An Improved Cooperative Control Method for Hybrid Unmanned Aerial-Ground System in Multitasks

The cooperative control in complex multitasks using unmanned aerial vehicle and unmanned ground vehicle (UAV/UGV) is an important and challenging issue in the multirobot cooperative field. The main goal of the task studied in this paper is to minimize the time and energy consumed by the system to complete the assigned tasks. In this paper, a complex multitask problem using the hybrid UAV/UGV system is studied, which is divided into three stages, namely, the stage of finding the optimal locations of the relay stations for the UGV; the stage of solving the path planning problem for the UGV; and the stage of the task assignment for multi-UAVs. Furthermore, an improved integrated method is proposed to deal with the cooperative control problems in these three stages. Firstly, an adaptive clustering method is proposed to determine the locations of the UGV relay stations, and then an improved cuckoo search algorithm is used to find the shortest path for the UGV. Finally, a grouping method is presented to solve the multitask allocation problem of UAVs, based on an improved dynamic programming algorithm. In addition, some simulations are carried out and the results show that the proposed method has better performance when it comes to the time and energy consumption and can effectively guide the hybrid UAV/UGV system to carry out the complex multitasks.

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Penerapan Algoritma Dynamic Programing pada Pergerakan Lawan dalam Permainan Police and Thief

JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING ◽

10.31289/jite.v2i2.2169 ◽

2019 ◽

Vol 2 (2) ◽

pp. 114

Author(s):

Insidini Fawwaz ◽

Agus Winarta

Keyword(s):

Artificial Intelligence ◽

Dynamic Programming ◽

Search Algorithm ◽

Dynamic Programming Algorithm ◽

Minimum Cost ◽

Programming Algorithm ◽

Shortest Route ◽

Basic Meaning ◽

Dynamic Programing ◽

Approximate Distance

Games have the basic meaning of games, games in this case refer to the notion of intellectual agility. In its application, a Game certainly requires an AI (Artificial Intelligence), and the AI used in the construction of this police and thief game is the dynamic programming algorithm. This algorithm is a search algorithm to find the shortest route with the minimum cost, algorithm dynamic programming searches for the shortest route by adding the actual distance to the approximate distance so that it makes it optimum and complete. Police and thief is a game about a character who will try to run from police. The genre of this game is arcade, built with microsoft visual studio 2008, the AI used is the Dynamic Programming algorithm which is used to search the path to attack players. The results of this test are police in this game managed to find the closest path determined by the Dynamic Programming algorithm to attack players

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Dynamic Programming Approach for Online Freeway Flow Propagation Adjustment

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1802-29 ◽

2002 ◽

Vol 1802 (1) ◽

pp. 263-270 ◽

Cited By ~ 4

Author(s):

Xuesong Zhou ◽

Hani S. Mahmassani

Keyword(s):

Dynamic Programming ◽

Control Method ◽

Dynamic Programming Algorithm ◽

Superior Performance ◽

Programming Algorithm ◽

Programming Approach ◽

Base Case ◽

Solution Quality ◽

Flow Propagation ◽

The Impact

An optimization framework for online flow propagation adjustment in a freeway context was proposed. Instead of performing local adjustment for individual links separately, the proposed framework considers the interconnectivity of links in a traffic network. In particular, dynamic behavior in the mesoscopic simulation is approximated by the finite-difference method at a macroscopic level. The proposed model seeks to minimize the deviation between simulated density and anticipated density. By taking advantage of the serial structure of a freeway, an efficient dynamic programming algorithm has been developed and tested. The experiment results compared with analytic results as the base case showed the superior performance of dynamic programming methods over the classical proportion control method. The effect of varying update intervals was also examined. The simulation results suggest that a greedy method considering the impact of inconsistency propagation achieves the best trade-off in terms of computation effort and solution quality.

