Self-organizing Control Research Articles

Control of Electric Motor Machine Tools using Self-Organizing Fuzzy Logic Controller

Control of Electric Motor Machine Tools using Self-Organizing Fuzzy Logic Controller

Biomineralization-inspired synthesis of functional organic/inorganic hybrid materials: organic molecular control of self-organization of hybrids.

Organisms produce various organic/inorganic hybrid materials, which are called biominerals. They form through the self-organization of organic molecules and inorganic elements under ambient conditions. Biominerals often have highly organized and hierarchical structures from nanometer to macroscopic length scales, resulting in their remarkable physical and chemical properties that cannot be obtained by simple accumulation of their organic and inorganic constituents. These observations motivate us to create novel functional materials exhibiting properties superior to conventional materials--both synthetic and natural. Herein, we introduce recent progress in understanding biomineralization processes at the molecular level and the development of organic/inorganic hybrid materials by these processes. We specifically outline fundamental molecular studies on silica, iron oxide, and calcium carbonate biomineralization and describe material synthesis based on these mechanisms. These approaches allow us to design a variety of advanced hybrid materials with desired morphologies, sizes, compositions, and structures through environmentally friendly synthetic routes using functions of organic molecules.

Fault-tolerant self-organizing control for command tracking of heterogeneous agents

This paper concerns the self-organizing networked control of heterogeneous agents that have to follow a common command signal and may be faulty. In addition to a basic communication, the agents request further information from other agents to avoid large control errors and to simultaneously reduce the communication effort, only if their local control error exceeds a given bound. The paper concerns possible failures of the transmission unit of the agents. To compensate the missing communication, the faulty agents have to be diagnosed and the communication among the other agents has to be reconfigured. As a consequence, the communication structure of the overall system is adjusted to the currently acting command signal and the present faulty agents. It is proven that after the reconfiguration of the communication structure asymptotic command tracking and a desired maximal control error can be guaranteed for the agents that are not faulty. The approach is demonstrated by its application to a robot formation.

Efficient data collection for self-organizing traffic signal systems based on vehicular sensor networks

The development of traffic signal systems based on vehicular sensor networks (VSNs) requires new methods to enable real-time collection and processing of the data registered by sensor-equipped vehicles. Owing to the large amounts of sensor readings, there is a necessity of selecting the data that have to be transferred to control nodes. Moreover, the control nodes need an appropriate algorithm to effectively utilise the information which is delivered from individual vehicles. This paper presents an approach, which enables efficient collection and utilisation of the detailed data from VSN for controlling traffic signals in a road network. A self-organising control strategy is used in the analysed system. The amount of transmitted data is reduced by taking into account uncertainties estimated at control nodes. Results of simulation experiments show that the proposed approach outperforms state-of-the-art methods in terms of data transfers and average vehicle delay.

Self-organising disturbance attenuation for synchronised agents with individual dynamics

This paper proposes a self-organising networked controller for disturbance attenuation in multi-agent systems. A disturbance affecting a single agent has some effect on all neighbouring agents through the communication network. To avoid large disturbance effects, the proposed self-organising controller switches off the communication whenever the effect of the disturbance on the corresponding agent exceeds a given bound. As a consequence, the structure of the networked controller is adjusted to the current disturbance. It is proved that the proposed controller bounds the effect of any disturbance on all undisturbed agents. The results are illustrated by their application to a robot formation problem.

О перспективах управления жилищно-коммунальным хозяйством на основе сетевых коммуникационных технологий

The major tasks to improve Russia’s housing and utilities infrastructure is the provision of an influx of private investment and qualified personnel, the creation of a network of regional service-quality-public-control centres, and the development and introduction of a state information system of the housing and utilities sector. The technological solutions developed for the sphere of network information technologies available and the scientific advances in the field of public conscience management afford an opportunity to create a «Special Social Network for Collaboration in the Housing and Utilities Sector» network. At the same time, Russian experts are developing and implementing a complex of measures intended to solve the informationtechnology-related problems that arise. However, little attention is paid to developing e-user competences of the housing and utilities sector’s costumers. Thus, not infrequently, the e-data collected by facility management companies are unreliable. In the course of developing an effective and financially sound management of the housing and utilities sector, special attention should be paid to creating professionally trained «small groups of continuous communication» among the population; the groups would be capable of exercising self-organized and self-modified control over the housing the utilities sector. Through the «Special Social Network for Collaboration in the Housing and Utilities Sector» network, «small groups» could share best consumer-rights-protection practices and improve their competences on a continuous basis. The network would also allow of interaction between experts, service consumers, facility management companies, and civil servants responsible for the local housing and utilities infrastructure.

