The efficient control of serial robots in the presence of dynamic uncertainties and external disturbances is significant in many industrial applications. In this work, an adaptive sliding mode control (ASMC) approach ...
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ISBN:
(数字)9798331527471
ISBN:
(纸本)9798331527488
The efficient control of serial robots in the presence of dynamic uncertainties and external disturbances is significant in many industrial applications. In this work, an adaptive sliding mode control (ASMC) approach with deep recurrent neural network (DRNN) is proposed for a 6-degree-of-freedom (6-DOF) industrial serial robot in joint space. A model-based sliding mode controller is developed to maintain the strong robustness of the robotic system. A deep recurrent neural network is designed to estimate the lumped system uncertainties in the controller. It consists of a feedforward structure through two hidden layers and a feedback loop from the output layer to the input layer, which exhibits more powerful online learning ability and dynamic property than shallow feedforward neural networks. According to Lyapunov theorem, the adaptation laws of the neural network parameters are derived, and the stability of the controller can be guaranteed. Simulation results demonstrate the effectiveness and superiority of the DRNN-based ASMC strategy regarding estimation convergence speed and trajectory tracking accuracy.
Fixed-time stable dynamical systems are capable of achieving exact convergence to an equilibrium point within a fixed time that is independent of the initial conditions of the system. This property makes them highly a...
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ISBN:
(数字)9798350382655
ISBN:
(纸本)9798350382662
Fixed-time stable dynamical systems are capable of achieving exact convergence to an equilibrium point within a fixed time that is independent of the initial conditions of the system. This property makes them highly appealing for designing control, estimation, and optimization algorithms in applications with stringent performance requirements. How-ever, the set of tools available for analyzing the interconnection of fixed-time stable systems is rather limited compared to their asymptotic counterparts. In this paper, we address some of these limitations by exploiting the emergence of multiple time scales in nonlinear singularly perturbed dynamical systems, where the fast dynamics and the slow dynamics are fixed-time stable on their own. By extending the so-called composite Lyapunov method from asymptotic stability to the context of fixed-time stability, we provide a novel class of Lyapunov-based sufficient conditions to certify fixed-time stability in a class of singularly perturbed dynamical systems. The results are illustrated, analytically and numerically, using a fixed-time gradient flow system interconnected with a fixed-time plant and an additional high-order example.
As the basis of information war, military network plays a vital role in the development of war. Network availability is one of the most important performance of military network construction and operation. It is also ...
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Spacecraft trajectory design is a global search problem, where previous work has revealed specific solution structures that can be captured with data-driven methods. This paper explores two global search problems in t...
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Laser powder bed fusion of unsupported overhang structures, required for metamaterial lattices, are difficult to manufacture. In this study, process parameters are experimentally determined to successfully fabricate a...
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This paper studies the dynamical properties of closed-loop systems obtained from control barrier function-based safety filters. We provide a sufficient and necessary condition for the existence of undesirable equilibr...
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This study employs intersection point height frequency analysis to quantitatively assess the balance control strategies used by individuals with Parkinson's disease (PD) during quiet stance. The changes in balance...
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ISBN:
(数字)9798350382655
ISBN:
(纸本)9798350382662
This study employs intersection point height frequency analysis to quantitatively assess the balance control strategies used by individuals with Parkinson's disease (PD) during quiet stance. The changes in balance strategy are quantified using a triple inverted pendulum human model with a linear quadratic regulator as the neural balance controller. By considering both translational and angular body accelerations, we extract intersection point frequency curves that contain crucial information about the neuromuscular balance strategy of the PD patients. To contextualize our findings, we compare the observed frequency behavior with previous studies examining quiet stance in individuals without PD. This comprehensive investigation furnishes valuable insights into the disparities between the balance strategies of the PD patients and the healthy counterparts, shedding light on the influence of PD on balance control dynamics. The findings hold promising potential for applications in PD diagnostics and the development of robotic assistive devices for PD patient rehabilitation.
Nickel-based superalloys are widely used in aviation, aerospace, energy, petrochemical and other industrial fields due to their excellent high temperature strength, oxidation and corrosion resistance, excellent creep ...
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This paper presents the technique of flex-and-flip manipulation. It is suitable for grasping thin, flexible linear objects lying on a flat surface. During the manipulation process, the object is first flexed by a robo...
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Due to the challenging conditions of underwater environments, such as node mobility and large-scale networks, achieving localization in large-scale mobile underwater sensor networks (UWSN) is a difficult task. This pa...
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