A novel fractional uplink power control framework for self-organizing networks

Internet of things and network densification bring significant challenges to uplink management.Only depending on optimization algorithm enhancements is not enough for uplink transmission.To control intercell interference,Fractional Uplink Power Control(FUPC)should be optimized from network-wide perspective,which has to find a better traffic distribution model.Conventionally,traffic distribution is geographic-based,and ineffective due to tricky locating efforts.This paper proposes a novel uplink power management framework for Self-Organizing Networks(SON),which firstly builds up pathloss-based traffic distribution model and then makes the decision of FUPC based on the model.PathLoss-based Traffic Distribution(PLTD)aggregates traffic based on the propagation condition of traffic that is defined as the pathloss between the position generating the traffic and surrounding cells.Simulations show that the improvement in optimization efficiency of FUPC with PLTD can be up to 40%compared to conventional GeoGraphic-based Traffic Distribution(GGTD).

Controllable fabrication of self-organized nano-multilayers in copper–carbon films

In order to clarify the influence of methane concentration and deposition time on self-organized nano-multilayers,three serial copper-carbon films have been prepared at various methane concentrations with different deposition times using a facile magnetron sputtering deposition system. The ratios of methane concentration(CH4/Ar+CH4) used in the experiments are 20%, 40%, and 60%, and the deposition times are 5 minutes, 20 minutes, and 40 minutes, respectively.Despite the difference in the growth conditions, self-organizing multilayered copper-carbon films are prepared at different deposition times by changing methane concentration. The film composition and microstructure are investigated by x-ray photoelectron spectroscopy(XPS), x-ray diffraction(XRD), field emission scanning electron microscopy(FESEM), and high-resolution transmission electron microscopy(HRTEM). By comparing the composition and microstructure of three serial films, the optimal growth conditions and compositions for self-organizing nano-multilayers in copper-carbon film are acquired. The results demonstrate that the self-organized nano-multilayered structure prefers to form in two conditions during the deposition process. One is that the methane should be curbed at low concentration for long deposition time,and the other condition is that the methane should be controlled at high concentration for short deposition time. In particular, nano-multilayered structure is self-organized in the copper-carbon film with copper concentration of 10-25 at.%.Furthermore, an interesting microstructure transition phenomenon is observed in copper-carbon films, that is, the nanomultilayered structure is gradually replaced by a nano-composite structure with deposition time and finally covered by amorphous carbon.

Self-organization of Reconfigurable Protocol Stack for Networked Control Systems

In networked control systems （NCS）,the control performance depends on not only the control algorithm but also the communication protocol stack.The performance degradation introduced by the heterogeneous and dynamic communication environment has intensified the need for the reconfigurable protocol stack.In this paper,a novel architecture for the reconfigurable protocol stack is proposed,which is a unified specification of the protocol components and service interfaces supporting both static and dynamic reconfiguration for existing industrial communication standards.Within the architecture,a triple-level self-organization structure is designed to manage the dynamic reconfiguration procedure based on information exchanges inside and outside the protocol stack.Especially,the protocol stack can be self-adaptive to various environment and system requirements through the reconfiguration of working mode,routing and scheduling table.Finally,the study on the protocol of dynamic address management is conducted for the system of controller area network （CAN）.The results show the efficiency of our self-organizing architecture for the implementation of a reconfigurable protocol stack.

Self-Organized Algorithm in LTE Networks： A Utility Function Based Optimal Power Control Scheme

In this paper, transmission power control problem for uplink LTE network is investigated and a new autonomic uplink power control scheme was proposed based on utility function, which is a self- organized algorithm. The whole approach is based on the economic concept named utility function. Then a self-organized algorithm is distributed in each mobile users to control the transmission power and to maximize the transmission utility. The proposed scheme is solved through the Lagrange multiplier technique. It is proved that the utility function based algorithm optimal power level can be model. is applicable and the achieved based on our

The self-organizing worm algorithm

A new multi-modal optimization algorithm called the self-organizing worm algorithm （SOWA） is presented for optimization of multi-modal functions. The main idea of this algorithm can be described as follows： disperse some worms equably in the domain; the worms exchange the information each other and creep toward the nearest high point; at last they will stop on the nearest high point. All peaks of multi-modal function can be found rapidly through studying and chasing among the worms. In contrast with the classical multi-modal optimization algorithms, SOWA is provided with a simple calculation, strong convergence, high precision, and does not need any prior knowledge. Several simulation experiments for SOWA are performed, and the complexity of SOWA is analyzed amply. The results show that SOWA is very effective in optimization of multi-modal functions.

