Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System

The integration of wind turbines(WTs)in variable speed drive systems belongs to the main factors causing lowstability in electrical networks.Therefore,in order to avoid this issue,WTs hybridization with a storage system is a mandatory.This paper investigates WT system operating at variable speed.The system contains of a permanent magnet synchronous generator(PMSG)supported by a battery storage system(BSS).To enhance the quality of active and reactive power injected into the network,direct power control(DPC)scheme utilizing space-vector modulation(SVM)technique based on proportional-integral(PI)control is proposed.Meanwhile,to improve the rendition of this method(DPC-SVM-PI),the rooted tree optimization technique(RTO)algorithm-based controller parameter identification is used to achieve PI optimal gains.To compare the performance ofRTO-based controllers,they were implemented and tested along with some other popular controllers under different working conditions.The obtained results have shown the supremacy of the suggested PIRTO algorithm compared to competing controllers regarding total harmonic distortion(THD),overshoot percentage,settling time,rise time,average active power value,overall efficiency,and active power steadystate error.

A Table Based Algorithm for MinimumDirected Spanning Trees

As far as the weighted digraph is considered, an optimal directed spanning tree algorithm called table based algorithm (TBA) is proposed in the paper based on the table instead of the weighted digraph. The optimality is proved, and a numerical example is demonstrated.

Table Operation Method for Optimal Spanning Tree Problem

As far as the weight digraph is considered, based on the table instead of the weightdigraph, an optimal spanning tree method called the Table Operations Method (TOM) is proposed.And the optimality is proved and a numerical example is demonstrated.

The Minimum Centroid Branch Spanning Tree Problem

For a spanning tree T of graph G,the centroid of T is a vertex v for which the largest component of T-v has as few vertices as possible.The number of vertices of this component is called the centroid branch weight of T.The minimum centroid branch spanning tree problem is to find a spanning tree T of G such that the centroid branch weight is minimized.In application to design of communication networks,the loads of all branches leading from the switch center should be as balanced as possible.In this paper,we prove that the problem is strongly NP-hard even for bipartite graphs.Moreover,the problem is shown to be polynomially solvable for split graphs,and exact formulae for special graph familis,say Kn_(1),n_(2),...,n_(k)and P_(m)×P_(n),are presented.

Sensor scheduling for ground maneuvering target tracking in presence of detection blind zone

Continuous and stable tracking of the ground maneuvering target is a challenging problem due to the complex terrain and high clutter. A collaborative tracking method of the multisensor network is presented for the ground maneuvering target in the presence of the detection blind zone(DBZ). First, the sensor scheduling process is modeled within the partially observable Markov decision process(POMDP) framework. To evaluate the target tracking accuracy of the sensor, the Fisher information is applied to constructing the reward function. The key of the proposed scheduling method is forecasting and early decisionmaking. Thus, an approximate method based on unscented sampling is presented to estimate the target state and the multi-step scheduling reward over the prediction time horizon. Moreover, the problem is converted into a nonlinear optimization problem, and a fast search algorithm is given to solve the sensor scheduling scheme quickly. Simulation results demonstrate the proposed nonmyopic scheduling method(Non-MSM) has a better target tracking accuracy compared with traditional methods.

OPTIMAL ALGORITHM FOR NO TOOl-RETRACTIONS CONTOUR-PARALLEL OFFSET TOOL-PATH LINKING

A contour-parallel offset （CPO） tool-path linking algorithm is derived without toolretractions and with the largest practicability. The concept of ＂tool-path loop tree＂ （TPL-tree） providing the information on the parent/child relationships among the tool-path loops （TPLs） is presented. The direction, tool-path loop, leaf/branch, layer number, and the corresponding points of the TPL-tree are introduced. By defining TPL as a vector, and by traveling throughout the tree, a CPO tool-path without tool-retractions can be derived.

