Robust Control for the Segway with Unknown Control Coefficient and Model Uncertainties

Kim, Byung Woo; Park, Bong Seok

doi:10.3390/s16071000

Cited by 22 publications

(12 citation statements)

References 26 publications

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“…The total mass occurs by a group of rotating wheels, and the chassis and person can be represented as a point mass at a certain distance from the axle. The Lagrange's equation for the rotational motion of the underactuated Segway model is described in [35,36] as…”

Section: Numerical Examplesmentioning

confidence: 99%

Quantized‐feedback hands‐off control for nonlinear systems

Sachan

Xiong

Soni

et al. 2021

IET Control Theory & Appl

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This paper addresses a quantized feedback hands-off control for a class of nonlinear systems. Here, [, ] sector is constructed with the suitable choice of control-Lyapunov function. With adjustment policy of quantization parameters, the quantized feedback hands-off control can force the states of the nonlinear feedback system to the interior of a continuous-time [, ] sector infinite time and the Lyapunov-candidate function decreases automatically inside the designed sector. Finally, the effectiveness of the proposed method is illustrated by numerical examples.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Numerical Examplesmentioning

confidence: 99%

Quantized‐feedback hands‐off control for nonlinear systems

Sachan

Xiong

Soni

et al. 2021

IET Control Theory & Appl

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“…The goal of the control system is to balance an inverted pendulum system by giving a control signal (force) to a cart that has been installed with a pendulum system [12] [13]. Some examples of inverted pendulum system applications are: balancing system in a rocket system when the rocket takes off [14], Missile Launcher [15] [16], Segway [17], balancing robots [18]- [20], humanoid robot [21]- [23], etc [24]. Some researches about inverted pendulum have been done by many.…”

Section: Introductionmentioning

confidence: 99%

Backstepping Sliding Mode Control for Inverted Pendulum System with Disturbance and Parameter Uncertainty

Ma’arif

Márquez-Vera²,

Mahmoud³

et al. 2021

Journal of Robotics and Control

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The inverted pendulum system is highly popular in control system applications and has the characteristics of unstable, nonlinear, and fast dynamics. A nonlinear controller is needed to control a system with these characteristics. In addition, there are disturbances and parameter uncertainty issues to be solved in the inverted pendulum system. Therefore, this study uses a nonlinear controller, which is the backstepping sliding mode control. The controller is robust to parameter uncertainty and disturbances so that it is suitable for controlling an inverted pendulum system. Based on testing with step and sine reference signals without interference, the controller can stabilize the system well and has a fast response. In testing with disturbances and mass uncertainty, the backstepping sliding mode controller is robust against these changes and able to make the system reach the reference value. Compared with sliding mode control, backstepping sliding mode control has a better and more robust response to disturbances and parameter uncertainty.

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“…Wheel-leg robots with one or more robotic arms have attracted a great deal of attention in recent years [1]- [3]. The WLRs have more degrees of freedom(DOFs) than two-wheeled robots [4], [5] respect to vertical direction. The wheeled mobile platform can provide more agile and faster moving speed for WLRs than legged robots [6].…”

Section: Introductionmentioning

confidence: 99%

Movements and Balance Control of a Wheel-Leg Robot Based on Uncertainty and Disturbance Estimation Method

Xin

Rong

et al. 2019

IEEE Access

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In order to control the posture, balance and movements of a wheel-leg robot(WLR) precisely, some problems have to be solved. The major problems involve the strongly coupling of movement states, the composite uncertainty with modeling errors, the time-varying internal and the external disturbances. In this paper, a force controller based on the uncertainty and disturbance estimation(UDE) method is designed. The feedforward compensation based on dynamic model allows for compliant and more precise motion control. The UDE can estimate and compensate the composite uncertainty without any priori information effectively. The posture controller is designed based on the virtual model control. The whole controller which includes the posture controller and the movements balance controller is proposed and applied for WLR that built in Webots. The simulation results of trajectory control, balance control and robust test are presented to demonstrate the effectiveness of the whole controller. INDEX TERMS Uncertainty and disturbance estimator (UDE), wheel-leg robot, virtual model control.

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Robust Control for the Segway with Unknown Control Coefficient and Model Uncertainties

Cited by 22 publications

References 26 publications

Quantized‐feedback hands‐off control for nonlinear systems

Quantized‐feedback hands‐off control for nonlinear systems

Backstepping Sliding Mode Control for Inverted Pendulum System with Disturbance and Parameter Uncertainty

Movements and Balance Control of a Wheel-Leg Robot Based on Uncertainty and Disturbance Estimation Method

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