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Jinzhu Peng

Showing results (1-10 of 11) with videos related to

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ISA Transactions|July 27, 2011
Identification and adaptive neural network control of a DC motor system with dead-zone characteristicsJinzhu Peng, Rickey Dubay
Mathematical Biosciences and Engineering : MBE|December 14, 2021
A Bio-inspired trajectory planning method for robotic manipulators based on improved bacteria foraging optimization algorithm and tau theoryZhiqiang Wang, Jinzhu Peng, Shuai Ding
ISA Transactions|June 12, 2014
Robust adaptive tracking control for nonholonomic mobile manipulator with uncertaintiesJinzhu Peng, Jie Yu, Jie Wang
Computational Intelligence and Neuroscience|February 24, 2015
A novel multiple instance learning method based on extreme learning machineJie Wang, Liangjian Cai, Jinzhu Peng, et al.
IEEE Transactions on Neural Networks and Learning Systems|May 31, 2023
Event-Triggered Adaptive Neural Impedance Control of Robotic SystemsShuai Ding, Jinzhu Peng, Hui Zhang, et al.
ISA Transactions|August 20, 2024
Event-triggered adaptive neural prescribed performance admittance control for constrained robotic systems without velocity measurementsPenghui Fan, Jinzhu Peng, Hongshan Yu, et al.
ISA Transactions|February 22, 2022
High-order control barrier functions-based impedance control of a robotic manipulator with time-varying output constraintsHaijing Wang, Jinzhu Peng, Fangfang Zhang, et al.
ISA Transactions|March 7, 2019
Robust adaptive motion/force control scheme for crawler-type mobile manipulator with nonholonomic constraint based on sliding mode control approachJinzhu Peng, Zeqi Yang, Yaonan Wang, et al.
IEEE Transactions on Cybernetics|July 9, 2025
Adaptive Safety-Based Tracking Control for Uncertain Robotic Systems With Input-Output Constraints: A Neural Network-Based Augmented High-Order Control Barrier Function ApproachHaijing Wang, Jinzhu Peng, Yaqiang Liu, et al.
IEEE Transactions on Neural Networks and Learning Systems|July 9, 2026
GVA-BLS: Gaussian Vector Autoregression Broad Learning System Based on Randomly Distributed Embedding for Multistep-Ahead PredictionMingyuan Yu, Bowen Sun, Heshan Wang, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
ISA Transactions|July 27, 2011
Identification and adaptive neural network control of a DC motor system with dead-zone characteristicsJinzhu Peng, Rickey Dubay
Mathematical Biosciences and Engineering : MBE|December 14, 2021
A Bio-inspired trajectory planning method for robotic manipulators based on improved bacteria foraging optimization algorithm and tau theoryZhiqiang Wang, Jinzhu Peng, Shuai Ding
ISA Transactions|June 12, 2014
Robust adaptive tracking control for nonholonomic mobile manipulator with uncertaintiesJinzhu Peng, Jie Yu, Jie Wang
Computational Intelligence and Neuroscience|February 24, 2015
A novel multiple instance learning method based on extreme learning machineJie Wang, Liangjian Cai, Jinzhu Peng, et al.
IEEE Transactions on Neural Networks and Learning Systems|May 31, 2023
Event-Triggered Adaptive Neural Impedance Control of Robotic SystemsShuai Ding, Jinzhu Peng, Hui Zhang, et al.
ISA Transactions|August 20, 2024
Event-triggered adaptive neural prescribed performance admittance control for constrained robotic systems without velocity measurementsPenghui Fan, Jinzhu Peng, Hongshan Yu, et al.
ISA Transactions|February 22, 2022
High-order control barrier functions-based impedance control of a robotic manipulator with time-varying output constraintsHaijing Wang, Jinzhu Peng, Fangfang Zhang, et al.
ISA Transactions|March 7, 2019
Robust adaptive motion/force control scheme for crawler-type mobile manipulator with nonholonomic constraint based on sliding mode control approachJinzhu Peng, Zeqi Yang, Yaonan Wang, et al.
IEEE Transactions on Cybernetics|July 9, 2025
Adaptive Safety-Based Tracking Control for Uncertain Robotic Systems With Input-Output Constraints: A Neural Network-Based Augmented High-Order Control Barrier Function ApproachHaijing Wang, Jinzhu Peng, Yaqiang Liu, et al.
IEEE Transactions on Neural Networks and Learning Systems|July 9, 2026
GVA-BLS: Gaussian Vector Autoregression Broad Learning System Based on Randomly Distributed Embedding for Multistep-Ahead PredictionMingyuan Yu, Bowen Sun, Heshan Wang, et al.
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