A novel bipartite consensus tracking scheme for unknown nonlinear multi-agent systems: Theoretical analysis and applications

This article proposes a novel distributed data-driven bipartite consensus tracking scheme for bipartite consensus tracking problems of multi-agent systems with bounded disturbances and coopetition networks. The proposed scheme only uses the input/output data of each agent without requiring the agents’ dynamics. We obtain the equivalent dynamic linearization data model for a controlled plant using the dynamic linearization technique based on the pseudo partial derivative. Considering the cooperative and competitive interactions among agents, the proposed method ensures that agents with adversarial relationships implement bipartite consensus tracking tasks even if only a subset of agents can access the information from the virtual leader. Moreover, the strict proof process of convergence properties reveals that the tracking error coverages to a small range around the origin. We also establish a set of software and hardware platform to demonstrate the effectiveness of the proposed distributed data-driven bipartite consensus tracking method.

Distributed Swarm Control Algorithm of Multiple Unmanned Surface Vehicles Based on Grouping Method

This paper addresses the distributed swarm control problem of multiple unmanned surface vehicles (USVs) in Euclidean space with virtual leader. Firstly, to investigate the topology of the neighborhood relations between vehicles, a new time-variant topology structure is proposed. Secondly, to research the dynamic properties of the group for the case where the number of virtual leader is different, a grouping method based on cosine similarity is proposed. Thirdly, to ensure the high effeciency of information transmission and the reduction of costs, a distributed swarm control algorithm is proposed, which is mainly composed of three parts: gradient descent term, velocity consensus term and navigational feedback term. To analyze the stability of system, the concept of translation framework is introduced. Based on the properties of the Hamiltonian and LaSalle invariance principle, the stability of multiple USVs swarm motion is proved. Finally, simulation results illustrate the effectiveness of the proposed methods.

Studies on Multi-Constraints Cooperative Guidance Method Based on Distributed MPC for Multi-Missiles

Cooperative terminal guidance with impact angle constraint is a key technology to achieve a saturation attack and improve combat effectiveness. The present study envisaged cooperative terminal guidance with impact angle constraint for multiple missiles. In this pursuit, initially, the three-dimensional cooperative terminal guidance law with multiple constraints was studied. The impact time cooperative strategy of virtual leader missile and follower missiles was designed by introducing virtual leader missiles. Subsequently, based on the distributed model prediction control combined with the particle swarm optimization algorithm, a cooperative terminal guidance algorithm was designed for multiple missiles with impact angle constraint that met the guidance accuracy. Finally, the effectiveness of the algorithm was verified using simulation experiments.

KOMUNIKASI KELOMPOK VIRTUAL LEADER PEMASARAN ASURANSI

Globalisasi adalah suatu proses menjadikan sesuatu (benda atau perilaku) sebagai ciri dari setiap individu di dunia ini tanpa dibatasi oleh wilayah. Globalisasi dapat juga diartikan beberapa karakteristik yang berbeda ( baca : budaya ) dapat berinteraksi secara masif. Perkembangan dunia teknologi komunikasi yang demikian pesatnya telah membawa manfaat luar biasa bagi kemajuan peradaban umat manusia. Kegiatan komunikasi yang sebelumnya menuntut peralatan yang begitu rumit, kini relatif sudah digantikan oleh perangkat mesin-mesin otomatis. Kegiatan komunikasi dalam artian pertukaran atau interaksi di antara berbagai budaya yang berbeda tidak terelakan dalam era globalisasi sekarang. Pasca Pandemi COVID -19, perubahan tatanan kehidupan sosial terjadi secara umum. Bentuk komunikasi tatap muka secara langsung semakin dibatasi dalam dunia bisnis, dunia pendidikan, dunia pergaulan sehari – hari dan lainnya. Salah satu bentuk komunikasi dalam dunia bisnis adalah Whatsapp Grup. Dengan adanya pandemi, komunikasi lewat Whatsapp Grup lebih intens dilakukan. Dalam konteks komunikasi, salah satunya adalah konteks komunikasi kelompok. Bentuk komunikasi kelompok mulai beralih dari komunikasi tatap muka menjadi komunikasi virtual melalui media sosial ataupun platform lainnya. Mau tidak mau segala aktifitas manusia semakin cepat dan serentak. Tulisan ini mencoba mendeskripsikan aktivitas komunikasi kelompok virtual yang terjadi pada grup whatsapp Victory West Leaders di era pandemi COVID – 19.Faktor kunci dalam aktivitas kelompok virtual ini adalah adanya persamaan tujuan kelompok,faktor leadership dari pemimpin dan kesadaran invidividu anggota kelompok dan factor kebersamaan dalam waktu yang lama.Situasi pandemi memaksa aktivitas grup bisnis lebih diperketat melalui aktivitas komunikasi virtual Whatsapp Grup. Hal ini bertujuan untuk menjaga kestabilan produktivitas team. Kata Kunci : Komunikasi Kelompok, Komunikasi Virtual, Grup Whatsapp, COVID -19, Leader Pemasaran Asuransi

