scholarly journals UAV Formation Shape Control via Decentralized Markov Decision Processes

Algorithms ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 91
Author(s):  
Md Ali Azam ◽  
Hans D. Mittelmann ◽  
Shankarachary Ragi
Keyword(s):  
Control Problem ◽  
Shape Control ◽  
Formation Control ◽  
Three Dimensional ◽  
Geographical Region ◽  
Dynamic Programming Method ◽  
Theoretic Approach ◽  
Control Approach ◽  
Uav Swarm ◽  
Markov Decision

In this paper, we present a decentralized unmanned aerial vehicle (UAV) swarm formation control approach based on a decision theoretic approach. Specifically, we pose the UAV swarm motion control problem as a decentralized Markov decision process (Dec-MDP). Here, the goal is to drive the UAV swarm from an initial geographical region to another geographical region where the swarm must form a three-dimensional shape (e.g., surface of a sphere). As most decision-theoretic formulations suffer from the curse of dimensionality, we adapt an existing fast approximate dynamic programming method called nominal belief-state optimization (NBO) to approximately solve the formation control problem. We perform numerical studies in MATLAB to validate the performance of the above control algorithms.

Optimal formation control with limited communication for multi-unmanned aerial vehicle in an obstacle-laden environment

2016 ◽  
Vol 231 (6) ◽  
pp. 979-997 ◽  
Author(s):  
Xiao Lin Ai ◽  
Jian Qiao Yu ◽  
Yong Bo Chen ◽  
Fang Zheng Chen ◽  
Yuan Chuan Shen
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
Formation Control ◽  
Control Laws ◽  
Control Approach ◽  
Practical Applications ◽  
Limited Communication ◽  
Aerial Vehicle ◽  
The Stability ◽  
Virtual Leader

This paper investigates the formation control problem of multiple unmanned aerial vehicles (UAVs) with limited communication in a known and realistic obstacle-laden environment. In order to deal with the limited communication constraints, the leader–follower strategy and the virtual leader strategy are integrated into an optimal control framework to formulate this formation control problem. This combination formation framework can be achieved by integrating a redefined directed graph and a proposed information vector. In more practical applications, an obstacle/collision avoidance strategy is achieved by constructing a non-quadratic cost function innovatively using a virtual flow field approach. The proposed optimal control laws, which derive from the local information rather than the global information, are proved to guarantee the stability of the close-loop system by an inverse optimal control approach. The simulation results demonstrate the effectiveness of the formation flight of multiple UAVs with limited communication in an obstacle-laden environment.

scholarly journals A leader–follower formation control approach for target hunting by multiple autonomous underwater vehicle in three-dimensional underwater environments

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141987066 ◽  
Author(s):  
Xiang Cao ◽  
Liqiang Guo
Keyword(s):  
Formation Control ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Control Approach ◽  
Challenging Tasks ◽  
System Use ◽  
Neural Network Algorithm

As one of the challenging tasks of multiple autonomous underwater vehicles systems, the realization of target hunting is the great significance. The multiple autonomous underwater vehicle target hunting is studied in this article. In some research, because the hunting members cannot reach the hunting point at the same time, the hunting time is long or the target escapes. To improve the efficiency of the target hunting, the leader–follower formation algorithm is introduced. Firstly, the task is assigned based on the distance between the autonomous underwater vehicle and the target. Then, the autonomous underwater vehicles with the same task are formed based on leader–follower mode, and the formation is kept to track the target. In the final capture phase, multiple autonomous underwater vehicle system use angle matching algorithm to round up target. The simulation results show that the proposed algorithm can effectively accomplish the target hunting task, save the hunting time, and avoid the target escape. Compared with the bioinspired neural network algorithm, the proposed algorithm shows better performance.

Constraint-following servo control for an underactuated mobile robot under hard constraints

2021 ◽  
pp. 095965182110248
Author(s):  
Duo Fu ◽  
Jin Huang ◽  
Wen-Bin Shangguan ◽  
Hui Yin
Keyword(s):  
Mobile Robot ◽  
Control Problem ◽  
Servo Control ◽  
Robot Motion ◽  
Soft Constraints ◽  
Rigorous Proof ◽  
Control Approach ◽  
Hard Constraints

This article formulates the control problem of underactuated mobile robot as servo constraint-following, and develops a novel constraint-following servo control approach for underactuated mobile robot under both servo soft and hard constraints. Servo soft constraints are expressed as equalities, which may be holonomic or non-holonomic. Servo hard constraints are expressed as inequalities. It is required that the underactuated mobile robot motion eventually converges to servo soft constraints, and satisfies servo hard constraints at all times. Diffeomorphism is employed to incorporate hard constraints into soft constraints, yielding new soft constraints to relax hard constraints. By this, we design a constraint-following servo control based on the new servo soft constraints, which drives the system to strictly follow the original servo soft and hard constraints. The effectiveness of the proposed approach is proved by rigorous proof and simulations.

scholarly journals Adaptive-Neural-Network-Based Shape Control for a Swarm of Robots

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Xuejing Lan ◽  
Zhenghao Wu ◽  
Wenbiao Xu ◽  
Guiyun Liu
Keyword(s):  
Neural Network ◽  
Nonlinear Dynamics ◽  
Shape Control ◽  
Formation Control ◽  
Adaptive Neural Network ◽  
Multirobot System ◽  
Control Scheme ◽  
Narrow Space ◽  
The Stability ◽  
Unknown Nonlinear Dynamics

This paper considers the region-based formation control for a swarm of robots with unknown nonlinear dynamics and disturbances. An adaptive neural network is designed to approximate the unknown nonlinear dynamics, and the desired formation shape is achieved by designing appropriate potential functions. Moreover, the collision avoidance, velocity consensus, and region tracking are all considered in the controller. The stability of the multirobot system has been demonstrated based on the Lyapunov theorem. Finally, three numerical simulations show the effectiveness of the proposed formation control scheme to deal with the narrow space, loss of robots, and formation merging problems.

