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A cooperative control algorithm of TCSC is developed to adjust the branch impedance and redistribute the power flow for the stress relief. To reduce computation burdens, an approximate method is adopted to estimate the Jacobian matrix for producing the TCSC control signals. In addition, a performance index is introduced to quantify the stress level of power system. Theoretical analysis is conducted to guarantee the convergence of performance index when the cooperative control algorithm is implemented in the uncertain environment.

Based on network connectivity robustness, node evaluation index and edge evaluation index are established. Then node reconstruction evaluation index and edge reconstruction evaluation index are established, and the influence of reconstruction on the network is analyzed. Then the robustness recovery is analyzed after network reconstruction. Keywords: Complex systems , Networked control systems , Data analytics.

Abstract: In this paper, a network dynamic Meso model is put forward to address the congestion in the communication networks of integrated avionics systems. In addition, the influence of network topology on the congestion of integrated avionics system, as well as the characteristics and property of information transmission in the complex networks, are analyzed. As is verified by simulation results, the proposed method can generate reliable paths of message transmission in real time, which reduce the communication congestion. The proposed method provides a solution to the communication control problem in avionics networks.

Keywords: Data analytics. Abstract: For the purpose of monitoring the health conditions of electrical machines, a framework is proposed to establish the methods to provide an early warning to potential machine failures in data mining terminology. The difference lies in the implementation choices of techniques and structures e.

As an example, the turn-to-turn short circuit fault of induction motor is used as the known fault in studies in this work. Simulation results show the effectiveness of the proposed techniques. In the future, UAV will have an important role.

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Firstly, a confrontation process based on Monte Carlo simulation is completed, and it is used to predict the maneuver behavior of UAV. Secondly, a multidimensional cloud model is used to access the situation of the UAV after different maneuver behavior.

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The final maneuver decision is chosen based on the evaluation results. A real-time simulation between UAV of our side and the opposite side under the pairwise confrontation is implemented. The simulation result shows that maneuver action from decision making method which is based on Monte Carlo process simulation and multidimensional cloud model evaluation is validity and effective.

At the end of this paper, the rationality and feasibility of the proposed models are checked by several cases. Keywords: Object recognition , Perception systems , Vision for robots Abstract: For a multirotor micro aerial vehicle MAV flying in the outdoor environment, its downside hemisphere has richest visual information. All that information can be obtained by a single fisheye camera with larger than degrees field of view FOV. Traditionally, the unrestored fisheye image is restored to a flat image before subsequent processing, which is both resource and time consuming.

In this paper, to save resource and time, a method of fisheye object detection and localization on the unrestored fisheye image is proposed. A single-stage neural network is built for object detection. To improve the performance of detector, its submodules are designed specifically by combining the central rotational property and severe distortion of the fisheye image. To meet the real-time requirements of onboard computation, the detector is also tuned to be light-weight.

After that, the detected objects are localized with assistance of by a data fusion on the fisheye model and MAV sensory data altitude, attitude, etc. The experimental results have validated the effectiveness of the proposed methods in this paper. Keywords: Cooperative control , Multi-agent systems , Adaptive control Abstract: This paper studies the containment control problems for fully heterogeneous multi-agent systems HMASs with switching topologies, where both the leaders and the followers have different dynamics. Firstly, a distributed observer is constructed for each follower to estimate the states of all the non-identical leaders using the neighboring interaction.

Then, based on the estimated states of the multiple leaders, an output containment control protocol is proposed for HMASs using the output regulation strategy, where several predefined weights are applied for the followers to specify the desired convex combinations of the leaders. Thus, the given containment format is independent of the interaction topology.

In light of the common Lyapunov stability and output regulation theory, it is proved that the desired output containment can be realized by fully HMASs under the influences of switching topologies. Finally, a simulation example is provided to verify the effectiveness of the theoretical results. Keywords: Multi-agent systems , Consensus algorithms , multi-robot systems Abstract: In this technical note, the event-based leader-following control is investigated for a multiple non-identical Euler-Lagrange system with a directed graph. An event-triggered observer is provided to estimate the state of a dynamic leader.

