On trajectory tracking control of the inertia wheel pendulum

Moreno–Valenzuela, Javier; Aguilar-Avelar, Carlos; Puga-Guzmán, Sergio

doi:10.1109/codit.2014.6996958

Cited by 6 publications

(6 citation statements)

References 13 publications

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“…(16) where K t is the motor's torque constant gain, K tr is the transmission ratio constant gain relating the motors rotations to the trolley displacement, and the jib rotation, L ind is the inductance of the motor, R coil is the resistance of the motor, J m is the load inertia including both the motor's rotor inertia and the load inertia, B m is the damping factor and K b is the back emf constant gain. The previously derived equations of motion were implemented and numerically simulated using Simulink.…”

Section: Modeling Of Tower Cranementioning

confidence: 99%

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Anti-sway control of marine cranes under the disturbance of a parallel manipulator

El-Badawy

Shehata

2015

Nonlinear Dyn

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Cranes are used to move loads from one location to another in minimum time such that the load reaches its destination without swinging. This swinging problem gets aggravated in the presence of external disturbances such as in the case of marine cranes. This paper investigates the modeling of a tower crane model and different types of control schemes for both anti-swaying and input tracking control for the tower crane model under continuous external disturbances. The input shaping technique was applied for a tower crane model under continuous external disturbance. Then a closed-loop PID input shaper was implemented instead of the open-loop input shaper to compensate for the external disturbances. Also the response of the closed-loop PID input shaper was compared to a controller based on inverse dynamics. Environmental disturbances such as sea waves were simulated by the movement of a Stewart platform.

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Section: Modeling Of Tower Cranementioning

confidence: 99%

“…Researchers discussed the use of PD controller to control the inverted pendulum [14]. Aguilar-Avelar et al [15,16] presented a nonlinear controller using feedback linearization to control the Furuta pendulum.…”

Section: Introductionmentioning

confidence: 99%

Anti-sway control of marine cranes under the disturbance of a parallel manipulator

El-Badawy

Shehata

2015

Nonlinear Dyn

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“…Instead, Controller 2 does include the term ′ . However, in case ′ is omitted from (17) and from (3), its effect on the Lyapunov derivative is the same as in (20) resulting in more stringent stability conditions than those expressed in Proposition 3. This indicates that neglecting large lateral forces can have a destabilizing effect on the system.…”

Section: Controllermentioning

confidence: 99%

“…In spite of these remarkable advances, conventional metallic needles remain ubiquitous in clinical practice, thus the study of control strategies for the insertion of standard needles is an active area of research [16]. Important results in this sense include: sliding-mode control algorithms [17,18]; modelbased optimal control of flexible needles [19,20]; an optimized path planning procedure for insertions in multi layered tissues [21]; an adaptive output-feedback controller [22]; an integrator backstepping approach to reduce needle deflection in 3D [11]. Notably, these approaches aim to influence the needle deflection as the insertion progresses by means of axial rotation of bevel-tip needles.…”

Section: Introductionmentioning

confidence: 99%

Adaptive energy shaping control of robotic needle insertion

Franco

Brown

Astolfi

et al. 2021

Mechanism and Machine Theory

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“…Simulations were conducted for system (33) with initial position q 1 = 0.1, q 2 = 0.2 and p = 0 employing the parameters: a 1 = 0.0124; a 2 = 0.0025; a 3 = 0.4446; m 1 = 0.40; m 2 = 1.08; m 3 = 5. Control (35) was implemented with the parameters: k p = 1; k v = 0.001; = 50.…”

Section: Inertia Wheel Pendulummentioning

confidence: 99%

Adaptive IDA‐PBC for underactuated mechanical systems with constant disturbances

Franco

2018

Adaptive Control & Signal

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This work investigates the control of nonlinear underactuated mechanical systems with matched and unmatched constant disturbances. To this end, a new control strategy is proposed, which builds upon the interconnection-anddamping-assignment passivity-based control, augmenting it with an additional term for the purpose of disturbance compensation. In particular, the disturbances are estimated adaptively and then accounted for in the control law employing a new matching condition of algebraic nature. Stability conditions are discussed, and for comparison purposes, an alternative controller based on partial feedback linearization is presented. The effectiveness of the proposed approach is demonstrated with numerical simulations for three motivating examples: the inertia wheel pendulum, the disk-on-disk system, and the pendulum-on-cart system. KEYWORDS adaptive control, matched and unmatched disturbances, nonlinear control, underactuated mechanical systems Int J Adapt Control Signal Process. 2019;33:1-15.wileyonlinelibrary.com/journal/acs

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On trajectory tracking control of the inertia wheel pendulum

Cited by 6 publications

References 13 publications

Anti-sway control of marine cranes under the disturbance of a parallel manipulator

Anti-sway control of marine cranes under the disturbance of a parallel manipulator

Adaptive energy shaping control of robotic needle insertion

Adaptive IDA‐PBC for underactuated mechanical systems with constant disturbances

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