Results 1 - 10 of 227

Neural Network-based Decoupled Sliding Mode Controller Design for Discrete-time Nonlinear MIMO Systems by SPSA Algorithm

by Ching-hung Lee, Hao-yuan Hsueh, Jen-chieh Chien
"... Abstract—In this paper, a neural network-based sliding-mode controller design approach with decoupled method is proposed for a class of nonlinear discrete-time uncertain multi-inputmulti-output (MIMO) systems. The neural network is used to generate the proper control inputs by simultaneous perturbat ..."
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Abstract—In this paper, a neural network-based sliding-mode controller design approach with decoupled method is proposed for a class of nonlinear discrete-time uncertain multi-inputmulti-output (MIMO) systems. The neural network is used to generate the proper control inputs by simultaneous

B.: Output feedback sliding-mode control for uncertain systems using fast output sampling technique

by S. Janardhanan, Student Member - IEEE Trans. Ind. Electron , 2006
"... Abstract—This paper presents a method for achieving quasi-sliding mode for uncertain systems using a fast output sampling control strategy that avoids switching of control and, hence, avoids chattering. This method does not need the system states for feed-back as it makes use of only the output samp ..."
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Abstract—This paper presents a method for achieving quasi-sliding mode for uncertain systems using a fast output sampling control strategy that avoids switching of control and, hence, avoids chattering. This method does not need the system states for feed-back as it makes use of only the output

ADAPTIVE FUZZY SLIDING MODE CONTROL OF UNCERTAIN NONLINEAR SYSTEMS

by Wallace Moreira Bessa, Roberto Souza, Sá Barrêto, Sistemas Incertos Não-lineares
"... This paper presents a detailed discussion about the convergence properties of a variable structure controller for uncertain single-input–single-output nonlinear systems (SISO). The adopted approach is based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm to cope with ..."
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This paper presents a detailed discussion about the convergence properties of a variable structure controller for uncertain single-input–single-output nonlinear systems (SISO). The adopted approach is based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm to cope

1Variable Structure Control of a Class of Uncertain Systems

by Mehmet Önder Efe, Cem Ünsal, Okyay Kaynak, Xinghuo Yu
"... This brief paper proposes a method for tuning the parameters of a variable structure controller. The approach presented extracts the error at the output of the controller and applies a nonlinear tuning law using this error measure. The adaptation mechanism drives the state tracking error vector to t ..."
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This brief paper proposes a method for tuning the parameters of a variable structure controller. The approach presented extracts the error at the output of the controller and applies a nonlinear tuning law using this error measure. The adaptation mechanism drives the state tracking error vector

ADAPTIVE SLIDING MODE BACKSTEPPING CONTROL OF NONLINEAR SYSTEMS WITH UNMATCHED UNCERTAINTY

by Ali J. Koshkouei, Alan S. I. Zinober, Keith J. Burnham
"... This paper considers an adaptive backstepping algorithm for designing the control for a class of nonlinear continuous uncertain processes with dis-turbances that can be converted to a parametric semi-strict feedback form. Sliding mode control using a combined adaptive backstepping sliding mode contr ..."
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This paper considers an adaptive backstepping algorithm for designing the control for a class of nonlinear continuous uncertain processes with dis-turbances that can be converted to a parametric semi-strict feedback form. Sliding mode control using a combined adaptive backstepping sliding mode

A Novel Higher-Order Model-Free Adaptive Control for a Class of Discrete-Time SISO Nonlinear Systems

by Shangtai Jin , Zhongsheng Hou , Ronghu Chi
"... In this work, a novel higher-order model-free adaptive control scheme is presented based on a dynamic linearization approach for a class of discrete-time single input and single output (SISO) nonlinear systems. The control scheme consists of an adaptive control law, a parameter estimation law, and ..."
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In this work, a novel higher-order model-free adaptive control scheme is presented based on a dynamic linearization approach for a class of discrete-time single input and single output (SISO) nonlinear systems. The control scheme consists of an adaptive control law, a parameter estimation law

ROBUST NEURAL IDENTIFICATION OF ROBOTIC MANIPULATORS USING DISCRETE TIME ADAPTIVE SLIDING MODE LEARNING

by Andon V. Topalov, Okyay Kaynak
"... Abstract: The problem of identification of uncertain nonlinear systems using feedforward neural networks is investigated. The weights of the neural identifier are updated on-line by a discrete-time learning algorithm based on the sliding mode control technique, which is well known with its robustnes ..."
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Abstract: The problem of identification of uncertain nonlinear systems using feedforward neural networks is investigated. The weights of the neural identifier are updated on-line by a discrete-time learning algorithm based on the sliding mode control technique, which is well known with its

Multirate Output Feedback Based Stochastic Sliding Mode Control

by Associate Professor A J Mehta , B Bandyopadhyay
"... In this paper, a multirate output feedback (MROF) based discrete-time sliding mode control for the stochastic system with slowly varying bounded uncertainty is proposed. The states are estimated by the multirate Kalman filter and are used for designing the stochastic sliding mode controller which g ..."
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In this paper, a multirate output feedback (MROF) based discrete-time sliding mode control for the stochastic system with slowly varying bounded uncertainty is proposed. The states are estimated by the multirate Kalman filter and are used for designing the stochastic sliding mode controller which

Adaptive Sliding Mode Control for Magnetic Levitation Vehicles *

by Juanjuan He, Yingmin Jia
"... This paper focuses on stability control for the levitated positioning of the magnetic levitation vehicle system. For the nonlinear magnetic levitation system model, the output feedback linearization method is employed to derive a global linearization error model. However, there exists uncertain item ..."
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item in the error model. To stabilize this error model, the adaptive sliding mode control method is used here. Simulations show that the magnetic levitation system can be stability quickly under controlled by the proposed control scheme.

Research Article Sliding Mode Control for a Class of Uncertain MIMO Nonlinear Systems with Application to Near-Space Vehicles

by Mou Chen, Rong Mei, Bin Jiang , 2013
"... which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. We propose a robust sliding mode control (SMC) scheme for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with the unknown external disturbance, the ..."
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which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. We propose a robust sliding mode control (SMC) scheme for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with the unknown external disturbance
Results 1 - 10 of 227