Direct adaptive NN control for a class of discrete-time nonlinear strict-feedback systems. - Yan-Jun Liu 003; Guoxing Wen 001; Shaocheng Tong (Neurocomputing, 2010)

Adaptive Robust NN Control of Nonlinear Systems. - Guoxing Wen 001; Yan-Jun Liu 003; C. L. Philip Chen (ISNN (2), 2011)

Adaptive Neural Output Feedback Tracking Control for a Class of Uncertain Discrete-Time Nonlinear Systems. - Yan-Jun Liu 003; C. L. Philip Chen; Guoxing Wen 001; Shaocheng Tong (IEEE Trans. Neural Networks, 2011)

Distributed consensus control using neural network for a class of nonlinear multi-agent systems. - Guoxing Wen 001; C. L. Philip Chen (SMC, 2012)

Direct adaptive robust NN control for a class of discrete-time nonlinear strict-feedback SISO systems. - Guoxing Wen 001; Yan-Jun Liu 003; C. L. Philip Chen (Neural Comput. Appl., 2012)

Adaptive NN Consensus Control for a Class of Nonlinear Multi-agent Time-Delay Systems. - Guoxing Wen 001; C. L. Philip Chen (SMC, 2013)

Fuzzy Neural Network-Based Adaptive Control for a Class of Uncertain Nonlinear Stochastic Systems. - C. L. Philip Chen; Yan-Jun Liu 003; Guoxing Wen 001 (IEEE Trans. Cybern., 2014)

Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks. - C. L. Philip Chen; Guoxing Wen 001; Yan-Jun Liu 003; Fei-Yue Wang 001 (IEEE Trans. Neural Networks Learn. Syst., 2014)

Adaptive NN consensus tracking control of a class of nonlinear multi-agent systems. - Jun Feng; Guoxing Wen 001 (Neurocomputing, 2015)

Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems. - C. L. Philip Chen; Guoxing Wen 001; Yan-Jun Liu 003; Zhi Liu 001 (IEEE Trans. Cybern., 2016)

Approximation-Based Adaptive Neural Tracking Control of an Uncertain Robot with Output Constraint and Unknown Time-Varying Delays. - Dapeng Li 004; Yan-Jun Liu 003; Dong-Juan Li; Shaocheng Tong; Duo Meng; Guoxing Wen 001 (ISNN (2), 2017)

Neural Network-Based Adaptive Leader-Following Consensus Control for a Class of Nonlinear Multiagent State-Delay Systems. - Guoxing Wen 001; C. L. Philip Chen; Yan-Jun Liu 003; Zhi Liu 001 (IEEE Trans. Cybern., 2017)

Artificial Potential-Based Adaptive H∞ Synchronized Tracking Control for Accommodation Vessel. - Guoxing Wen 001; Shuzhi Sam Ge; Fangwen Tu; Yoo Sang Choo (IEEE Trans. Ind. Electron., 2017)

Simulation and Comparison of Different Types of First-order Decentralized Sliding Mode Estimators. - Ning Zhou; Guoxing Wen 001; Jie Huang 007; Qingkai Yang; Liangming Chen (ICARCV, 2018)

Optimized Multi-Agent Formation Control Based on an Identifier-Actor-Critic Reinforcement Learning Algorithm. - Guoxing Wen 001; C. L. Philip Chen; Jun Feng; Ning Zhou (IEEE Trans. Fuzzy Syst., 2018)

Formation Control With Obstacle Avoidance for a Class of Stochastic Multiagent Systems. - Guoxing Wen 001; C. L. Philip Chen; Yan-Jun Liu 003 (IEEE Trans. Ind. Electron., 2018)

Optimized Backstepping for Tracking Control of Strict-Feedback Systems. - Guoxing Wen 001; Shuzhi Sam Ge; Fangwen Tu (IEEE Trans. Neural Networks Learn. Syst., 2018)

Design of Variable-Gain First Order Sliding Mode and its Application to Spacecraft Attitude Synchronization. - Ning Zhou; Riqing Chen; Li Li 050; Guoxing Wen 001 (IEEE Access, 2019)

