A Wireless Sensor Network (WSN) is a collection of distributed, specialised sensors that can analyse, communicate, and sense data from a base station known as the sink. WSN is essential when a network connection is ne...
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ISBN:
(纸本)9798331300579
A Wireless Sensor Network (WSN) is a collection of distributed, specialised sensors that can analyse, communicate, and sense data from a base station known as the sink. WSN is essential when a network connection is needed immediately, such as in cases of emergency surveillance, remote monitoring, healthcare, military field communication, home automation, or industrial automation. Usually, sensor nodes are positioned in inaccessible or challenging-to-reach locations. Gathering data from sensor nodes and sending it to a sink is the WSN's main duty. In essence, the sensor nodes are clustered using the clustering approach. A sensor node designated as the Cluster Head (CH) in each cluster has the power to add and remove Cluster members. The gateway (GW) node in WSNs links to many clusters for multi-hop communication. The communication overhead for multi-hop communication is kept to a minimum and the quickest path between the source node and the sink is carefully chosen. Because the CH and GW nodes were carefully chosen, the WSN's lifespan is increased while the VI sensor nodes' energy consumption is reduced. The key challenge for cluster-based routing is choosing an efficient CH and GW node. For this reason, the REAS (Residual Energy Aware Angle-based Routing Protocol for Cluster-based Wireless Sensor Networks) is recommended for the strategic selection of the CH and GW nodes, leveraging elements such as the node's residual energy and the angle and distance between the node and the sink. The setup phase and steady-state phase of REAS are used to ensure efficient information routing from the source node to the sink. When the clusters are constructed using the CM, CH, and GW nodes, the shortest routing path is determined. During the steady-state phase, data are collected from the CMs and transferred to the sink. While evaluating REAS performance, end-to-end latency, remaining energy, longevity, packet delivery ratio, and energy efficiency are all taken into account. The RE
One of the most critical challenges in Robotic Eye Surgery (RES) is the applied force of the surgical instrument of the robot as it penetrates the human eye. Safe surgery requires accurate control of this force. In a ...
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ISBN:
(纸本)9798350311075
One of the most critical challenges in Robotic Eye Surgery (RES) is the applied force of the surgical instrument of the robot as it penetrates the human eye. Safe surgery requires accurate control of this force. In a teleoperated eye surgical system, there is likely to be a time delay that can affect the system control. This paper focuses on designing a predefined-time Sliding Mode control (SMC) method to control a teleoperated robotic eye surgical system under an unknown time delay of the communication channel. The Lyapunov theory is used to prove the system stability. For the master and slave parts, manipulator robots are considered for designing and testing the controller. MATLAB software is used to simulate the controller. The simulation results show the robustness of the controller against the time delay of the communication channel.
The 4th Industrial Revolution has driven innovations in integrating Information Technologies (IT) with Operations Technologies (OT). This integration is essential for developing Cyber-Physical Production Systems (CPPS...
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The need for electricity has become essential to human existence. All our enterprises, daily activities, communication, etc., rely on power. The issue is that as automation technology progresses and life becomes easie...
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Nowadays automation is extremely essential in academics. Especially, when data on training programs, conferences, and workshops are to be managed and certificates of attendees are to be sent. This paper proposes a com...
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The automation of height-increasing bridges during floating events is a crucial engineering challenge in areas prone to flooding or water surges. It proposes a solution to adjust the bridge height automatically based ...
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作者:
Zhan, LeiChn Energy Zhishen Control Technology Co.
Ltd. Beijing Engineering Research Center of Power Station Automation State R&D Center of Control System and Information Security Technologies for Energy Industry Beijing102211 China
Aiming at the operation and maintenance management and control issues of large-scale photovoltaic power stations, a smart photovoltaic power station control system based on DCS architecture was studied. In terms of sy...
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Electric vehicle (EV) batteries are essential to increasing the effectiveness and affordability of EVs. To optimize battery usage and improve performance and longevity, it is essential to establish the relationship be...
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In the modern world, robotics is a rapidly expanding and fascinating discipline. Robotics are now widely used in both business and household settings to complete difficult tasks in a more practical and straightforward...
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In recent years, advanced model-based and data-driven control methods are unlocking the potential of complex robotics systems, and we can expect this trend to continue at an exponential rate in the near future. Howeve...
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ISBN:
(纸本)9798350384581;9798350384574
In recent years, advanced model-based and data-driven control methods are unlocking the potential of complex robotics systems, and we can expect this trend to continue at an exponential rate in the near future. However, ensuring safety with these advanced control methods remains a challenge. A well-known tool to make controllers (either Model Predictive controllers or Reinforcement Learning policies) safe, is the so-called control-invariant set (a.k.a. safe set). Unfortunately, for nonlinear systems, such a set cannot be exactly computed in general. Numerical algorithms exist for computing approximate control-invariant sets, but classic theoretic control methods break down if the set is not exact. This paper presents our recent efforts to address this issue. We present a novel Model Predictive control scheme that can guarantee recursive feasibility and/or safety under weaker assumptions than classic methods. In particular, recursive feasibility is guaranteed by making the safe-set constraint move backward over the horizon, and assuming that such set satisfies a condition that is weaker than control invariance. Safety is instead guaranteed under an even weaker assumption on the safe set, triggering a safe task-abortion strategy whenever a risk of constraint violation is detected. We evaluated our approach on a simulated robot manipulator, empirically demonstrating that it leads to less constraint violations than state-of-the-art approaches, while retaining reasonable performance in terms of tracking cost, number of completed tasks, and computation time.
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