Saturated output feedback tracking control for robot manipulators via fuzzy self-tuning. - Huashan Liu; Shiqiang Zhu; Zhang-wei Chen (J. Zhejiang Univ. Sci. C, 2010)

Almost surely exponential stability of neural networks with Lévy noise and Markovian switching. - Wuneng Zhou; Jun Yang; Xueqing Yang; Anding Dai; Huashan Liu; Jian-An Fang (Neurocomputing, 2014)

Improved adaptive output feedback controller for flexible-joint robot manipulators. - Huashan Liu; Yong Huang; Wenxiang Wu (ICIA, 2016)

Saturated adaptive back-stepping control for robot manipulators with RBF neural network approximation. - Huashan Liu; Yajun Zhang; Wenxiang Wu (ICIA, 2016)

A Real-Time Data-Driven control System for Multi-motor-Driven Mechanisms. - Huashan Liu; Lingbin Zeng; Wuneng Zhou; Shiqiang Zhu (Int. J. Robotics Autom., 2017)

Synchronisation control for neutral-type multi-slave stochastic hybrid systems. - Jun Zhou 003; Feng Pan; Tingting Cai; Yuqing Sun 003; Wuneng Zhou; Huashan Liu (Int. J. Syst. Sci., 2017)

Robust adaptive output feedback tracking control for flexible-joint robot manipulators based on singularly perturbed decoupling. - Huashan Liu; Yong Huang (Robotica, 2018)

Exponential stability for Markovian neutral stochastic systems with general transition probabilities and time-varying delay. - Xin Zhang 037; Huashan Liu; Yiyuan Zheng; Yuqing Sun 003; Wuneng Zhou; Yiming Gan; Guo Wei (Trans. Inst. Meas. Control, 2019)

A Novel Post-Processing Method Based on a Weighted Composite Filter for Enhancing Semantic Segmentation Results. - Xin Cheng; Huashan Liu (Sensors, 2020)

Adaptive neural backstepping control for flexible-joint robot manipulator with bounded torque inputs. - Xin Cheng; Yajun Zhang; Huashan Liu; Dirk Wollherr; Martin Buss (Neurocomputing, 2021)

Easy Pose-Error Calibration for Articulated Serial Robot Based on Three-Closed-Loop Transformations. - Mingjun Cai; Huashan Liu; Menghua Dong (IEEE Trans. Instrum. Meas., 2021)

A General Framework of Motion Planning for Redundant Robot Manipulator Based on Deep Reinforcement Learning. - Xiangjian Li; Huashan Liu; Menghua Dong (IEEE Trans. Ind. Informatics, 2022)

A Holistic Power Management Strategy of Microgrids Based on Model Predictive Control and Particle Swarm Optimization. - Yinghao Shan; Jiefeng Hu; Huashan Liu (IEEE Trans. Ind. Informatics, 2022)

Extensively Explored and Evaluated Actor-Critic With Expert-Guided Policy Learning and Fuzzy Feedback Reward for Robotic Trajectory Generation. - Fengkang Ying; Huashan Liu; Rongxin Jiang 002; Menghua Dong (IEEE Trans. Ind. Informatics, 2022)

Robotic motion planning with obstacle avoidance based on hierarchical deep reinforcement learning. - Guoquan Zhao; Fengkang Ying; Zuowei Pang; Huashan Liu (RobCE, 2023)

Towards Efficient Deep Hashing Retrieval: Condensing Your Data via Feature-Embedding Matching. - Tao Feng; Jie Zhang; Huashan Liu; Zhijie Wang 001; Shengyuan Pang (ICASSP, 2025)

Robotic Motion Planning Based on Deep Reinforcement Learning and Artificial Neural Networks. - Huashan Liu; Xiangjian Li; Menghua Dong; Yuqing Gu; Bo Shen 001 (IEEE Trans Autom. Sci. Eng., 2025)

WarmFed: Federated Learning with Warm-Start for Globalization and Personalization Via Personalized Diffusion Models. - Tao Feng; Jie Zhang; Xiangjian Li; Rong Huang 003; Huashan Liu; Zhijie Wang 001 (CoRR, 2025)