Formation control with obstacle avoidance of second-order multi-agent systems under directed communication topology. - Guoxing Wen 001; C. L. Philip Chen; Hui Dou; Hongli Yang; Chunfang Liu (Sci. China Inf. Sci., 2019)

Adaptive Tracking Control of Surface Vessel Using Optimized Backstepping Technique. - Guoxing Wen 001; Shuzhi Sam Ge; C. L. Philip Chen; Fangwen Tu; Shengnan Wang (IEEE Trans. Cybern., 2019)

Optimized Adaptive Nonlinear Tracking Control Using Actor-Critic Reinforcement Learning Strategy. - Guoxing Wen 001; C. L. Philip Chen; Shuzhi Sam Ge; Hongli Yang; Xiaoguang Liu (IEEE Trans. Ind. Informatics, 2019)

Adaptive Neural Network Leader-Follower Formation Control for a Class of Second-Order Nonlinear Multi-Agent Systems With Unknown Dynamics. - Guoxing Wen 001; Chenyang Zhang; Ping Hu; Yang Cui 002 (IEEE Access, 2020)

Simplified optimized control using reinforcement learning algorithm for a class of stochastic nonlinear systems. - Guoxing Wen 001; C. L. Philip Chen; Wei Nian Li (Inf. Sci., 2020)

Adaptive neural network control for time-varying state constrained nonlinear stochastic systems with input saturation. - Qidan Zhu; Yongchao Liu; Guoxing Wen 001 (Inf. Sci., 2020)

Optimized Formation Control Using Simplified Reinforcement Learning for a Class of Multiagent Systems With Unknown Dynamics. - Guoxing Wen 001; C. L. Philip Chen; Bin Li 042 (IEEE Trans. Ind. Electron., 2020)

Adaptive Neural Network Optimized Control Using Reinforcement Learning of Critic-Actor Architecture for a Class of Non-Affine Nonlinear Systems. - Xue Yang; Bin Li 042; Guoxing Wen 001 (IEEE Access, 2021)

Command-filter-based adaptive finite-time consensus control for nonlinear strict-feedback multi-agent systems with dynamic leader. - Yang Cui 002; Xiaoping Liu 004; Xin Deng; Guoxing Wen 001 (Inf. Sci., 2021)

Simplified Optimized Backstepping Control for a Class of Nonlinear Strict-Feedback Systems With Unknown Dynamic Functions. - Guoxing Wen 001; C. L. Philip Chen; Shuzhi Sam Ge (IEEE Trans. Cybern., 2021)

Reinforcement learning-based optimised control for a class of second-order nonlinear dynamic systems. - Bin Li 042; Xue Yang; Ranran Zhou; Guoxing Wen 001 (Int. J. Syst. Sci., 2022)

Optimized tracking control based on reinforcement learning for a class of high-order unknown nonlinear dynamic systems. - Guoxing Wen 001; Ben Niu 003 (Inf. Sci., 2022)

Optimized Backstepping Control Using Reinforcement Learning of Observer-Critic-Actor Architecture Based on Fuzzy System for a Class of Nonlinear Strict-Feedback Systems. - Guoxing Wen 001; Bin Li 042; Ben Niu 003 (IEEE Trans. Fuzzy Syst., 2022)

Adaptive Tracking Control for Perturbed Strict-Feedback Nonlinear Systems Based on Optimized Backstepping Technique. - Yongchao Liu; Qidan Zhu; Guoxing Wen 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

Optimized Backstepping Tracking Control Using Reinforcement Learning for Quadrotor Unmanned Aerial Vehicle System. - Guoxing Wen 001; Wei Hao 003; Weiwei Feng; Kaizhou Gao (IEEE Trans. Syst. Man Cybern. Syst., 2022)

Optimized Leader-Follower Consensus Control Using Reinforcement Learning for a Class of Second-Order Nonlinear Multiagent Systems. - Guoxing Wen 001; Bin Li 042 (IEEE Trans. Syst. Man Cybern. Syst., 2022)

Tracking control based on adaptive Bernstein polynomial approximation for a class of unknown nonlinear dynamic systems. - Guoxing Wen 001; Yongchao Liu (J. Frankl. Inst., 2023)

