A Robust Approach to Stabilization of 2-DOF Underactuated Mechanical Systems

Aminsafaee, Maryam; Shafiei, Mohammad Hossein

doi:10.1017/s0263574720000053

Cited by 8 publications

(6 citation statements)

References 32 publications

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“…Where q_i represents the generalized coordinates, and the last term stands for the generalized forces, i.e., the projection of the active forces onto the generalized coordinates direction. For a point r of the pendulum in the coordinate system shown in Figure 1, the position can be expressed as eq (2):…”

Section: Equations Of Motion Using the Lagrangian Methodsmentioning

confidence: 99%

“…From a superficial inspection of the equations, nonlinearities become evident; analyzing these nonlinearities escapes the scope of this work. If the reader wants to investigate the phase portraits of a controlled Furuta pendulum, [2] is an informative source.…”

Section: Equations Of Motion Using the Lagrangian Methodsmentioning

confidence: 99%

“…The main objective of this project is to identify a neural network model of a nonlinear mechatronic system, the Furuta pendulum; several aspects of the mechanism must be kept under consideration, aspects which make this specific system to be used vastly in research dealing with modeling and control strategies for mechatronic systems [1] but there is no information about a Neural Network Armax Model applied to this mechatronic system. There are several works on Furuta Pendulum; the authors in [2] study anti-swing controllers for the nominal and disturbed system, they propose a combination of collocated partial feedback linearization and hierarchical sliding mode control inside a two-loop controller. The authors in [3] developed a control for the Furuta pendulum utilizing on-off-type cold gas thrusters as the actuators and an observer-based state feedback controller.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Neural network ARMAX model for a Furuta pendulum

Villamil¹,

Bolivar²,

Polania³

et al. 2021

Ingeniare. Rev. chil. ing.

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The rotational inverted pendulum or Furuta Pendulum is a mechatronic system used by control engineers to explore a various dynamic modeling and control schemes. Due to its nonlinear nature, open-loop instability, and because it is an under-actuated system (more degrees of freedom than actuators), which is the basis for the design of vehicles such as the Segway, the self-balancing scooter, hoverboard, or selfbalancing board, among others. The authors present a model for the Furuta Pendulum using the equations of Euler-Lagrange and the methodology to identify a black-box model by training an NNARMAX (Neural Network Auto-Regressive Moving Average with exogenous inputs). The results show that two interconnected MISO-NNARMAX estimates 10-step-ahead predictions accurately for the horizontal and vertical angles.

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Section: Equations Of Motion Using the Lagrangian Methodsmentioning

confidence: 99%

Section: Equations Of Motion Using the Lagrangian Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Neural network ARMAX model for a Furuta pendulum

Villamil¹,

Bolivar²,

Polania³

et al. 2021

Ingeniare. Rev. chil. ing.

View full text Add to dashboard Cite

show abstract

“…The first step is to choose an appropriate sliding surface for satisfying the control objective, and the second step is to design a discontinuous control law that forces the error trajectories to reach the sliding surface. [39][40][41][42][43] Based on the mentioned points, the sliding surface is suggested as:…”

Section: Phasementioning

confidence: 99%

Adaptive Robust Tracker Design for Nonlinear Sandwich Systems Subject to Saturation Nonlinearities

Azhdari

Binazadeh

2020

Robotica

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SUMMARY This paper addresses the tracking problem for uncertain nonlinear sandwich systems that consist of two nonlinear subsystems and saturation nonlinearity, which is sandwiched between the subsystems. The considered sandwich system is also subject to a nonsymmetric input saturation constraint. Due to the nonsmooth characteristics of sandwiched saturation nonlinearity and also the input saturation function, the design procedure deals with hard challenges. To overcome these difficulties, a recursive approach is suggested that consists of two phases. For the implementation of the proposed approach, a tracking problem is solved in each phase. In the first phase, the second subsystem with sandwiched saturation nonlinearity is considered and the output tracking problem of the desired time-varying reference signal is solved using backstepping method. The outcome of the first phase is the desired reference signal that should be tracked by the first subsystem in the next phase. In the second phase, the robust control input is designed for the first subsystem by employing adaptive sliding mode technique such that, despite the nonsymmetric input saturation constraint, model uncertainty and external disturbances, the output of the first subsystem follows the desired signal that is obtained in the previous phase. The simulation results for a mechanical sandwich system are illustrated to verify the effectiveness of the proposed control method.

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“…Underactuated mechanical systems have fewer independent actuators than the degrees of freedom [1, 2]. Due to the reduction of actuators, these systems have some important merits which include lighter weight, lower cost, and less energy consumption and thus have been widely applied in industries [3], such as cranes [4], robots [5, 6], hovercrafts [7], surface/underwater vehicles [8, 9], and spacecrafts [10].…”

Section: Introductionmentioning

confidence: 99%

Adaptive robust control for Pendubot with matched–mismatched uncertainty via constraint-following

Wei

Chen²,

Chai³

et al. 2023

Robotica

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The study presents an adaptive robust control method for the Pendubot subjects to matched and mismatched uncertainty. First, the control task is formatted as a reduced-dimension equality constraint of the system states. To handle the matched and mismatched uncertainties, an orthogonal decomposition method is employed to make the mismatched part disappear after decomposition. Based on the above, an adaptive robust control law based on constraint-following is devised. By the Lyapunov approach, it is rigorously proven that the proposed approach ensures the uniform boundedness and uniform ultimate boundedness of the closed-loop control system and thus renders approximate constraint-following, regardless of uncertainty. Simulation and experimental results are provided and discussed, demonstrating the good performance of the proposed approach.

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A Robust Approach to Stabilization of 2-DOF Underactuated Mechanical Systems

Cited by 8 publications

References 32 publications

Neural network ARMAX model for a Furuta pendulum

Neural network ARMAX model for a Furuta pendulum

Adaptive Robust Tracker Design for Nonlinear Sandwich Systems Subject to Saturation Nonlinearities

Adaptive robust control for Pendubot with matched–mismatched uncertainty via constraint-following

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