“…Since the main focus of this study is reconfigurable robot hand design and the relevant control logic design for grasping, the large and sharply varying delays are not considered in this paper. For more information about guaranteeing system stability under large and sharply varying delays, please refer to [50]- [54].…”
This paper develops an innovative multilateral teleoperation system with two haptic devices on the master side and a newly designed reconfigurable multi-fingered robot on the slave side. A novel nonsingular fast terminal sliding-mode algorithm, together with varying dominance factors for cooperation, is proposed to offer this system's fast position and force tracking, as well as an integrated perception for the operator on the reconfigurable slave robot (manipulator). The Type-2 fuzzy model is used to describe the overall system dynamics, and accordingly a new fuzzy-model-based state observer is proposed to compensate for system uncertainties. A sliding-mode adaptive controller is designed to deal with the varying zero drift of the force sensors and force observers. The stability of the closed-loop system under time-varying delays is proved using Lyapunov-Krasovskii functions. Finally, experiments to grasp different objects are performed to verify the effectiveness of this multilateral teleoperation system.
“…Since the main focus of this study is reconfigurable robot hand design and the relevant control logic design for grasping, the large and sharply varying delays are not considered in this paper. For more information about guaranteeing system stability under large and sharply varying delays, please refer to [50]- [54].…”
This paper develops an innovative multilateral teleoperation system with two haptic devices on the master side and a newly designed reconfigurable multi-fingered robot on the slave side. A novel nonsingular fast terminal sliding-mode algorithm, together with varying dominance factors for cooperation, is proposed to offer this system's fast position and force tracking, as well as an integrated perception for the operator on the reconfigurable slave robot (manipulator). The Type-2 fuzzy model is used to describe the overall system dynamics, and accordingly a new fuzzy-model-based state observer is proposed to compensate for system uncertainties. A sliding-mode adaptive controller is designed to deal with the varying zero drift of the force sensors and force observers. The stability of the closed-loop system under time-varying delays is proved using Lyapunov-Krasovskii functions. Finally, experiments to grasp different objects are performed to verify the effectiveness of this multilateral teleoperation system.
“…The neural networks are applied with the design of new error transformed variables in [32] to let the tracking errors quickly converge to zero. The neural-networkbased passivity control scheme with the type-2 fuzzy model of master/slave subsystems is designed in [33] and [34], where the nonlinear teleoperation system is divided into a group of linear models for the implementation of robust control algorithms via mature linear theories.…”
The bilateral teleoperation technique has drawn much attention with its attractive superiority to implement the tasks in hazardous environments. Transmission delays and uncertainties are the two main challenges in the nonlinear bilateral teleoperation system to guarantee stability and achieve good transparency performance (including position tracking and force feedback) simultaneously. In this paper, a radial basis function neural network (RBFNN)-based adaptive sliding mode control design is developed for the nonlinear bilateral teleoperation system with transmission delays and uncertainties. For details, the reference trajectory producer is designed in both the master and slave sides to produce the passive reference trajectories for the tracking of master/slave manipulators. The RBFNN-based adaptive sliding mode controller is designed separately for the master and slave to achieve the good tracking performance under system uncertainties. To mitigate the negative effect of transmission delays on the system's stability, a projection mapping by saturation function is applied in the master side to guarantee the boundedness of the delayed environmental torque. Thus, the global stability and the good transparency performance with both position tracking and force feedback can be simultaneously achieved for our proposed method. The comparative experiment is carried out, and the results show the significant performance improvement with our proposed control design. INDEX TERMS Bilateral teleoperation, adaptive sliding mode control, neural network, transmission delays, uncertainties.
“…Could linear GPC be applied to the fractional-order nonlinear HTRS? The well-known Takagi-Sugeno (T-S) fuzzy model could approximate nonlinear systems universally [33][34][35]. The nonlinear model is described through fuzzy rules; then, a certain region of the system state is locally represented by the linearisation description [36,37].…”
This study focuses on a fuzzy generalised predictive control method for a fractional-order hydro-turbine regulating system (HTRS). Based on the Grünwald-Letnikov (G-L) definition of fractional calculus and discretisation, the fractional-order hydraulic servo system is transformed into the standard controlled autoregressive integrating moving average (CARMA) model. With the help of fuzzy linearisation theory, the fuzzy predictive model of the integer-order part of the HTRS is presented. Furthermore, by using the fourth-order Runge-Kutta algorithm, the obtained fuzzy predictive model can be easily transformed into the CARMA model. Then, based on the overall CARMA model and the generalised predictive control theory, a novel nonlinear fuzzy generalised predictive controller is designed for the fractional-order HTRS. Finally, numerical simulations are implemented to verify the validity and superiority of the proposed method. It also provides a reference for relevant hydropower systems.
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