Robust PID Controller Design on Quantum Fuzzy Inference: Imperfect KB Quantum Self-Organization Effect-Quantum Supremacy Effect

The new method of robust self-organized PID controller design based on a quantum fuzzy inference algorithm is proposed.The structure and mechanism of a quantum PID controller(QPID)based on a quantum decision-making logic by using two K-gains of classical PID(with constant K-gains)controllers are investigated.Computational intelligence toolkit as a soft computing technology in learning situations is applied.Benchmark’s simulation results of intelligent robust control are demonstrated and analyzed.Quantum supremacy demonstrated.

Controlling the dynamic behavior of decentralized cluster through centralized approaches

How to control the dynamic behavior of large-scale artificial active matter is a critical concern in experimental research on soft matter, particularly regarding the emergence of collective behaviors and the formation of group patterns. Centralized systems excel in precise control over individual behavior within a group, ensuring high accuracy and controllability in task execution. Nevertheless, their sensitivity to group size may limit their adaptability to diverse tasks. In contrast, decentralized systems empower individuals with autonomous decision-making, enhancing adaptability and system robustness. Yet, this flexibility comes at the cost of reduced accuracy and efficiency in task execution. In this work, we present a unique method for regulating the centralized dynamic behavior of self-organizing clusters based on environmental interactions. Within this environment-coupled robot system, each robot possesses similar dynamic characteristics, and their internal programs are entirely identical. However, their behaviors can be guided by the centralized control of the environment, facilitating the accomplishment of diverse cluster tasks. This approach aims to balance the accuracy and flexibility of centralized control with the robustness and task adaptability of decentralized control. The proactive regulation of dynamic behavioral characteristics in active matter groups, demonstrated in this work through environmental interactions, holds the potential to introduce a novel technological approach and provide experimental references for studying the dynamic behavior control of large-scale artificial active matter systems.

TYPICAL ARCHITECTURES FOR FUZZY CONTROL

Some typical structural schemes of Fuzzy control have been surveyed. Besides general structure of fuzzy logic controller (FLC), the structural schemes include PID fuzzy controller, self-organizing fuzzy controller, selftuning fuzzy controller, self-learning fuzzy controller, and expect fuzzy controller, etc. This survey focuses on the control principle, and provides a basis for potential applications. Most of the structures have been used in various control fields, one of application areas is in the metallurgy industry, e. g., the temperature control of the electric furnace, the control of the aluminum smelting process, etc. According to the application requirements, one can choose a structural scheme for special use.

Thickness and Shape Synthetical Adjustment for DC Mill Based on Dynamic Nerve-Fuzzy Control

Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model,a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy control was put forward,and a self-organizing fuzzy control model was established.The structure of the network can be optimized dynamically.In the course of studying,the network can automatically adjust its structure based on the specific questions and make its structure the optimal.The input and output of the network are fuzzy sets,and the trained network can complete the composite relation,the fuzzy inference.For decreasing the off-line training time of BP network,the fuzzy sets are encoded.The simulation results indicate that the self-organizing fuzzy control based on dynamic neural network is better than traditional decoupling PID control.

Position Control of Single Pneumatic Muscle Actuator

The PID, fuzzy, self-organized fuzzy and self-organized fuzzy-PID controllers are adopted in the position control of single pneumatic muscle actuator. Experiments show that the self-organized fuzzy-PID is obviously effective for the position control of single pneumatic muscle actuator, which can realize precision within 0.3 mm and withstand 18?N variable load plus about 36?N fixed load. It is relatively precise and robust.

