This paper develops a vector Lyapunov function based approach to the stability of continuous and discrete 2D nonlinear systems with Markovian jumps. Nonlinear continuous- time 2D systems described by a Roesser model a...
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In this paper we propose a novel target-tracking control scheme for a carangiform robotic fish based on a faithful dynamic model that combines rigid-body dynamics with Lighthill's large-amplitnde elongated-body **...
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ISBN:
(纸本)9781479900305
In this paper we propose a novel target-tracking control scheme for a carangiform robotic fish based on a faithful dynamic model that combines rigid-body dynamics with Lighthill's large-amplitnde elongated-body *** first average the dynamic model under periodic tail-actuation,which results in an average model with tail-beat patterns(bias,frequency,and amplitude) as new control inputs that axe nonlinearly *** introducing two new state variables,the orientation angle error and the distance between the robotic fish body and the target location,we derived the dynamic equations for these variables, which are then used in backstepping-based controller design.A hybrid controller is proposed,where the switching is determined by whether the orientation error is above a threshold *** Lyapunov analysis,we show that the trajectory of the robotic fish will converge to the target point if the given condition is ***,the effectiveness of the proposed control strategy is demonstrated through simulation results.
In this paper we propose sampled-data periodic predictor feedback controllers for linear systems with input *** any size of input delay and any prescribed sampling period,an explicit sampled-data periodic predictor fe...
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ISBN:
(纸本)9781479900305
In this paper we propose sampled-data periodic predictor feedback controllers for linear systems with input *** any size of input delay and any prescribed sampling period,an explicit sampled-data periodic predictor feedback controller is constructed and shown to be able to stabilize the given delay *** a controller utilizes only the state information at the latest sampling instant and the control inputs at some past sampling *** the condition that the open-loop system is not exponentially unstable(but maybe polynomially unstable),a truncated version of the sampled-data periodic predictor feedback controller is also proposed,which is a memoryless controller that needs only the state at the latest sampling *** of the closed-loop system under the truncated sampled-data periodic predictor feedback controller is *** numerical examples are given to illustrate the effectiveness of the proposed designs.
The Cyber-threats Situation Assessment (CSA) could show the macro security situation of Electric Power Information Networks (EPIN) in real time. Researching the efficient CSA method will be helpful to enhance the secu...
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ISBN:
(纸本)9781467347129
The Cyber-threats Situation Assessment (CSA) could show the macro security situation of Electric Power Information Networks (EPIN) in real time. Researching the efficient CSA method will be helpful to enhance the security protection ability of EPIN. A hierarchical CSA method, which is based on both the Analytic Hierarchy Process (AHP) and the Grey Clustering Algorithm (GCA), is proposed and implemented. The Cyber-threats Situation Value (CSV) is used to describe the cyber-threats situation. The higher CSV shows worse security situation, on the contrary, the lower CSV shows the better. In order to determine the weights of all cyber-threats, the AHP is used to design the hierarchical CSA index system that could divide all cyber-threats into the “Strong”, “Medium” and “Weak” 3 grey clustering classes. At the same time, the GCA is used to construct the criteria layer of index system. The key components of CSV could be clearly shown by those above ways. The CSV value is the summation of products, which products are multiplied by the occurrences number of each cyber-threat and its weight. Finally, the experimental results and system normal operation show that this method can dynamic display the macro security situation of EPIN in real time, with a high practical value.
The optimal control of two pursuers searching for a slower moving evader on a Manhattan grid road network is considered. The pursuers do not have on-board capability to detect the evader and rely instead on Unattended...
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ISBN:
(数字)9781624102240
ISBN:
(纸本)9781624102240
The optimal control of two pursuers searching for a slower moving evader on a Manhattan grid road network is considered. The pursuers do not have on-board capability to detect the evader and rely instead on Unattended Ground Sensors (UGSs) to locate the evader. We assume that all the intersections in the road network have been instrumented with UGSs. When an evader passes by an UGS location, it triggers the UGS and this time-stamped information is stored by the UGS. When a pursuer arrives at an UGS location, the UGS informs the pursuer if and when the evader passed by. When the evader and a pursuer arrive at an UGS location simultaneously, the UGS is triggered and this information is instantly relayed to the pursuer, thereby enabling "capture". We derive exact values for the minimum time guaranteed capture of the evader on the Manhattan grid and the corresponding pursuit policy.
In this work, we propose a buffer-aided successive opportunistic relaying scheme that aims to improve the average capacity of the network when inter-relay interference arises between relays that are selected for trans...
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In this work, we propose a buffer-aided successive opportunistic relaying scheme that aims to improve the average capacity of the network when inter-relay interference arises between relays that are selected for transmission and reception. In order to exploit the benefits of buffering at the relays, we propose a relay-pair selection policy that decouples the receiving relay at the previous time slot from being the transmitting relay at the next slot. Furthermore, we impose an interference cancellation threshold allowing the relay that is selected for reception, to decode and subtract the inter-relay interference. The proposed relaying scheme selects the relaying pair that maximizes the average capacity of the relay network. The performance of the proposed scheme is evaluated via simulation and comparisons with other state-of-the-art half and full-duplex relay selection schemes, in terms of outage probability, average capacity and average delay. The results reveal the need for a tradeoff between improving the outage on the cost of reduced capacity and increased delay, and vice versa. Finally, conclusions are drawn and future directions are discussed, including the need for a hybrid scheme incorporating both half and full-duplex characteristics.
Recently the power grid at home and abroad are faced with the challenge of natural disasters, to guarantee the safe and stable operation of power grid is the key. In this paper, through the grid risk identification an...
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Aiming at the incompleteness and uncertainty of information existing in power system fault diagnosis, a new fault diagnosis approach based on Bayesian network is proposed in this paper. Through the Bayesian network of...
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Power grid is a complicated and huge system, many links are involved during its lifecycle, and serious information exchange and sharing problems can be found between these links, they restrict the level of power grid&...
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Imitation is different from other similar social learning techniques such as mimicking. True imitation is goal-directed and involves abstraction. This paper presents a hierarchical concept learning scheme, which uses ...
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Imitation is different from other similar social learning techniques such as mimicking. True imitation is goal-directed and involves abstraction. This paper presents a hierarchical concept learning scheme, which uses imitation to learn new actions based on perceived observations. Presented demonstrations are composed of a spatio-temporal signal and a feature vector. In this paper a probabilistic model is provided in order to represent these hybrid demonstrations. These models have been used in an autonomous concept learning algorithm which uses effects of actions as a measure of functional similarity. Also a functional space is defined to determine concepts similarity. An algorithm for high-level concept formation in this space is provided. The proposed methods are used and evaluated in an air hockey simulation environment. Simulation results show efficiency of the proposed methods in recognition and reproduction of air hockey basic shots and their ability for hierarchical concept learning.
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