STERILIZATION OF CANNED VISCOUS FOODS: AN OPTIMAL CONTROL APPROACH

2004 ◽  
Vol 14 (03) ◽  
pp. 355-374 ◽  
Author(s):  
L. J. ALVAREZ-VAZQUEZ ◽  
M. MARTA ◽  
A. MARTINEZ
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
Nutrient Retention ◽  
Reaction Diffusion ◽  
The State ◽  
Reaction Diffusion Equations ◽  
Boussinesq System ◽  
Temperature Dependent Viscosity ◽  
Control Approach ◽  
Dependent Viscosity

In this paper, we study an optimal control problem with pointwise constraints on state and control, related to sterilization processes involving heat transfer by natural convection. We introduce the mathematical model for the state system, which couples the Boussinesq system for temperature-dependent viscosity and the convection-reaction-diffusion equations, and we set the whole problem as a control problem, assuring the micro-organism reduction, the nutrient retention and the energy saving. The existence and the regularity of the state are studied. Finally, we obtain existence results for the optimal solutions and a first-order optimality condition for their characterization.

scholarly journals Three-dimensional data-tracking simulations of sprinting using a direct collocation optimal control approach

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10975
Author(s):  
Nicos Haralabidis ◽  
Gil Serrancolí ◽  
Steffi Colyer ◽  
Ian Bezodis ◽  
Aki Salo ◽  
...  
Keyword(s):  
Experimental Data ◽  
Reaction Force ◽  
Three Dimensional ◽  
Contact Model ◽  
Model Parameters ◽  
Ground Contact ◽  
Control Approach ◽  
Average Percentage ◽  
Data Tracking ◽  
The Individual

Biomechanical simulation and modelling approaches have the possibility to make a meaningful impact within applied sports settings, such as sprinting. However, for this to be realised, such approaches must first undergo a thorough quantitative evaluation against experimental data. We developed a musculoskeletal modelling and simulation framework for sprinting, with the objective to evaluate its ability to reproduce experimental kinematics and kinetics data for different sprinting phases. This was achieved by performing a series of data-tracking calibration (individual and simultaneous) and validation simulations, that also featured the generation of dynamically consistent simulated outputs and the determination of foot-ground contact model parameters. The simulated values from the calibration simulations were found to be in close agreement with the corresponding experimental data, particularly for the kinematics (average root mean squared differences (RMSDs) less than 1.0° and 0.2 cm for the rotational and translational kinematics, respectively) and ground reaction force (highest average percentage RMSD of 8.1%). Minimal differences in tracking performance were observed when concurrently determining the foot-ground contact model parameters from each of the individual or simultaneous calibration simulations. The validation simulation yielded results that were comparable (RMSDs less than 1.0° and 0.3 cm for the rotational and translational kinematics, respectively) to those obtained from the calibration simulations. This study demonstrated the suitability of the proposed framework for performing future predictive simulations of sprinting, and gives confidence in its use to assess the cause-effect relationships of technique modification in relation to performance. Furthermore, this is the first study to provide dynamically consistent three-dimensional muscle-driven simulations of sprinting across different phases.

Energy efficiency path planning for a quadrotor aerial vehicle

2021 ◽  
pp. 014233122110585
Author(s):  
Fouad Yacef ◽  
Nassim Rizoug ◽  
Laid Degaa ◽  
Omar Bouhali ◽  
Mustapha Hamerlain
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Weather Conditions ◽  
Optimization Method ◽  
Control Approach ◽  
Mission Success ◽  
Aerial Vehicle ◽  
Vehicle Trajectory ◽  
Point To Point

Unmanned aerial vehicles are used today in many real-world applications. In all these applications, the vehicle endurance (flight time) is an important constraint that affects mission success. This study investigates the limitations of embedded energy for a quadrotor aerial vehicle. We consider a quadrotor simple tasked to travel from an initial hover configuration to a final hover configuration. In order to have a precise approximation of the consumed energy, we propose a power consumption model with battery dynamic, motor dynamic, and rotor efficiency function. We then introduce an optimization algorithm to minimize the energy consumption during quadrotor aerial vehicle mission. The proposed algorithm is based on an optimal control problem formulated for the quadrotor model and solved using nonlinear programming. In the optimal control problem, we seek to find control inputs (rotor velocity) and vehicle trajectory between initial and final configurations that minimize the consumed energy during a point-to-point mission. We extensively test in simulation experiments the proposed algorithm under normal and windy weather conditions. We compare the proposed optimization method with a nonlinear adaptive control approach to highlight the saved amount of energy.

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