Adaptive decentralized control of robot manipulators driven by current-fed induction motors

Hsu, Su-Hau; Fu, Li‐Chen

doi:10.1109/tmech.2005.852453

Cited by 30 publications

(22 citation statements)

References 10 publications

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“…In fact, the majority of contemporary robots are still controlled by the decentralized (independent joint) proportional-integral-derivative (PID) law in favor of its simple computation and low-cost setup [3], [4]. Due to strong nonlinearities in dynamics, advanced decentralized control techniques are still attracting much attention to achieve a satisfactory trajectory performance of robot manipulators [5]- [11].…”

Section: Introductionmentioning

confidence: 99%

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Decentralized Adaptive Robust Control of Robot Manipulators Using Disturbance Observers

Yang

Fukushima

Qin

2012

IEEE Trans. Contr. Syst. Technol.

148

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In this paper, we propose a decentralized adaptive robust controller for trajectory tracking of robot manipulators. In each local controller, a disturbance observer (DOB) is introduced to compensate for the low-passed coupled uncertainties, and an adaptive sliding mode control term is employed to handle the fastchanging components of the uncertainties beyond the pass-band of the DOB. In contrast to most of the local controllers using DOB for robot manipulators that are based on linear control theory, in this study, by some special nonlinear damping terms, the boundedness of the signals of the overall nonlinear system is first ensured. This paves the way to analyze how the DOB and adaptive sliding mode control play in a cooperative way in each local subsystem to achieve an excellent control performance. Simulation results are provided to support the theoretical results.

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Section: Introductionmentioning

confidence: 99%

“…It has been however, found that in the manipulators the strength of the interconnections is bounded by second-order polynomials in states [5]- [10]. Inspired by this, with a third-order feedback control term, adaptive sliding mode controller [6], and adaptive controller [10] with local model estimation have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Adaptive Robust Control of Robot Manipulators Using Disturbance Observers

Yang

Fukushima

Qin

2012

IEEE Trans. Contr. Syst. Technol.

148

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“…As a result, it is difficult to obtain an accurate mathematical model so that model-based decentralized robust controllers can be accurately applied [12,13]. Although decentralized adaptive controllers can achieve fine control and compensate for partially unknown manipulator dynamics, they often suffer from incapacity to deal with unstructured uncertainties [14][15][16]. Hence, there is a need for model-free adaptive control strategies.…”

Section: Introductionmentioning

confidence: 99%

Decentralized adaptive fuzzy sliding mode control for reconfigurable modular manipulators

Zhu

2009

Intl J Robust & Nonlinear

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SUMMARYA stable decentralized adaptive fuzzy sliding mode control scheme is proposed for reconfigurable modular manipulators to satisfy the concept of modular software. For the development of the decentralized control, the dynamics of reconfigurable modular manipulators is represented as a set of interconnected subsystems. A first-order Takagi-Sugeno fuzzy logic system is introduced to approximate the unknown dynamics of subsystem by using adaptive algorithm. The effect of interconnection term and fuzzy approximation error is removed by employing an adaptive sliding mode controller. All adaptive algorithms in the subsystem controller are derived from the sense of Lyapunov stability analysis, so that resulting closed-loop system is stable and the trajectory tracking performance is guaranteed. The simulation results are presented to show the effectiveness of the proposed decentralized control scheme.

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“…Nevertheless, induction motor control constitutes a rather difficult problem due to the highly nonlinear and multivariable nature of its model and to the non-measurability of all state variables: while rotor position and speed along with stator currents can be easily measured, flux sensors are not available in standard induction motors. Solutions to the problem of controlling robot manipulators actuated by induction motors are presented in [1][2][3][4][5]. A local partial state feedback link position tracking controller is proposed in [1], while global output feedback position tracking is obtained in [2]: exact model knowledge is required.…”

Section: Introductionmentioning

confidence: 99%

“…By assuming linear parameterization of manipulator inertia matrix determinant, global asymptotic link position tracking is guaranteed in [3] despite parametric uncertainties in the mechanical subsystem. Robust control algorithms for uncertain robot manipulators driven by current-fed induction motors are proposed in [4,5]: an arbitrarily small link position tracking error can be obtained by properly setting the design parameters. In the case of periodic reference trajectories, system parameter uncertainties may cause periodic disturbances in motor servo drives so that learning control techniques may be successfully applied.…”

Section: Introductionmentioning

confidence: 99%

Robust output feedback learning control for induction motor servo drives

Tomei

Verrelli

Montanari

et al. 2008

Intl J Robust & Nonlinear

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This paper addresses the output feedback tracking control problem for induction motor servo drives with mechanical uncertainties: rotor angle, rotor speed and stator Currents are assumed to be available for feedback. A robust adaptive learning control is designed under the assumption that the reference profile for the rotor angle is periodic with known period: it 'learns' the periodic disturbance signal by identifying the Fourier coefficients of any truncated approximation; L-2 and L-infinity transient performances are guaranteed in the 'learning phase'. It is shown that, for any motor initial condition belonging to an arbitrary given compact set, by properly setting the control parameters: (i) the rotor position and flux modulus tracking errors, exponentially converge to residual sets, which may be arbitrarily reduced by increasing the number of terms in the truncated Fourier series; (ii) when the unknown periodic disturbance can be represented by a finite Fourier series, the rotor position and flux modulus tracking errors exponentially converge to zero. As in field oriented-control, the control algorithm generates references for the magnetizing flux component and for the torque component of the stator current leading to significant simplifications for current-fed motors. Copyright (C) 2008 John Wiley & Sons, Ltd

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Adaptive decentralized control of robot manipulators driven by current-fed induction motors

Cited by 30 publications

References 10 publications

Decentralized Adaptive Robust Control of Robot Manipulators Using Disturbance Observers

Decentralized Adaptive Robust Control of Robot Manipulators Using Disturbance Observers

Decentralized adaptive fuzzy sliding mode control for reconfigurable modular manipulators

Robust output feedback learning control for induction motor servo drives

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