage of the recommended method compared to the existing well‐known extended state observer‐based control approaches.

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