Even the simple run of a medium size system dynamics model can be a cumbersome process, since the uncertainty of the parameters forces the modeler to consider many runs before being confident of how the model behaves....
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Strict quality of service requirements of industrial applications, challenged by harsh environments and huge interference especially in multi-vendor sites, demand incorporation of cognition in industrial wireless sens...
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ISBN:
(纸本)9781479966509
Strict quality of service requirements of industrial applications, challenged by harsh environments and huge interference especially in multi-vendor sites, demand incorporation of cognition in industrial wireless sensor networks (IWSNs). In this paper, a distributed protocol of light complexity for congestion regulation in cognitive IWSNs is proposed to improve the channel utilization while ensuring predetermined performance for specific devices, called primary devices. By sensing the congestion level of a channel with local measurements, a novel congestion control protocol is proposed by which every device decides whether it should continue operating on the channel, or vacate it in case of saturation. Such a protocol dynamically changes the congestion level based on variations of non-stationary wireless environment as well as traffic demands of the devices. The proposed protocol is implemented on STM32WI08 chips that offer IEEE 802.15.4 standard communications. Experimental results confirm substantial performance enhancement compared to the original standard, while imposing almost no signaling/computational overhead. In particular, channel utilization is increased by 56% with fairness and delay guarantees. The presented results provide useful insights on low-complexity adaptive congestion control mechanism in IWSNs.
This paper introduces a numerical method to estimate the region of attraction for polynomial nonlinear systems using sum of squares programming. This method computes a local Lyapunov function and an invariant set arou...
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Efficient handover algorithms are essential for highly performing cellular networks. These algorithms depend on numerous parameters, whose settings must be appropriately optimized to offer a seamless connectivity. Nev...
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In this paper we consider the minimization of 0-regularized nonlinear optimization problems, where the objective function is the sum of a smooth convex term and the 0 quasi-norm of the decision variable. We introduce ...
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In many animals intersegmental reflexes are important for postural control and movement making them ideal candidates for the bio-inspired design of medical treatment for neuromuscular injuries in cases such as drop fo...
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ISBN:
(纸本)9789897580543
In many animals intersegmental reflexes are important for postural control and movement making them ideal candidates for the bio-inspired design of medical treatment for neuromuscular injuries in cases such as drop foot and possibly in robot design. In this paper we study an intersegmental reflex of the foot (tarsus) of the locust hind leg, which is a reflex that raises the tarsus when the tibia is flexed and depresses it when the tibia is extended. A novel method is described to quantify the intersegmental responses in which an Artificial Neural Network, the Time Delay Neural Network, is applied. The architecture of the network is optimised through a metaheuristic algorithm to produce accurate predictions with short computational time and complexity and high generalisation to different individual responses. The results show that ANNs provide accurate predictions when trained with an average reflex response to Gaussian White Noise stimulation compared to autoregressive models. Furthermore, the network model can calculate the individual responses from each of the animals and responses to another input such as a sinusoid. A detailed understanding of such a reflex response could be included in the design of orthoses or functional electrical stimulation treatments to improve walking in patients with neuromuscular disorders.
This tutorial paper will discuss the development of novel state-of-the-art control approaches and theory for complex systems based on machine intelligence in order to enable full autonomy. Given the presence of modeli...
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ISBN:
(纸本)9781479917730
This tutorial paper will discuss the development of novel state-of-the-art control approaches and theory for complex systems based on machine intelligence in order to enable full autonomy. Given the presence of modeling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of teams of complex systems, there is a need for approaches that respond to situations not programmed or anticipated in design. Unfortunately, existing schemes for complex systems do not take into account recent advances of machine intelligence. We shall discuss on how to be inspired by the human brain and combine interdisciplinary ideas from different fields, i.e. computational intelligence, game theory, control theory, and information theory to develop new self-configuring algorithms for decision and control given the unavailability of model, the presence of enemy components and the possibility of network attacks. Due to the adaptive nature of the algorithms, the complex systems will be capable of breaking or splitting into parts that are themselves autonomous and resilient. The algorithms discussed will be characterized by strong abilities of learning and adaptivity. As a result, the complex systems will be fully autonomous, and tolerant to communication failures.
The power system now is a typical complex system, which has inherent characteristics of SOC. Studying on cascading failures are necessary and meaningful to insure the grid's safety, national security and economic ...
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ISBN:
(纸本)9781479947249
The power system now is a typical complex system, which has inherent characteristics of SOC. Studying on cascading failures are necessary and meaningful to insure the grid's safety, national security and economic development. This paper firstly establishes the indices of power system development diagnosis, which are closely relevant to the trigger of power system evolution. Then a cascading failure model is proposed, considering planning and evolution of the power system. This model is based on OPA model, including both fast dynamics and slow dynamics. The slow dynamic process simulates the evolution of power system, which represents the functions of the planning department, while the fast dynamic process simulates power flow and cascading failures, which takes the effects of dispatch, relay protection and automation into consideration. Moreover, simulations are tested on the case of Kaifeng-Shangqiu power system in Henan Province of China, and evolution results are presented.
In this paper, we propose an aperiodic formulation of Distributed Model Predictive control for the cooperation of multi-agent systems under additive bounded disturbances. In the proposed method, each agent solves an O...
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Surge Impedance Relay(SIR) is applied to DC system. Characteristics of SIR in DC line are analysed. A DC SIR algorithm implementing wavelet transform applied to HVDC line protection is proposed. The feasibility of DC ...
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ISBN:
(纸本)9781849198349
Surge Impedance Relay(SIR) is applied to DC system. Characteristics of SIR in DC line are analysed. A DC SIR algorithm implementing wavelet transform applied to HVDC line protection is proposed. The feasibility of DC SIR is verified and the performance of DC SIR is simulated and analysed.
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