UAV Formation Control Based on the Improved APF

2014 ◽  
Vol 933 ◽  
pp. 358-364 ◽  
Author(s):  
Jie Yang ◽  
Ke Yi Zhang ◽  
Xin Ming Wang ◽  
Cheng Long Hao ◽  
Tao Wei
Keyword(s):  
Formation Control ◽  
Local Minimum ◽  
Route Planning ◽  
Minimum Point ◽  
Relative Distance ◽  
Random Fluctuation ◽  
Target Point ◽  
Turning Angle ◽  
Fluctuation Method ◽  
Global Minimum Point

Malfunction such as target non-reach ability, local minimum pole and oscillation happens when traditional APF is applied to route planning. This paper proposes an improved APF model, considering the relative distance between the UAV and the target, the relative distance between the lead craft and the wing craft and the safety. We ensure the point of target to be the global minimum point in the entire potential fieldtarget non-reach ability caused by the threat and target point being too close are solved by adopting the modified repulsive potential function; planning failure in which UAVs falling into local minimum point is solved by adopting random fluctuation method; considering the oscillation of traditional potential field, the obstacle link method is proposed. The results of the simulation indicate the single UAV simulation route after obstacles overall planning, track route of UAV formation and formation route with obstacles with turning angle constraints. Requirements of Formation control and formation obstacle avoidance have been well satisfied.

A singularly perturbed elliptic problem involving supercritical Sobolev exponent

1998 ◽  
Vol 128 (4) ◽  
pp. 809-819 ◽  
Author(s):  
Yaotian Shen ◽  
Shusen Yan
Keyword(s):  
Elliptic Problem ◽  
Local Minimum ◽  
Global Minimum ◽  
Singularly Perturbed ◽  
Minimum Point ◽  
Regular Part ◽  
Local Minimum Point ◽  
Minimisation Problem ◽  
Sobolev Exponent ◽  
Global Minimum Point

This paper deals with −Δu + εuq−1 = u2*−1, , where q > 2*, ε > 0. We first show that the minimiser of the associated minimisation problem blows up at the global minimum point of H(x, x), where H(y, x) is the regular part of the Green's function. We then prove that for each strictly local minimum point x0 of H(x, x), this problem has a solution concentrating at x0 as ε→0.

On the number of interior peaks of solutions to a non-autonomous singularly perturbed Neumann problem

2009 ◽  
Vol 139 (2) ◽  
pp. 427-448 ◽  
Author(s):  
Chunyi Zhao
Keyword(s):  
Positive Integer ◽  
Neumann Problem ◽  
Smooth Function ◽  
Local Minimum ◽  
Singularly Perturbed ◽  
Minimum Point ◽  
Local Minimum Point ◽  
Image Position

We study the following non-autonomous singularly perturbed Neumann problem:where the index p is subcritical and a(x) is a positive smooth function in . We show that, given ε small enough, there exists a K(ε) such that, for any positive integer K ≤ K(ε), there always exists a solution with K interior peaks concentrating at a strict sth-order local minimum point of a.

Regulating a Formation of a Large Number of Vehicles

2005 ◽  
Author(s):  
Akira Okamoto ◽  
Dean B. Edwards
Keyword(s):  
Control Problem ◽  
Coordinate System ◽  
Formation Control ◽  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Degree Of Freedom ◽  
Relative Distance ◽  
Control Algorithms ◽  
Distance Measurements ◽  
Six Degree Of Freedom

Various control algorithms have been developed for fleets of autonomous vehicles. Many of the successful control algorithms in practice are behavior-based control or nonlinear control algorithms, which makes analyzing their stability difficult. At the same time, many system theoretic approaches for controlling a fleet of vehicles have also been developed. These approaches usually use very simple vehicle models such as particles or point-mass systems and have only one coordinate system which allows stability to be proven. Since most of the practical vehicle models are six-degree-of-freedom systems defined relative to a body-fixed coordinate system, it is difficult to apply these algorithms in practice. In this paper, we consider a formation regulation problem as opposed to a formation control problem. In a formation control problem, convergence of a formation from random positions and orientations is considered, and it may need a scheme to integrate multiple moving coordinates. On the contrary, in a formation regulation problem, it is not necessary since small perturbations from the nominal condition, in which the vehicles are in formation, are considered. A common origin is also not necessary if the relative distance to neighbors or a leader is used for regulation. Under these circumstances, the system theoretic control algorithms are applicable to a formation regulation problem where the vehicle models have six degrees of freedom. We will use a realistic six-degree-of-freedom model and investigate stability of a fleet using results from decentralized control theory. We will show that the leader-follower control algorithm does not have any unstable fixed modes if the followers are able to measure distance to the leader. We also show that the leader-follower control algorithm has fixed modes at the origin, indicating that the formation is marginally stable, when the relative distance measurements are not available. Multi-vehicle simulations are performed using a hybrid leader-follower control algorithm where each vehicle is given a desired trajectory to follow and adjusts its velocity to maintain a prescribed distance to the leader. Each vehicle is modeled as a three-degree-of-freedom system to investigate the vehicle’s motion in a horizontal plane. The examples show efficacy of the analysis.