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A Hierarchical Cooperative Mission Planning Mechanism for Multiple Unmanned Aerial Vehicles

Electronics ◽

10.3390/electronics8040443 ◽

2019 ◽

Vol 8 (4) ◽

pp. 443 ◽

Cited By ~ 7

Author(s):

Zhe Zhao ◽

Jian Yang ◽

Yifeng Niu ◽

Yu Zhang ◽

Lincheng Shen

Keyword(s):

Unmanned Aerial Vehicles ◽

Search Algorithm ◽

Pseudospectral Method ◽

Task Assignment ◽

Mission Planning ◽

Planning Problem ◽

B Spline ◽

Aerial Vehicles ◽

Third Stage ◽

Multiple Unmanned Aerial Vehicles

In this paper, the cooperative multi-task online mission planning for multiple Unmanned Aerial Vehicles (UAVs) is studied. Firstly, the dynamics of unmanned aerial vehicles and the mission planning problem are studied. Secondly, a hierarchical mechanism is proposed to deal with the complex multi-UAV multi-task mission planning problem. In the first stage, the flight paths of UAVs are generated by the Dubins curve and B-spline mixed method, which are defined as “CBC)” curves, where “C” stands for circular arc and “B” stands for B-spline segment. In the second stage, the task assignment problem is solved as multi-base multi-traveling salesman problem, in which the “CBC” flight paths are used to estimate the trajectory costs. In the third stage, the flight trajectories of UAVs are generated by using Gaussian pseudospectral method (GPM). Thirdly, to improve the computational efficiency, the continuous and differential initial trajectories are generated based on the “CBC” flight paths. Finally, numerical simulations are presented to demonstrate the proposed approach, the designed initial solution search algorithm is compared with existing methods. These results indicate that the proposed hierarchical mission planning method can produce satisfactory mission planning results efficiently.

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Control and HIL Simulation of Series Hybrid Electric Vehicles Based on Dynamic Programming Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.602-605.1149 ◽

2014 ◽

Vol 602-605 ◽

pp. 1149-1152

Author(s):

Liang Zhang ◽

Bin Jiao ◽

Xiu Hong Guo

Keyword(s):

Dynamic Programming ◽

Electric Vehicles ◽

Power Flow ◽

Hybrid Electric Vehicles ◽

Control Method ◽

Dynamic Programming Algorithm ◽

Programming Algorithm ◽

Exhaust Gas Emission ◽

Hybrid Electric ◽

Hil Simulation

Hybrid electric vehicles has the potential to save energy consumption and relieve exhaust gas emission while the power flow control techniques are very important for improving a hybrid electric vehicle’s performance. In this paper, the system simulation and control method of series hybrid electric vehicles were proposed. The control method was based on enhancing the energy transfer efficiency based on dynamic programming algorithm. The hardware in the loop (HIL) simulation was constructed containing a real-time driver and controller in the simulation platform, which can be used to evaluate the proposed strategy.

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On computing secure domination of trees

Discrete Mathematics Algorithms and Applications ◽

10.1142/s1793830921500555 ◽

2020 ◽

pp. 2150055

Author(s):

Abolfazl Poureidi

Keyword(s):

Linear Time ◽

Search Algorithm ◽

Dominating Set ◽

Domination Number ◽

Dynamic Programming Algorithm ◽

Programming Algorithm ◽

Time And Space ◽

Minimum Cardinality ◽

Secure Domination ◽

Appl Math

Let [Formula: see text] be a graph. A subset [Formula: see text] is a dominating set of [Formula: see text] if for each [Formula: see text] there is a vertex [Formula: see text] adjacent to [Formula: see text]. A dominating set [Formula: see text] of [Formula: see text] is a secure dominating set of [Formula: see text] if for each [Formula: see text] there is a vertex [Formula: see text] adjacent to [Formula: see text] such that [Formula: see text] is also a dominating set of [Formula: see text]. The minimum cardinality of a secure dominating set of [Formula: see text] is called the secure domination number of [Formula: see text]. Burger et al. [A linear algorithm for secure domination in trees, Discrete Appl. Math. 171 (2014) 15–27] proposed a nontrivial algorithm for computing a minimum secure dominating set of a given tree in linear time and space. In this paper, we give a dynamic programming algorithm to compute the secure domination number of a given tree [Formula: see text] in [Formula: see text] time and space and then using a backtracking search algorithm we can find a minimum secure dominating set of [Formula: see text] in [Formula: see text] time and space that its implementation is much simpler than the implementation of the algorithm proposed by Burger et al.

