By designing the decentralized time-regularized (Zeno-free) event-triggered strategies for the state-feedback control law, this paper considers the stochastic stabilization of a class of networked controlsystems, whe...
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By designing the decentralized time-regularized (Zeno-free) event-triggered strategies for the state-feedback control law, this paper considers the stochastic stabilization of a class of networked controlsystems, where two sources of randomness exist in multiple decentralized networks that operate asynchronously and independently: the communication channels are constrained by the stochastic network delays and also by Poisson pulsing denial-of-service (Pp-DoS) attacks. The time delay in the network denotes the length from a transmission instant to the corresponding update instant, and is supposed to be a continuous random variable subject to certain continuous probability distribution;while the attacks' cardinal number is a discrete random variable supposed to be subject to Poisson distribution, so the inter-attack time, i.e., the time between two consecutive attack instants, is subject to exponential distribution. The considered system is modeled as a stochastic hybrid formalism, where the randomness enters through the jump map into the reset value (the inter-attack time directly related) of each triggered strategy. By only sampling/transmitting state measurements when needed and simultaneously by taking the specific medium access protocols into account, the designed event-triggered strategies are synthesized in a state-based and decentralized form, which are robust (tolerable well) to stochastic network delays, under different tradeoff-conditions between the minimum inter-event times, maximum allowable delays (i.e., potentially tolerable delays) and the frequencies of attacks. Using stochastic hybrid tools to combine attack-active parts with attack-over parts, the designed triggered strategies, if designed well according to the actual system needs, can tolerate (be resilient to) the Pp-DoS attacks and stochastic network delays without jeopardizing the stability and Zeno-freeness, which is verified by the robust global attitude stabilization of flexible combined ro
Optical tactile sensors provide robots with rich force information for robot grasping in unstructured environments. The fast and accurate calibration of three-dimensional contact forces holds significance for new sens...
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Vision-based tactile sensors (VBTSs) provide high-resolution tactile images crucial for robot in-hand manipulation. However, force sensing in VBTSs is underutilized due to the costly and time-intensive process of acqu...
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The concept of "autonomous greenhouse" hints the automatic setting of control target, and giving orders on facilities to reach these targets (set point). Information and communication technologies are widely...
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ISBN:
(数字)9781728176871
ISBN:
(纸本)9781728176888
The concept of "autonomous greenhouse" hints the automatic setting of control target, and giving orders on facilities to reach these targets (set point). Information and communication technologies are widely used, but how to integrate common sense or knowledge in decision-making is still challenging. Semi-autonomous greenhouse control is to set rules with joint advantages of experienced grower and powerful machinery, with the support of knowledge graph and semantic analysis. The contribution of each side is dependent on the intelligence level of computers, the availability of data, etc. In this work, the hybrid system between human and machinery is shown with the temperature control in greenhouse. The target is set mainly by expert knowledge, while the temperature controlled by vent opening is decided by an algorithm. Result shows that the target is better reached compared to that of the experience-based approach. This example shows the feasibility of human-machine hybrid intelligence system for greenhouse environment control. Although this approach is tested for temperature control, it can be extended to control multiple factors simultaneously (temperature, light intensity, humidity, etc.) by driving multiple facilities (heating, lightening, venting, etc.).
Optical tactile sensors play a pivotal role in robot perception and manipulation tasks. The membrane of these sensors can be painted with markers or remain markerless, enabling them to function in either marker or mar...
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We address robust stabilization problem for networked controlsystems with nonlinear uncertainties and packet losses by modelling such systems as a class of uncertain switched systems. Based on theories on switched Ly...
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ISBN:
(纸本)9781424445233
We address robust stabilization problem for networked controlsystems with nonlinear uncertainties and packet losses by modelling such systems as a class of uncertain switched systems. Based on theories on switched Lyapunov functions, we derive the robustly stabilizing conditions for state feedback stabilization and design packet-loss dependent controllers by solving some matrix inequalities. A numerical example and some simulations are worked out to demonstrate the effectiveness of the proposed design method.
In this paper, we study the task of hallucinating an authentic high-resolution (HR) face from an occluded thumbnail. We propose a multi-stage Progressive Upsampling and Inpainting Generative Adversarial Network, dubbe...
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Flexibility and robustness have become key points in the development of surgical robot controller for physical interactions. However, the conventional impedance control schemes unaware of the actual surgical scenario,...
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ISBN:
(数字)9781728158716
ISBN:
(纸本)9781728158723
Flexibility and robustness have become key points in the development of surgical robot controller for physical interactions. However, the conventional impedance control schemes unaware of the actual surgical scenario, including complex physical interaction on the robot arm, lead to the loss of accuracy. In this paper, a hierarchical task impedance control scheme is proposed for Minimally Invasive Surgery (MIS) based on an operational space formulation of a 7 DoFs redundant robot. Its redundancy is exploited to guarantee a remote center of motion (RCM) constraint and to provide a flexible workspace for the medical staff to assist physicians. In addition to the achievement of the classical whole-body impedance control, the issue of uncertain disturbances will be addressed by a decoupled adaptive approximation based on a radial basis function neural network (RBFNN) within the control framework. Task performances under the hierarchical task impedance controller were validated and compared with previous work in the literature. Experimental results showed its improved performance in terms of positional error and RCM constraint, regardless of the existing uncertain physical interaction.
The knowledge of solar greenhouse growers on environment control plays an important role in greenhouse production and management. We proposed a way to extract the control strategies from the monitored data of greenhou...
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The knowledge of solar greenhouse growers on environment control plays an important role in greenhouse production and management. We proposed a way to extract the control strategies from the monitored data of greenhouses by building a long short-term memory (LSTM) model. The result is verified according to the real monitored data of a solar greenhouse, which shows that the model can learn the control strategy of a ventilator in the solar greenhouse. Through monitored data and models, the knowledge of greenhouse ventilation control can be learned, and automatic control can be achieved in a greenhouse with a similar configuration.
A brain-computer interface (BCI) establishes a direct communication pathway between the human brain and a computer. It has been widely used in medical diagnosis, rehabilitation, education, entertainment, etc. Most res...
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