Ming-Feng Ge

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This paper investigates the target tracking problem for networked robotic systems (NRSs) under sampled interaction. The target is assumed to be time-varying and described by a second-order oscillator. Two novel distributed controller-estimator algorithms (DCEA), which consist of both continuous and discontinuous signals, are presented. Based on the(More)
Comparing with traditional fixed formation for a group of dynamical systems, time-varying formation can produce the following benefits: i) covering the greater part of complex environments; ii) collision avoidance. This paper studies the time-varying formation tracking for multiple manipulator systems (MMSs) under fixed and switching directed graphs with a(More)
A novel adaptive sliding mode control (ASMC) algorithm is derived to deal with seam tracking control problem of welding robotic manipulator, during the process of large-scale structure component welding. The controllers robustness is verified by the Lyapunov stability theory, and the analytical results show that the proposed algorithm enables better(More)
A novel adaptive sliding mode control algorithm is derived to deal with synchronized joint position tracking control of robot manipulators. The proposed algorithm does not require the precise dynamic model, and is very practical. The cross-coupled technology is incorporated into the adaptive sliding mode control architecture through feedback of joint(More)
This paper studies the task-space coordinated tracking of a time-varying leader for multiple heterogeneous manipulators (MHMs), containing redundant manipulators and nonredundant ones. Different from the traditional coordinated control, distributed controller-estimator algorithms (DCEA), which consist of local algorithms and networked algorithms, are(More)
This paper investigates the optimal modified tracking performance of multi-input multi-output (MIMO) networked control systems (NCSs) with packet dropouts and bandwidth constraints. Some explicit expressions are obtained by using co-prime factorization and the spectral decomposition technique. The obtained results show that the optimal modified tracking(More)
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