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Data-Driven Distributionally Robust Stochastic Control of Energy Storage for Wind Power Ramp Management Using the Wasserstein Metric

Energies ◽

10.3390/en12234577 ◽

2019 ◽

Vol 12 (23) ◽

pp. 4577

Author(s):

Insoon Yang

Keyword(s):

Energy Storage ◽

Wind Power ◽

Control Method ◽

Empirical Distribution ◽

Dynamic Programming Algorithm ◽

Piecewise Linear Approximation ◽

Programming Algorithm ◽

Worst Case ◽

Robust Solution ◽

Distributionally Robust

The integration of wind energy into the power grid is challenging because of its variability, which causes high ramp events that may threaten the reliability and efficiency of power systems. In this paper, we propose a novel distributionally robust solution to wind power ramp management using energy storage. The proposed storage operation strategy minimizes the expected ramp penalty under the worst-case wind power ramp distribution in the Wasserstein ambiguity set, a statistical ball centered at an empirical distribution obtained from historical data. Thus, the resulting distributionally robust control policy presents a robust ramp management performance even when the future wind power ramp distribution deviates from the empirical distribution, unlike the standard stochastic optimal control method. For a tractable numerical solution, a duality-based dynamic programming algorithm is designed with a piecewise linear approximation of the optimal value function. The performance and utility of the proposed method are demonstrated and analyzed through case studies using the wind power data in the Bonneville Power Administration area for the year 2018.

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A Heuristic Mission Planning Algorithm for Heterogeneous Tasks with Heterogeneous UAVs

Unmanned Systems ◽

10.1142/s2301385015500132 ◽

2015 ◽

Vol 03 (03) ◽

pp. 205-219 ◽

Cited By ~ 9

Author(s):

Jingjing Wang ◽

Y. F. Zhang ◽

L. Geng ◽

J. Y. H. Fuh ◽

S. H. Teo

Keyword(s):

Task Scheduling ◽

Search Algorithm ◽

Time Windows ◽

Task Assignment ◽

Flight Path ◽

Mission Planning ◽

Planning Problem ◽

Planning Algorithm ◽

Aerial Vehicle ◽

Good Plan

This paper investigates the unmanned aerial vehicle (UAV)-mission planning problem (MPP) in which one needs to quickly find a good plan/schedule to carry out various tasks of different time windows at various locations using a fleet of fixed-winged heterogeneous UAVs. Such a realistic and complex UAV-MPP is decomposed into two sub-problems: flight path planning and task scheduling. A graph construction and search algorithm is developed for the flight path generation. For the task scheduling problem, a new hybrid algorithm based on heuristic has been proposed: (1) small-to-medium sized problem — heuristics for task assignment and all permutations for sequencing, and (2) large sized problem — heuristics for both task assignment and sequencing. The proposed algorithms have been implemented and tested. Numerical experimental results show that the proposed algorithm is very efficient and can effectively solve relatively big problems.

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Multiple-Choice Hardware/Software Partitioning for Tree Task-Graph on MPSoC

The Computer Journal ◽

10.1093/comjnl/bxy140 ◽

2019 ◽

Vol 63 (5) ◽

pp. 688-700 ◽

Cited By ~ 1

Author(s):

Wenjun Shi ◽

Jigang Wu ◽

Guiyuan Jiang ◽

Siew-kei Lam

Keyword(s):

Dynamic Programming ◽

Tabu Search ◽

Embedded System ◽

Exact Solutions ◽

Heuristic Algorithm ◽

Search Algorithm ◽

Dynamic Programming Algorithm ◽

Programming Algorithm ◽

Task Graph ◽

Tabu Search Algorithm

Abstract Hardware/software (HW/SW) partitioning, that decides which components of an application are implemented in hardware and which ones in software, is a crucial step in embedded system design. On modern heterogeneous embedded system platform, each component of application can typically have multiple feasible configurations/implementations, trading off quality aspects (e.g. energy consumption, completion time) with usage for various types of resources. This provides new opportunities for further improving the overall system performance, but few works explore the potential opportunity by incorporating the multiple choices of hardware implementation in the partitioning process. This paper proposes three algorithms for multiple-choice HW/SW partitioning of tree-shape task graph on multiple processors system on chip (MPSoC) with the objective of minimizing execution time, while meeting area constraint. Firstly, an efficient heuristic algorithm is proposed to rapidly generate an approximate solution. The obtained solution produced by the first algorithm is then further refined by a customized Tabu search algorithm. We also propose a dynamic programming algorithm to calculate the exact solutions for relatively smaller scale instances. Simulation results show that the proposed heuristic algorithm is able to quickly generate good approximate solutions, and the solutions become very close to the exact solutions after refined by the proposed Tabu search algorithm, in comparison to the exact solutions produced by the dynamic programming algorithm.

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