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2021 Index IEEE Transactions on Fuzzy Systems Vol. 29
2021
IEEE transactions on fuzzy systems
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Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. ...
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Triggered Control Design for Nonlinear Systems With Full State Constraints. ...
doi:10.1109/tfuzz.2021.3134727
fatcat:m66dl6wxdbgendhdx4bliy6nky
2019 Index IEEE Transactions on Fuzzy Systems Vol. 27
2019
IEEE transactions on fuzzy systems
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Adaptive Fuzzy Event-Triggered Control for Stochastic Nonlinear Systems With Full State Constraints and Actuator Faults. ...
., +, TFUZZ Sept. 2019 1793-1806 Adaptive Fuzzy Event-Triggered Control for Stochastic Nonlinear Systems With Full State Constraints and Actuator Faults. ...
Nonlinear filters Adaptive Neuro-Fuzzy Control for Discrete-Time Nonaffine Nonlinear Systems. Gil ...
doi:10.1109/tfuzz.2020.2966828
fatcat:pgfo5oksjrdbpa5s534ky74bie
2021 Index IEEE Transactions on Systems, Man, and Cybernetics: Systems Vol. 51
2021
IEEE Transactions on Systems, Man & Cybernetics. Systems
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., +, TSMC May 2021 2712-2725 Reduced Adaptive Fuzzy Tracking Control for High-Order Stochastic Nonstrict Feedback Nonlinear System With Full-State Constraints. ...
doi:10.1109/tsmc.2021.3136054
fatcat:b5hcsfwjw5hllpenqmaq6wpke4
2021 Index IEEE Transactions on Cybernetics Vol. 51
2021
IEEE Transactions on Cybernetics
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., +, TCYB June 2021 2870-2881 Nonlinear systems Adaptive Fuzzy Tracking Control for a Class of Uncertain Switched Nonlinear Systems With Full-State Constraints and Input Saturations. ...
doi:10.1109/tcyb.2021.3139447
fatcat:myjx3olwvfcfpgnwvbuujwzyoi
2019 Index IEEE Transactions on Systems, Man, and Cybernetics: Systems Vol. 49
2019
IEEE Transactions on Systems, Man & Cybernetics. Systems
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Finite-Time Adaptive Fuzzy Control for Nonlinear Systems With Full State Constraints. ...
Distributed Adaptive Fuzzy Containment Control of Stochastic Pure-Feedback Nonlinear Multiagent Systems With Local Quantized Controller and Tracking Constraint. ...
Open loop systems ...
doi:10.1109/tsmc.2019.2956665
fatcat:xhplbanlyne7nl7gp2pbrd62oi
Barrier Lyapunov functions-based adaptive neural tracking control for non-strict feedback stochastic nonlinear systems with full-state constraints: A command filter approach
2022
Mathematical Control and Related Fields
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<p style='text-indent:20px;'>In this paper, an adaptive neural network command filter controller is investigated for a class of non-strict feedback stochastic nonlinear systems with full-state constraints ...
nonlinear functions that contain all the state variables of the system. ...
In [35] , an adaptive neural tracking controller is presented for a class of non-strict feedback stochastic nonlinear systems with full-state constraints, time-delay, and saturation input. ...
doi:10.3934/mcrf.2022024
fatcat:gfw2r3uv7zemlkpyuc3utvyg5y
2020 Index IEEE Transactions on Systems, Man, and Cybernetics: Systems Vol. 50
2020
IEEE Transactions on Systems, Man & Cybernetics. Systems
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., +, TSMC July 2020 2351-2361 Neural Network-Based Adaptive Control for Pure-Feedback Stochastic Nonlinear Systems With Time-Varying Delays and Dead-Zone Input. ...
doi:10.1109/tsmc.2021.3054492
fatcat:zartzom6xvdpbbnkcw7xnsbeqy
Low-complexity Adaptive Tracking Control for Unknown Pure Feedback Nonlinear Systems with Multiple Constraints
2019
IEEE Access
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INDEX TERMS Pure feedback nonlinear systems, low-complexity adaptive control, full state constraints, input saturation, prescribed performance. ...
constraints, full states constraints, and input saturation constraint. ...