Health indicator construction for roller bearing based on an unsupervised deep belief network with a novel sigmoid zero local minimum point model

2020 ◽  
pp. 147592172096395
Author(s):  
Fan Xu ◽  
Xin Shu ◽  
Xin Li ◽  
Ruoli Tang
Keyword(s):  
Local Minimum ◽  
Roller Bearing ◽  
Main Idea ◽  
Deep Belief Network ◽  
Remaining Useful Life ◽  
Minimum Point ◽  
Sigmoid Function ◽  
Health Indicator ◽  
Belief Network ◽  
Local Minimum Point

Extracting bearing degradation curves with good smoothness and monotonicity as a health indicator lays a solid foundation for predicting the bearing’s remaining useful life. Traditional bearing health indicator construction methods generally have the following problems: (1) they require manual experience, such as manual labeling of data is burdensome when the amount of collected data is large, for feature extraction, selection, and fusion with other indicators and models because the methods rely on substantial expert experience and signal-processing technology; (2) deep belief networks in deep learning require engineering experts with rich experience to label the data, and because the degradation state of a bearing is constantly changing, it is difficult to rely on manual experience to distinguish and label it accurately; (3) owing to the noise in the data collected during the study, the extracted health indicator curve shows obvious oscillation and poor smoothness. In response to the above problems, this study proposes a model based on an unsupervised deep belief network and a new sigmoid zero local minimum point to eliminate health indicator curve oscillation and improve monotonicity. The main idea is that a deep belief network without a label output layer is used to extract the preliminary health indicator curve directly from the original signal, whereas the sigmoid zero local minimum point uses the average value based on a sigmoid function to reduce the weight of the current health indicator value to eliminate concussion, and then it uses the zero and local minimum points to further improve the monotonicity of the extracted health indicator without parameters. Finally, the superiority of the model proposed in this study (deep belief network–sigmoid zero local minimum point) is verified through a comparison of multiple bearing datasets and other models.

scholarly journals Study on the Formation Control Methods for Multi-Agent Based on Geometric Characteristics

2013 ◽  
Vol 765-767 ◽  
pp. 1928-1931
Author(s):  
Li Li He ◽  
Xiao Chun Lou
Keyword(s):  
Formation Control ◽  
Three Dimensional ◽  
Target Point ◽  
Control Methods ◽  
Agent Based ◽  
Geometric Characteristics ◽  
Specific Direction ◽  
Multi Agent ◽  
Formation Method ◽  
Dimensional Simulation

Multi-agent formation control is the process in which the teams formed by multiple agents move to specific target or specific direction. The formation method of the linear formation and circular formation are given in this paper, based on the geometric characteristics of the formation formed by multi-agent. The process in which 5 agents arrived at the designated target point and formed a linear formation is achieved through simulation; and 4 agents formed a circular formation and cooperated to carry heavy weights. The result of the three-dimensional simulation shows the feasibility of the method to form multi-agent formations in different environments and different tasks.

The Null Space Based Cooperative Formation Control for UAVs Swarm

2013 ◽  
Vol 341-342 ◽  
pp. 824-829
Author(s):  
Shi You Dong ◽  
Xiao Ping Zhu ◽  
Guo Qing Long
Keyword(s):  
Control Strategy ◽  
Formation Control ◽  
Local Minimum ◽  
Null Space ◽  
Potential Functions ◽  
Good Effect ◽  
Artificial Potential Field ◽  
Minimum Problem ◽  
Control Approach ◽  
Local Minimum Problem

In this paper, the formation problem of UAVs swarm is studied based on a combination of the potential functions. On the basis of mathematical models of the traditional artificial potential field,a new formation potential function is proposed. The potential functions is merged using null space control strategy which is capable of dealing with conflicts among elementary potential functions and avoid local minimum problem. The results achieved by computer simulations suggest that the control approach can produces good effect.