A novel strategy of smart manipulation by micro-scale oscillatory networks of the reactionary zones for enhanced extreme thrust control of the next-generation solid propulsion systems

The main aim of this research is to get a better knowledge and understanding of the micro-scale oscillatory networks behavior in the solid propellants reactionary zones. Fundamental understanding of the micro-and nano-scale combustion mechanisms is essential to the development and further improvement of the next-generation technologies for extreme control of the solid propellant thrust. Both experiments and theory confirm that the micro-and nano-scale oscillatory networks excitation in the solid propellants reactionary zones is a rather universal phenomenon. In accordance with our concept,the micro-and nano-scale structures form both the fractal and self-organized wave patterns in the solid propellants reactionary zones. Control by the shape, the sizes and spacial orientation of the wave patterns allows manipulate by the energy exchange and release in the reactionary zones. A novel strategy for enhanced extreme thrust control in solid propulsion systems are based on manipulation by selforganization of the micro-and nano-scale oscillatory networks and self-organized patterns formation in the reactionary zones with use of the system of acoustic waves and electro-magnetic fields, generated by special kind of ring-shaped electric discharges along with resonance laser radiation. Application of special kind of the ring-shaped electric discharges demands the minimum expenses of energy and opens prospects for almost inertia-free control by combustion processes. Nano-sized additives will enhance self-organizing and self-synchronization of the micro-and nano-scale oscillatory networks on the nanometer scale. Suggested novel strategy opens the door for completely new ways for enhanced extreme thrust control of the solid propulsion systems.

Self-Structured Organizing Single-Input CMAC Control for De-icing Robot Manipulator

This paper presents a self-structured organizing single-input control system based on differentiable cerebellar model articulation controller (CMAC) for an n-link robot manipulator to achieve the high-precision position tracking. In the proposed scheme, the single-input CMAC controller is solely used to control the plant, so the input space dimension of CMAC can be simplified and no conventional controller is needed. The structure of single-input CMAC will also be self-organized;that is, the layers of single-input CMAC will grow or prune systematically and their receptive functions can be automatically adjusted. The online tuning laws of single-input CMAC parameters are derived in gradient-descent learning method and the discrete-type Lyapunov function is applied to determine the learning rates of the proposed control system so that the stability of the system can be guaranteed. The simulation results of three-link De-icing robot manipulator are provided to verify the effectiveness of the proposed control methodology.

基于模糊模型的工业过程稳态优化控制方法

本文提出了一种解决复杂非线性工业过程的稳态优化控制方法 ,对过程建立模糊模型 ,用自相关函数检验法验证模型的正确性 ,用改进的遗传算法实现稳态优化计算 ,并以一炼油厂催化裂化实际生产过程的稳态数据进行试验 ,结果说明该方法的正确性。

Efficient Exciton Transfer from In0.35Ga0.65As Template into InAs Quantum Dots Grown on GaAs （311）B Substrates

Atomic force microscopy （AFM） and power-dependent micro-photoluminescence （μ-PL） spectroscopy are used to study the structure and exciton energy states in InAs quantum dots （QDs） grown on an In0.35Ga0.65As template on GaAs （311）B. The In0.35Ga0.65As template, consisting of a two-dimensionally modulated layer of closely packed connected cells, has a remarkable effect on the optical properties of the IhAs QDs. By comparing the emission spectra of the samples without and with InAs QDs and the work carried out by Gong et al. [J. Cryst. Growth 251 （2003） 150; Appl. Phys. Lett. 81 （2002） 3254] we conclude that the existence of the In0.35Ga0.65As template enhances the photo-absorption and therefore the exeiton emission from the QDs due to efficient exciton transfer from the template into the QDs. Furthermore, the PL emission from the QDs dearly reveals four discrete energy levels, S, P, D, and F with increasing excitation power.

Effect of SEN Parameters on 3D Flow Field in Mould of Beam Blank Continuous Caster

Due to the complexity of thickness and shape synthetical adjustment system and the difficulties to build a mathematical model, a thickness and shape synthetical adjustment scheme on DC mill based on dynamic nerve-fuzzy control was put forward, and a self-organizing fuzzy control model was established. The structure of the network can be optimized dynamically. In the course of studying, the network can automatically adjust its structure based on the specific questions and make its structure the optimal. The input and output of the network are fuzzy sets, and the trained network can complete the composite relation, the fuzzy inference. For decreasing the off-line training time of BP network, the fuzzy sets are encoded. The simulation results indicate that the self-organizing fuzzy control based on dynamic neural network is better than traditional decoupling PID control.