Distributed privacy protection strategy for MEC enhanced wireless body area networks

With the rapid development and widespread application of Wireless Body Area Networks(WBANs),the traditional centralized system architecture cannot handle the massive data generated by the edge devices.Meanwhile,in order to ensure the security of physiological privacy data and the identity privacy of patients,this paper presents a privacy protection strategy for Mobile Edge Computing(MEC)enhanced WBANs,which leverages the blockchain-based decentralized MEC paradigm to support efficient transmission of privacy information with low latency,high reliability within a high-demand data security scenario.On this basis,the Merkle tree optimization model is designed to authenticate nodes and to verify the source of physiological data.Furthermore,a hybrid signature algorithm is devised to guarantee the node anonymity with unforgeability,data integrity and reduced delay.The security performance analysis and simulation results show that our proposed strategy not only reduces the delay,but also secures the privacy and transmission of sensitive WBANs data.

Parameter Identification of Magic Formula Tire Model Based on Fibonacci Tree Optimization Algorithm

The magic formula(MF)tire model is a semi-empirical tire model that can precisely simulate tire behavior.The heuristic optimization algorithm is typically used for parameter identification of the MF tire model.To avoid the defect of the traditional heuristic optimization algorithm that can easily fall into the local optimum,a parameter identification method based on the Fibonacci tree optimization(FTO)algorithm is proposed,which is used to identify the parameters of the MF tire model.The proposed method establishes the basic structure of the Fibonacci tree alternately through global and local searches and completes optimization accordingly.The global search rule in the original FTO was modified to improve its efficiency.The results of independent repeated experiments on two typical multimodal function optimizations and the parameter identification results showed that FTO was not sensitive to the initial values.In addition,it had a better global optimization performance than genetic algorithm(GA)and particle swarm optimization(PSO).The root mean square error values optimized with FTO were 5.09%,10.22%,and 3.98%less than the GA,and 6.04%,4.47%,and 16.42%less than the PSO in pure lateral and longitudinal forces,and pure aligning torque parameter identification.The parameter identification method based on FTO was found to be effective.

0N THE COMPLEXITY OF AN OPTIMAL ROUTING TREE PROBLEM

A routing tree for a set of tasks is a decision tree which assigns the tasks to their destinationsaccording to the features of the tasks. A weighted routing tree is one with costs attached to each linkof the tree. Links of the same feature have the same cost. It is proved that the problem of finding ?routing tree of the minimum cost for a given set of tasks of two features is NP-complete.

The Minimum Stretch Spanning Tree Problem for Typical Graphs

With applications in communication networks,the minimum stretch spanning tree problem is to find a spanning tree T of a graph G such that the maximum distance in T between two adjacent vertices is minimized.The problem has been proved NP-hard and fixed-parameter polynomial algorithms have been obtained for some special families of graphs.In this paper,we concentrate on the optimality characterizations for typical classes of graphs.We determine the exact formulae for the complete k-partite graphs,split graphs,generalized convex graphs,and several planar grids,including rectangular grids,triangular grids,and triangulated-rectangular grids.

Exponentially many maximum genus embeddings and genus embeddings for complete graphs

There are many results on the maximum genus, among which most are written for the existence of values of such embeddings, and few attention has been paid to the estimation of such embeddings and their applications. In this paper we study the number of maximum genus embeddings for a graph and find an exponential lower bound for such numbers. Our results show that in general case, a simple connected graph has exponentially many distinct maximum genus embeddings. In particular, a connected cubic graph G of order n always has at least $ (\sqrt 2 )^{m + n + \tfrac{\alpha } {2}} $ distinct maximum genus embeddings, where α and m denote, respectively, the number of inner vertices and odd components of an optimal tree T. What surprise us most is that such two extremal embeddings (i.e., the maximum genus embeddings and the genus embeddings) are sometimes closely related with each other. In fact, as applications, we show that for a sufficient large natural number n, there are at least $ C2^{\tfrac{n} {4}} $ many genus embeddings for complete graph K n with n ≡ 4, 7, 10 (mod12), where C is a constance depending on the value of n of residue 12. These results improve the bounds obtained by Korzhik and Voss and the methods used here are much simpler and straight.