To avoid continuous interaction among agents, a broadcasting communication mechanism based on models is utilized. Combining with the event-triggered observer, a distributed adaptive tracking control is presented for multiple lagrangian systems with uncertainties such that all nodes asymptotically follow a virtual leader governed by a linear model.

Finally, a simulation with 2-degree-of-freedom manipulators is presented to verify the usefulness of our proposed methods. Keywords: Multi-agent systems , Fuzzy systems , Consensus algorithms Abstract: This paper presents a fuzzy-model-based method for solving the consensus problem of a class of nonlinear multi-agent systems MASs with input saturation. Since each agent has nonlinear dynamics, the system is not asymptotically null controllable with bounded controls ANCBC. Therefore, the widely-used low-gain feedback method for designing consensus protocols of MASs with input saturation can no longer work.

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To this end, the Takagi-Sugeno T-S fuzzy model is adopted to formulate the error dynamics of those nonlinear follower agents with input saturation as well as a leader with time-varying states. Accordingly, by using the properties of convex hull, a set of invariance condition in the format of linear matrix inequality LMI is designed. Furthermore, by enlarging the shape reference set, the estimation of the attraction domain can be obtained.

Simultaneously, by viewing the control gain as an extra free parameter in the LMI optimization procedure, the leader-follower consensus algorithm is proposed, which guarantees that all followers with input saturation can track the leader, and they can asymptotically reach consensus. Finally, numerical experiments validate the effectiveness of the proposed anti-saturation consensus algorithm. Keywords: Robust control , Cooperative control , Distributed estimation Abstract: This paper addresses the robust cooperative control for lateral formation tracking a set of circles on the given sphere in an absolutely unknown spatial flowfield.

Different from the adaptive estimation method for the unknown flow speed with knowledge of the velocity direction in the literatures, a novel adaptive neural estimate is constructed based on the neighbors' information to approximate the unknown flow velocity. It is noted that such neighbor-based adaptive neural estimation develops the traditional adaptive neural approach by consensus.

Then, a robust spherical formation tracking control law is established according to flow estimation. The uniform ultimate boundedness is proven when the communication topology associated with networked first-order agents. The effectiveness of the analytical results is verified by numerical simulations. Keywords: Multi-agent systems , Mobile sensor networks , multi-robot systems Abstract: In this paper we consider a multi-UAV formation whose goal is to efficiently gather data from sensors deployed in a cluttered environment while in the same time keeping communication with ground terminals.

Consensus Problem of Delayed Linear Multi-agent Systems

We formulate these requirements and constraints as a nonlinear constrained optimization problem and recast them in a mixed-integer form with the help of a hyperplane arrangement construction. Particular attention is given to line-of-sight constraints which ensure permanent communication between UAVs and ground terminals. Reference trajectories are generated in simulation over illustrative examples. Because it is necessary to have a real overview of a specific area in the shortest time, our methodology proposes a neural network with backpropagation approach for flood detection from UAV images.

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The LBP operator labels each pixel of an image by comparing it with its neighbors, which ends with the computation of a binary number that it is converted to decimal format named LBP code. Thus, based on the LBP codes generated for an image, a histogram type feature is generated and used in both training and testing phases of the proposed neural network.

Over 50 images obtained with the aid of UAV technology were tested with the proposed neural network approach and good results in terms of accuracy for flood areas detection were obtained. Keywords: Localization, navigation and mapping , Robot sensing and data fusion Abstract: With the development of industry and commerce, the demands for indoor positioning are increasing. Indoor positioning requires higher reliability, speed and accuracy of the positioning system. However, a single positioning system has its own advantages and disadvantages, which makes it difficult to meet the positioning requirements at the same time.