Time-varying Algorithm for Swarm Robotics

Ever since the concept of swarm intelligence was brought out, a variety of control algorithms for swarm robotics has been put forward, and many of these algorithms are stable enough and efficient. Most of the researches only take an invariable controller which functions through the whole stage into consideration, the situation in which controller changes over time is rarely taken into account. However, there are limitations for invariable controller dominated algorithms in practical situation,which makes them unable to meet changing environment. On the contrary, variable controller is more flexible and can be able to adapt to complex environment. Considering such advantages,a time-varying algorithm for swarm robotics is presented in this paper. The algorithm takes time as one of the independent variables so that the controller is no longer fixed through the time,but can be changed over time, which brings more choices for the swarm robot system. In this paper, some relevant simulations are designed to test the algorithm. Different control strategies are applied on the same flock during the time, and a more complex,flexible and practical control effect is acquired successfully.

Distributed intelligent self-organized mission planning of multi-UAV for dynamic targets cooperative search-attack

This article studies the cooperative search-attack mission problem with dynamic targets and threats, and presents a Distributed Intelligent Self-Organized Mission Planning(DISOMP)algorithm for multiple Unmanned Aerial Vehicles(multi-UAV). The DISOMP algorithm can be divided into four modules: a search module designed based on the distributed Ant Colony Optimization(ACO) algorithm, an attack module designed based on the Parallel Approach(PA)scheme, a threat avoidance module designed based on the Dubins Curve(DC) and a communication module designed for information exchange among the multi-UAV system and the dynamic environment. A series of simulations of multi-UAV searching and attacking the moving targets are carried out, in which the search-attack mission completeness, execution efficiency and system suitability of the DISOMP algorithm are analyzed. The simulation results exhibit that the DISOMP algorithm based on online distributed down-top strategy is characterized by good flexibility, scalability and adaptability, in the dynamic targets searching and attacking problem.

Design and mathematical analysis of activating transcriptional amplifiers that enable modular temporal control in synthetic juxtacrine circuits

The ability to control mammalian cells such that they self-organize or enact therapeutic effects as desired has incredible implications.Not only would it further our understanding of native processes such as development and the immune response,but it would also have powerful applications in medical fields such as regenerative medicine and immunotherapy.This control is typically obtained by synthetic circuits that use synthetic receptors,but control remains incomplete.The synthetic juxtacrine receptors(SJRs)are widely used as they are fully modular and enable spatial control,but they have limited gene expression amplification and temporal control.As these are integral facets to cell control,I therefore designed transcription factor based amplifiers that amplify gene expression and enable unidirectional temporal control by prolonging duration of target gene expression.Using a validated in silico framework for SJR signaling,I combined these amplifiers with SJRs and show that these SJR amplifier circuits can direct spatiotemporal patterning and improve the quality of self-organization.I then show that these circuits can improve chimeric antigen receptor(CAR)T cell tumor killing against various heterogenous antigen expression tumors.These amplifiers are flexible tools that improve control over SJR based circuits with both basic and therapeutic applications.

基于系统自组织控制的高校网络教育管理模式探索——东财网院管理模式案例研究

高校网络教育体系具有无边界性和系统开放性的重要特征,其由多个虚拟组织构成。网络教育办学的规模化和教学分离使得其有别于传统教育。基于系统自组织控制(SSOC)的高校网络教育管理模式是由他组织向自组织发展的一种全新探索,其突破以内部组织制度为基础的传统管理方式,从运作方面突破组织边界的障碍,将整个组织变成一个灵活的系统,有效地解决了高校网络教育办学涉及的多主体间的协同问题。SSOC的管理思想可以通过管理系统平台来实现,基于SSOC的协同管理系统是网络教育自组织系统的信息中心,围绕这一系统形成了高效的信息传递机制,通过与业务流程的高度耦合,可以有效地保障网络教学与服务的质量。东北财经大学网络教育学院通过"协同管理平台"和"工时统计平台"的研发与运行、闭环的信息反馈与协调机制及双层的质量保障体系,有效地保障了网络教育的质量。

一种大工业过程稳态优化控制方法

催化裂化装置是一个高度非线性、时变和长时延、强耦合、分布参数和不确定性的复杂系统。为解决催化裂化过程的优化控制问题 ,采用多层前馈神经网络进行辨识、建模 ,用周期图检验法对模型检验 ,用改进的 Frank- Wolfe算法进行稳态优化计算 ,并以大港炼油厂实际生产过程的稳态数据进行试验和验证 ,说明神经网络适合于解决非线性复杂生产过程的辨识。