Tracking Control of an Inverted Pendulum Using Computed Feedback Linearization Technique

Chancharoen, Ratchatin; Sangveraphunsiri, Viboon; Chantranuwathana, Supavut

doi:10.1109/ramech.2006.252680

Cited by 10 publications

(4 citation statements)

References 6 publications

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“…Linear controllers such as in [13] use a robust LQR-based ANFIS (Adaptive neuro fuzzy inference system), and [14] involves the Jacobian linearization method to extract a linear quadratic regulator and hybrid PID with LQR. For nonlinear approaches, a feedback linearization controller has been proposed by [15] to control the inertia wheel pendulum, [16] for TORA system and [17] to control the inverted pendulum.…”

Section: Motivation: a Literature Reviewmentioning

confidence: 99%

Adaptive Wavelets Sliding Mode Control for a Class of Second Order Underactuated Mechanical Systems

Nafa

Boudouda

Smaani³

2021

Acta Polytech

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The control of underactuated mechanical systems (UMS) remains an attracting field where researchers can develop their control algorithms. To this date, various linear and nonlinear control techniques using classical and intelligent methods have been published in literature. In this work, an adaptive controller using sliding mode control (SMC) and wavelets network (WN) is proposed for a class of second-order UMS with two degrees of freedom (DOF).This adaptive control strategy takes advantage of both sliding mode control and wavelet properties. In the main result, we consider the case of un-modeled dynamics of the above-mentioned UMS, and we introduce a wavelets network to design an adaptive controller based on the SMC. The update algorithms are directly extracted by using the gradient descent method and conditions are then settled to achieve the required convergence performance.The efficacy of the proposed adaptive approach is demonstrated through an application to the pendubot.

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Section: Motivation: a Literature Reviewmentioning

confidence: 99%

Adaptive Wavelets Sliding Mode Control for a Class of Second Order Underactuated Mechanical Systems

Nafa

Boudouda

Smaani³

2021

Acta Polytech

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“…The perching dynamics are most similar to the balancedbeam inverted pendulum, which may be controlled using feedback-linearized state-space control [6]. Integral action on the vehicle angle may be added in order to compensate for small positional estimate bias due to tread slippage; however, it cannot be guaranteed to converge at a rate sufficient for successfully transitioning between upright roving and perching maneuvers.…”

Section: Motivation: Treaded Vehicle Perchingmentioning

confidence: 99%

Inertial rotation center position estimation for a perching treaded vehicle

Schmidt-Wetekam

Morozovsky

Bewley

2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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A method for estimating the rotation center position (RCP) of a rigid body in the x-y plane using two offset accelerometers is presented. RCP estimation via inertial measurement is motivated by the related problems of detecting foot slippage of legged robots and detecting stair edges for treaded robots, for applications in which alternative methods such as discontinuity recognition, visual tracking, and/or tactile feedback are impractical. The RCP may be directly solved for as a function of the two offset tangential acceleration measurements, when the RCP is colinear with the two accelerometers, and when the common-mode tangential accelerations, due to linear acceleration and/or gravity, can be independently measured or estimated. Angular velocity estimates may be enhanced by combining calculated angular acceleration with gyroscope measurements, even when both the RCP and common-mode tangential accelerations cannot be independently measured. An input variance modulated variable cutoff low-pass filter is also proposed for RCP estimation in the absence of independent measurements, which is validated on a balance-beam invertedpendulum apparatus.

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“…A cart inverted pendulum system has been served as a general model for robotic systems. The cart pendulum system is a non-linear, under-actuated system with unstable zero dynamics and must be controlled such that the position is at its unstable equilibrium [1][2][3][4][5]. The most common method to perform the swing-up of an inverted pendulum is energy control where the energy of the system is controlled instead of directly controlling its position and velocity.…”

Section: Introductionmentioning

confidence: 99%

Non-linear Control of Inverted Pendulum

Coşkun

2020

Çukurova Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

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Presented is a study of non-linear control for an inverted pendulum system. The inverted pendulum system is a great example of an underactuated, non-minimum phase, and highly unstable system. The objective of this research paper is to derive non-linear control laws for an inverted pendulum system. First, dynamic equations of the inverted pendulum are derived by utilizing the Lagrange's equations and then it is linearized around an unstable upright position. Secondly, the corresponding analysis uses the standard linear stability arguments and the traditional Lyapunov method. The non-linear sliding mode control and feedback linearization control laws are then derived The feedback linearization control law is used to transform the non-linear system into an equivalent linear system such that a suitable feedback control law can be proposed. The stabilization of the initial condition and reference tracking is studied in this paper. I demonstrate the effectiveness of the proposed non-linear control strategies using MATLAB/Simulink software.

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Tracking Control of an Inverted Pendulum Using Computed Feedback Linearization Technique

Cited by 10 publications

References 6 publications

Adaptive Wavelets Sliding Mode Control for a Class of Second Order Underactuated Mechanical Systems

Adaptive Wavelets Sliding Mode Control for a Class of Second Order Underactuated Mechanical Systems

Inertial rotation center position estimation for a perching treaded vehicle

Non-linear Control of Inverted Pendulum

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