Optimized Backstepping Consensus Control Using Reinforcement Learning for a Class of Nonlinear Strict-Feedback-Dynamic Multi-Agent Systems. - Guoxing Wen 001; C. L. Philip Chen (IEEE Trans. Neural Networks Learn. Syst., 2023)

Optimized Backstepping Tracking Control Using Reinforcement Learning for a Class of Stochastic Nonlinear Strict-Feedback Systems. - Guoxing Wen 001; Liguang Xu; Bin Li 042 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Reinforcement Learning Based Optimized Sliding-Mode Consensus Control of High-Order Nonlinear Canonical Dynamic Multiagent System. - Zijun Li 008; Yanfen Song; Guoxing Wen 001 (IEEE Syst. J., 2023)

Optimized dead-zone inverse control using reinforcement learning and sliding-mode mechanism for a class of high-order nonlinear systems. - Shuaihua Ma; Wenxia Sun; Guoxing Wen 001 (Eur. J. Control, 2024)

Optimized leader-follower consensus control for high-order nonlinear multi-agent system modeled in canonical dynamic form. - Zijun Li 008; Yanfen Song; Bin Li 042; Guoxing Wen 001 (J. Frankl. Inst., 2024)

Optimized backstepping consensus control using adaptive observer-critic-actor reinforcement learning for strict-feedback multi-agent systems. - Jiahao Zhu; Guoxing Wen 001; Kalyana C. Veluvolu (J. Frankl. Inst., 2024)

Game-Based Backstepping Design for Strict-Feedback Nonlinear Multi-Agent Systems Based on Reinforcement Learning. - Jia Long; Dengxiu Yu; Guoxing Wen 001; Li Li 050; Zhen Wang 004; C. L. Philip Chen (IEEE Trans. Neural Networks Learn. Syst., 2024)

Adaptive neural network observer control for a class of nonlinear strict-feedback systems with unmeasurable states. - Ranran Zhou; Guoxing Wen 001; Jiahao Zhu; Bin Li 042 (Int. J. Control, 2024)

Adaptive Control of Constrained Nonlinear CPSs Under Deception Attacks Through Sensor and Actuator Networks. - Yahui Gao; Ben Niu 003; Wendi Chen; Huanqing Wang 001; Chaoxu Mu; Guoxing Wen 001 (IEEE Trans. Circuits Syst. II Express Briefs, 2024)

Time-Varying Optimal Formation Control for Second-Order Multiagent Systems Based on Neural Network Observer and Reinforcement Learning. - Jie Lan; Yan-Jun Liu 003; Dengxiu Yu; Guoxing Wen 001; Shaocheng Tong; Lei Liu 006 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Optimized Backstepping Combined With Dynamic Surface Technique for Single-Input-Single-Output Nonlinear Strict-Feedback System. - Guoxing Wen 001; Ranran Zhou; Yanlong Zhao; Ben Niu 003 (IEEE Trans. Syst. Man Cybern. Syst., 2024)

Optimized Fuzzy Attitude Control of Quadrotor Unmanned Aerial Vehicle Using Adaptive Reinforcement Learning Strategy. - Guoxing Wen 001; Dengxiu Yu; Yanlong Zhao (IEEE Trans. Aerosp. Electron. Syst., 2024)

Optimized inverse dead-zone formation control using reinforcement learning for the nonlinear single-integrator dynamic multi-agent system. - Guoxing Wen 001; Wenxia Sun; Shuaihua Ma (Neurocomputing, 2025)

Optimized consensus control of multi-manipulator system having actuator fault using reinforcement learning approximation strategy. - Yu Cao; Guoxing Wen 001; Baoshuo Feng; Bin Li 042 (Inf. Sci., 2025)

Optimised backstepping control for the nonlinear strict-feedback system having unknown control dead-zone. - Wenxia Sun; Shuaihua Ma; Bin Li 042; Guoxing Wen 001 (Int. J. Control, 2025)

Optimized Leader-Follower Consensus Control of Multi-QUAV Attitude System Using Reinforcement Learning and Backstepping. - Guoxing Wen 001; Yanfen Song; Zijun Li 008; Bin Li 042 (IEEE Trans. Emerg. Top. Comput. Intell., 2025)