Heuristic Approaches in Clustering Problems

2018 ◽  
pp. 107-124 ◽  
Author(s):  
Onur Doğan
Keyword(s):  
Local Minimum ◽  
Heuristic Algorithms ◽  
Minimum Point ◽  
Optimization Approach ◽  
Similar Data ◽  
Heuristic Approaches ◽  
Clustering Problem ◽  
Local Minimum Point ◽  
Np Hard Problem ◽  
Short Time

Clustering is an approach used in data mining to classify objects in parallel with similarities or separate according to dissimilarities. The aim of clustering is to decrease the amount of data by grouping similar data items together. There are different methods to cluster. One of the most popular techniques is K-means algorithm and widely used in literature to solve clustering problem is discussed. Although it is a simple and fast algorithm, there are two main drawbacks. One of them is that, in minimizing problems, solution may trap into local minimum point since objective function is not convex. Since the clustering is an NP-hard problem and to avoid converging to a local minimum point, several heuristic algorithms applied to clustering analysis. The heuristic approaches are a good way to reach solution in a short time. Five approaches are mentioned briefly in the chapter and given some directions for details. For an example, particle swarm optimization approach was used for clustering problem. In example, iris dataset including 3 clusters and 150 data was used.

scholarly journals Formation control of unmanned underwater vehicles using local sensing means in absence of follower position information

2021 ◽  
Vol 18 (1) ◽  
pp. 172988142098674
Author(s):  
Zheping Yan ◽  
Da Xu ◽  
Tao Chen ◽  
Jiajia Zhou
Keyword(s):  
Formation Control ◽  
Control Structure ◽  
Controller Design ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Lyapunov Methods ◽  
Relative Distance ◽  
Position Information ◽  
State Information ◽  
Unmanned Underwater Vehicles

Formation control is one of the essential problems in multi-unmanned underwater vehicle (UUV) coordination. In this article, a practically oriented UUV formation control structure and method are proposed for the problem of large communication in leader–follower approach. To solve the problem of large communication in multi-UUVs, local sensing means of acoustic positioning is used to provide the real relative distance and angle information for the follower UUV. So, only a small amount of state information of the leader UUV needs to be sent to the follower UUV by acoustic communication. Then, the formation control structure in absence of follower position information is proposed. In this control structure, only the relative distance and angle, as well as velocity and heading of the leader UUV, are used for the formation controller design of the follower UUV. Backstepping and Lyapunov methods are used to design the formation controller without position information of the follower UUV. Two formation configurations of rectangle and triangle with five UUVs are simulated to verify the effectiveness of the method proposed. The simulation results show that the follower UUV can successfully constitute and maintain the desired formation by controlling each real relative distance and angle.

scholarly journals Leaderless Maneuver Guidance and Event-Triggered Formation Control for Distributed Multi-Space-Robot Systems

2021 ◽  
Author(s):  
Xuan Wang ◽  
Xing Chu ◽  
Yunhe Meng ◽  
Guoguang wen ◽  
Qian Jiang
Keyword(s):  
Formation Control ◽  
Linear Quadratic Regulator ◽  
Space Robot ◽  
Target Point ◽  
Linear Quadratic ◽  
Guidance Control ◽  
Control Framework ◽  
Robot Systems ◽  
Event Times ◽  
Event Triggered

Abstract In this paper, the distributed displacement-based formation and leaderless maneuver guidance control problems of multi-space-robot systems are investigated by introducing event-triggered control update mechanisms. A distributed formation and leaderless maneuver guidance control framework is first constructed, which includes two parallel controllers, namely, an improved linear quadratic regulator and a distributed consensus-based formation controller. By applying this control framework, the desired formation configuration of multi-space-robot systems can be achieved and the center of leaderless formation can converge to the target point globally. Second, a pull-based event triggering mechanism is introduced to the distributed formation controller, which makes the control update independent of the events of neighboring robots, avoids unnecessary control updates, and saves the extremely limited energy of space robots. Furthermore, the potential Zeno behaviors have been excluded by proving a positive lower bound for the inter-event times. Finally, numerical simulation verifies the effectiveness of the theoretical results.

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