Therefore, this paper proposes a fusion positioning technology that combines ultra-wideband UWB Ultra-wide Bandwidth positioning technology and inertial navigation technology using Kalman filter in the case of line of sight. Through the simulation experiment on matlab, by comparing fusion positioning technology with the single UWB positioning technology and the single inertial navigation technology, it is found that the fusion positioning technology improves the positioning accuracy, and meanwhile increases the stability of the system.

Keywords: Mechanism design and applications. Since human fingers are distributed in a crosswise narrow space, it may cause many problems in size and flexibility if we apply traditional rigid structure based on pin joints. Besides, the distance between joints in human fingers varies from person to person, which means that the exoskeleton has to be tailor-made for each patient. However, a jointless structure with no pin joint can be very soft and ignores the diversity of the distance between human fingers.

The proposed exoskeleton is developed to assist adduction and abduction motion of fingers.

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Smart Dual-Motor System with tension response is used actuate the exoskeleton. Based on kinematic models of the proposed device, assessment of the range of movement ROM can be made. The software is based on pressure-torque feedback control logic. The pressure sensors and tensiometers collect data and store it into several buffer for further processing with FIR filters.

A finite state machine FSM is integrated to support the sequential logic. In this paper, we proposed a novel knee exoskeleton driven by Series Elastic Actuator SEA which is a compliant actuator has the characteristic low output impedance, low friction, high quality force control and back-drivability.

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As for walking assistance, the force control is vital. Here, we mainly apply two control method to achieve the robust force control, one is the feedback control with enchaned distrubance observer, another is the Integral Sliding Mode Control ISM. We test both the stability and force tracking performance of the two controler. The result showed that both algorithms can achieve the satisfactory performance and the ISM algorithm obtained the slightly better result.

Keywords: Medical robots and bio-robotics , Micro robots and micro-manipulation , Biomedical instrumentation and applications Abstract: The zona pellucida ZP micro-dissection technology has played a key role in the field of artificial assisted reproduction such as ZP thinning, preimplantation genetic diagnosis PGD , etc. Currently, laser ZP micro-cutting technology using far-infrared beam has the disadvantages of high price, thermal damage, and low degree of freedom.

Piezoelectric ultrasonic micro-cutting technology has matured at the biological tissue level, but ultrasonic cutting at the single-cell level is still difficult to achieve. In this paper, based on piezoelectric ultrasonic tissue micro-cutting theory, the mechanism of ultrasonic cutting of the oocyte ZP was researched, and a cutting method for the ZP was proposed.

An ultrasonic cell surgery instrument based on a three-dimensional stereoscopic flexure-guided structure was designed. The modal analysis and the harmonic response analysis of the structure were performed using finite element software. Among them, when the operating frequency is around Finally, the theoretical method of piezoelectric ultrasonic cutting on single cell layer is presented for the first time, which has a broad prospect and significance for artificial assisted reproduction.

Keywords: Object recognition , Big data , Electric vehicles and intelligent transportation. Abstract: In the all-season indoor and outdoor background, facing the complicated environment formed by different lighting, partial blocked, pseudo-object interference, noise and other factors, the recognition and positioning of the charging port of an electric vehicle cannot be conventionally partitioned into a difficult problem.

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This paper studies the method for charging port recognition in a complex environment based on CNN, which not only ensures the accuracy and robustness of the recognition, but also provides a solution for accurately locating the charging port. The overall goal of the charging port recognition in this paper is to identify the category of the current image, and then identify the intensity of light for the image with the charging port.

We built a sample set of charging port after the denoising of median filter, which is divided into four categories: complete, none, fake, and incomplete; In order to improve the generalization ability of the model, we add the number of LeNet-5 model and use the Relu activation function; Use the above two sample sets to train the models separately, save the models and parameters, and finally actually test.

The integrity information and light intensity information are feedback to the automatic charging system, in order to accurately position the charging port subsequently, the camera position and the subtraction light strategy are adaptively adjusted to obtain a clearer image.