In [26] , an adaptive neural tracking control problem for a class of MIMO stochastic nonlinear pure-feedback systems with full-state constraints and input saturation was investigated, which employs a ...
doi:10.1109/access.2019.2902021
fatcat:wnretk3w5rha3lgk6oggiinkh4
Robust Adaptive Tracking Control of the Underwater Robot with Input Nonlinearity Using Neural Networks
2010
International Journal of Computational Intelligence Systems
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Backstepping control of the system dynamics is introduced to develop full state feedback tracking control. ...
Using parameter adaptation, backstepping control and variable structure based techniques, the robust adaptive tracking control is presented for underwater robots to handle the uncertainties, saturation ...
The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation. ...
doi:10.1080/18756891.2010.9727730
fatcat:mwliz532c5a2xfqcj4qhnl3wce
Robust Adaptive Tracking Control of the Underwater Robot with Input Nonlinearity Using Neural Networks
2010
International Journal of Computational Intelligence Systems
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Backstepping control of the system dynamics is introduced to develop full state feedback tracking control. ...
Using parameter adaptation, backstepping control and variable structure based techniques, the robust adaptive tracking control is presented for underwater robots to handle the uncertainties, saturation ...
The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation. ...
doi:10.2991/ijcis.2010.3.5.13
fatcat:2gvxdcgk6jgrlc3qjuxatga6sa
Adaptive Neural Fault-Tolerant Control for the Yaw Control of UAV Helicopters with Input Saturation and Full-State Constraints
2020
Applied Sciences
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The scheme incorporates a non-affine nonlinear system that manages actuator faults, input saturation, full-state constraints, and external disturbances. ...
In this paper, an adaptive neural fault-tolerant tracking control scheme is presented for the yaw control of an unmanned-aerial-vehicle helicopter. ...
In [36] , an adaptive neural control was addressed for a class of stochastic pure-feedback nonlinear time-delay systems with unknown direction control gains and full-state constraints. ...
doi:10.3390/app10041404
fatcat:egafmpowhvgsxjd6thzx7nbwfa
2020 Index IEEE Transactions on Fuzzy Systems Vol. 28
2020
IEEE transactions on fuzzy systems
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., and Shieh, J., An Optimized Type-2 Self-Organizing Fuzzy Logic Controller Applied in Anesthesia for Propofol Dosing to Regulate BIS; TFUZZ June 2020 1062-1072 Weinstein, A., see Veloz, A., TFUZZ Jan ...
Adaptive Fuzzy Control for High-Order Nonlinear Time-Delay Systems With Full-State Constraints and Input Saturation. ...
., +, TFUZZ Jan. 2020 122-133 Adaptive Fuzzy Control for High-Order Nonlinear Time-Delay Systems With Full-State Constraints and Input Saturation. ...
doi:10.1109/tfuzz.2020.3048828
fatcat:vml5fun6szcqbhpceebk3xfg2u
Adaptive Neural Tracking Control for a Class of Pure-Feedback Systems with Output Constraints Based on Event-triggered Strategy
2020
IEEE Access
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In this paper, an adaptive event-triggered tracking control problem is considered for a class of pure-feedback nonlinear systems with output constraints. ...
The simulation results prove the effectiveness of the controller design. INDEX TERMS Pure-feedback nonlinear systems, event-triggered control, output constraints, RBF neural network. ...
Reference [9] introduced an adaptive control for a class of nonlinear pure-feedback systems with full state constraints. ...
doi:10.1109/access.2020.2984344
fatcat:xo6mmd6msjgizdgbdp65kwtm7y
Adaptive Neural Network Control for Nonlinear Hydraulic Servo-System with Time-Varying State Constraints
2017
Complexity
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An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. ...
Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual systems. ...
Acknowledgments The work is supported by the National Natural Science Foundation of China (61603164, 61473139, and 61622303) and the project for Distinguished Professor of Liaoning Province. ...
doi:10.1155/2017/6893521
fatcat:ptsqsi2izfbx7dduoftburzj2u
Q-Learning Neural Controller for Steam Generator Station in Micro Cogeneration Systems
2021
Energies
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The example is considered for the implementation of advanced control systems in micro-, small- and medium-power cogeneration and trigeneration systems in order to improve their final efficiency and increase ...
The work shows how the model is adapted to the real system and the impact of the control algorithms on the efficiency of the combustion process. ...
Introduction The problem of optimal control of nonlinear multi-input multi-output (MIMO) systems is very complex [1] [2] [3] [4] . ...
doi:10.3390/en14175334
doaj:fe7ebe7a25fe4a5c915578502ced0a79
fatcat:5xx7c3e6nncibdehvsfygrxdym
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