Formation Control of Swarming Vessels Using a Virtual Matrix Approach and ISOT Guidance Algorithm

The formation control for the effective operation of multiple vessels is discussed. First, a virtual matrix approach is proposed to improve the formation robustness and transform performance during swarm operations, which is created based on the virtual leader vessel location, and agents composing the formation follow cells in the matrix to maintain formation. This approach is affected by the virtual leader vessel location. The virtual leader vessel location is defined by two cases: matrix center and geometric center; furthermore, robustness and efficiency comparison simulations are performed. The simulation results show that in most formations, the geometric center is better in terms of efficiency and robustness. Second, the isosceles triangle guidance algorithm is proposed to improve the “go-back behavior” of certain agents during excessive maneuvering. Through a waypoint-following simulation, the algorithm is confirmed to be superior to the line-of-sight guidance algorithm. The swarm simulation on the virtual map verifies the performance of the proposed formation n control and guidance algorithm.

Building a Connected Communication Network for UAV Clusters Using DE-MADDPG

Clusters of unmanned aerial vehicles (UAVs) are often used to perform complex tasks. In such clusters, the reliability of the communication network connecting the UAVs is an essential factor in their collective efficiency. Due to the complex wireless environment, however, communication malfunctions within the cluster are likely during the flight of UAVs. In such cases, it is important to control the cluster and rebuild the connected network. The asymmetry of the cluster topology also increases the complexity of the control mechanisms. The traditional control methods based on cluster consistency often rely on the motion information of the neighboring UAVs. The motion information, however, may become unavailable because of the interrupted communications. UAV control algorithms based on deep reinforcement learning have achieved outstanding results in many fields. Here, we propose a cluster control method based on the Decomposed Multi-Agent Deep Deterministic Policy Gradient (DE-MADDPG) to rebuild a communication network for UAV clusters. The DE-MADDPG improves the framework of the traditional multi-agent deep deterministic policy gradient (MADDPG) algorithm by decomposing the reward function. We further introduce the reward reshaping function to facilitate the convergence of the algorithm in sparse reward environments. To address the instability of the state-space in the reinforcement learning framework, we also propose the notion of the virtual leader–follower model. Extensive simulations show that the success rate of the DE-MADDPG is higher than that of the MADDPG algorithm, confirming the effectiveness of the proposed method.

Finite-Time Coordinated Path Following Control of Leader-Following Multi-Agent Systems

The applications of the continuous feedback method to achieve both path following and a formation moving along desired orbits at a finite time is presented. It is assumed that the topology among the virtual leader and the followers is directed. An additional condition of so called barrier function to yield all the agents moving within a limited area is designed. A novel continuous finite-time path following control law is first designed based on the barrier function and backstepping. Then a novel continuous finite-time formation algorithm is designed by regarding the path following errors as disturbances. The settling time properties of the resulting system are studied in detail. Simulations are presented to validate the proposed strategies.