On parameter identification of the Furuta pendulum

Garćıa-Alarćon, Octavio; Puga-Guzmán, Sergio; Moreno–Valenzuela, Javier

doi:10.1016/j.proeng.2012.04.167

Cited by 26 publications

(17 citation statements)

References 5 publications

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“…The dynamic equations of the Furuta pendulum are given by (Fu and Lin 2005;Hera et al 2009;Garcia-Alarcon et al 2012;Ramirez-Neria et al 2013):…”

Section: Dynamic Model Of the Furuta Pendulummentioning

confidence: 99%

“…In Hera et al (2009), the stabilization of a Furuta pendulum applying an efficient control law to obtain the desired trajectory tracking is corroborated by the respective phase portraits. Some authors propose the parameter identification of the model (Garcia-Alarcon et al 2012) implementing a least square algorithm; becoming an important technique that can be used in adaptive control strategies. Another significant control approach is implemented by Fu and Lin (2005) where a backstepping controller is applied for the stabilization of the Furuta pendulum where a linearized model of the pendulum is used to stabilizes this mechanical system around the equilibrium point.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Sliding Mode Control of the Furuta Pendulum

Azar

Serrano

2014

Advances and Applications in Sliding Mode Control Systems

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In this chapter an adaptive sliding mode controller for the Furuta pendulum is proposed. The Furuta pendulum is a class of underactuated mechanical systems commonly used in many control systems laboratories due to its complex stabilization which allows the analysis and design of different nonlinear and multivariable controllers that are useful in some fields such as aerospace and robotics. Sliding mode control has been extensively used in the control of mechanical systems as an alternative to other nonlinear control strategies such as backstepping, passivity based control etc. The design and implementation of an adaptive sliding mode controller for this kind of system is explained in this chapter, along with other sliding mode controller variations such as second order sliding mode (SOSMC) and PD plus sliding mode control (PD + SMC) in order to compare their performance under different system conditions. These control techniques are developed using the Lyapunov stability theorem and the variable structure design procedure to obtain asymptotically stable system trajectories. In this chapter the adaptive sliding mode consist of a sliding mode control law with an adaptive gain that makes the controller more flexible and reliable than other sliding mode control (SMC) algorithms and nonlinear control strategies. The adaptive sliding mode control (ASMC) of the Furuta pendulum, and the other SMC strategies shown in this chapter, are derived according to the Furuta's pendulum dynamic equations making the sliding variables, position errors and velocity errors reach the zero value in a specified reaching time. The main reason of deriving two well known sliding mode control strategy apart from the proposed control strategy of this chapter (adaptive sliding mode control) is for comparison purposes and to evince the advantages and disadvantages of adaptive sliding mode control over other sliding mode control strategies for the stabilization of the Furuta pendulum. A chattering analysis of the three SMC variations is done, to examine the response of the system, and to test the performance of the ASMC in comparison with the other control strategies explained in this chapter.

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“…The dynamic equations of the Furuta pendulum are given by (Fu and Lin 2005;Hera et al 2009;Garcia-Alarcon et al 2012;Ramirez-Neria et al 2013):…”

Section: Dynamic Model Of the Furuta Pendulummentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Control of the Furuta Pendulum

Azar

Serrano

2014

Advances and Applications in Sliding Mode Control Systems

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“…The damping force presented in the actuated coordinate is neglected in order to simplify the methodology presented here. It is important to remark that this force can be easily compensated by using any adaptive control algorithm ( [20,29]). …”

Section: Problem Statementmentioning

confidence: 99%

“…According to (20) and the fact that s 1 → 0 and q 4 → 0, the last differential equation turns out to be…”

Section: Control Of the Cart Pole Systemmentioning

confidence: 99%

Stabilization of the cart pole system: by sliding mode control

Aguilar-Ibáñez¹,

Mendoza-Mendoza²,

Dávila³

2014

Nonlinear Dyn

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This paper presents a control strategy designed as a combination of a PD controller and a twistinglike algorithm to stabilize the damped cart pole system, provided that the pendulum is initially placed within the upper-half plane. To develop the strategy, the original system is transformed into a four-order chain of integrator form, where the damping force is included through an additional nonlinear perturbation. The strategy consists of simultaneously bringing the position and velocity of the pendulum to within a compact region by applying the PD controller. Meanwhile, the system state variables are brought to the origin by the twisting-like algorithm. The corresponding convergence analysis is done using several Lyapunov functions. The control strategy is illustrated with numerical simulations.

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“…According to Definition 6.7, page 244 in [5], for the output function defined as in (11) and the system in (7), the relative degree of the system is r = 1. Then, we have that the control input given by…”

Section: A Controller Derived From Feedback Linearizationmentioning

confidence: 99%

A feedback linearization controller for trajectory tracking of the Furuta pendulum

Aguilar-Avelar

Moreno–Valenzuela

2014

2014 American Control Conference

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A Furuta pendulum is a two degrees-of-freedom mechanism consisting of an arm rotating in the horizontal plane and a pendulum rotating in the vertical plane. The pendulum is attached to the arm tip. The complexity in the control of this system relies on that only the arm is actuated. The problem addressed in this paper consists in the design of a controller such that the difference between the desired joint position and the actual one is uniformly ultimately bounded. In particular, the desired arm position is a time varying signal and the desired pendulum position is zero. Roughly speaking, this has the physical meaning that the arm should be moving while the pendulum should be kept at the upward position. To satisfy that control goal, in this document a new controller based on the feedback linearization technique is introduced. The new scheme has been experimentally compared with respect to a known algorithm.

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On parameter identification of the Furuta pendulum

Cited by 26 publications

References 5 publications

Adaptive Sliding Mode Control of the Furuta Pendulum

Adaptive Sliding Mode Control of the Furuta Pendulum

Stabilization of the cart pole system: by sliding mode control

A feedback linearization controller for trajectory tracking of the Furuta pendulum

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