Self-organizing traffic signals using secondary extension and dynamic coordination

Actuated traffic signal control logic has many advantages because of its responsiveness to traffic demands, short cycles, effective use of capacity leading to and recovering from oversaturation, and amenability to aggressive transit priority. Its main drawback has been its inability to provide good progression along arterials. However, the traditional way of providing progression along arterials, coordinated–actuated control with a common, fixed cycle length, has many drawbacks stemming from its long cycle lengths, inflexibility in recovering from priority interruptions, and ineffective use of capacity during periods of oversaturation. This research explores a new paradigm for traffic signal control, “self-organizing signals,” based on local actuated control but with some additional rules that create coordination mechanisms. The primary new rules proposed are for secondary extensions, in which the green may be held to serve an imminently arriving platoon, and dynamic coordination, in which small groups of closely spaced signals communicate with one another to cycle synchronously with the group’s critical intersection. Simulation tests in VISSIM performed on arterial corridors in Massachusetts and Arizona show overall delay reductions of up to 14% compared to an optimized coordinated–actuated scheme where there is no transit priority, and more than 30% in scenarios with temporary oversaturation. Tests also show that with self-organizing control, transit signal priority can be more effective than with coordinated–actuated control, reducing transit delay by about 60%, or 12 to 14s per intersection with little impact on traffic delay.

INFLUENCE LEARNING FOR MULTI-AGENT SYSTEM BASED ON REINFORCEMENT LEARNING

This paper describes a multi-agent influence learning approach and reinforcement learning adaptation to it. This learning technique is used for distributed, adaptive and self-organizing control in multi-agent system. This technique is quite simple and uses agent’s influences to estimate learning error between them. The best influences are rewarded via reinforcement learning which is a well-proven learning technique. It is shown that this learning rule supports positive-reward interactions between agents and does not require any additional information than standard reinforcement learning algorithm. This technique produces optimal behavior of multi-agent system with fast convergence patterns.

Simulation of Permanent Magnet Linear Synchronous Motor’s Self-Organizing Rule and Self-Regulared Parameter Fuzzy Control

In view of the permanent magnet linear synchronous motor vector control system, this paper proposes a model reference adaptive speed controller gain fuzzy self-tuning neurons. The simulation results show that when a sudden load disturbance or parameter mutation, the gain of model reference adaptive fuzzy self-tuning neuron speed control has quick response, strong robustness, good dynamic and static characteristic, etc.

Сетевые коммуникационные технологии в жилищно-коммунальном хозяйстве

An effective and financially sound management of the housing and utilities sector requires that a relevant professionally trained “small groups of continuous communication” be created among the population. These groups would be capable of exercising self-organized and self-modified control over the housing the utilities sector. Through interaction, the participants of the “4C HUS” network could generate and refine the criteria for assessing the performance of facility management companies, which would contribute to the transparency policy in the sector, as well as the sector’s attractiveness for potential investors. 
 

Active modal damping control of a smart truss structure using a self-organizing fuzzy controller

This paper presents design, implementation and experimental results of active vibration control of a truss structure using a pair of piezoelectric ceramic stack actuators. To reduce the vibrations caused by an impulse force, two active strut members are installed along a vertical of the base bay of the truss. The active strut element consists of a piezoelectric ceramic actuator stack, a force transducer and mechanical interfaces. A self-organizing fuzzy controller (SOFC) is designed to suppress vibration of the truss. The SOFC, which uses the input and output history in its fuzzy rules, is designed to maximize modal damping of a constructed truss structure. Experimental results illustrate that the active piezoceramic strut actuators and the SOFC can effectively reduce vibration of the truss.

Performance analysis of extracted rule-base multivariable type-2 self-organizing fuzzy logic controller applied to anesthesia.

We compare type-1 and type-2 self-organizing fuzzy logic controller (SOFLC) using expert initialized and pretrained extracted rule-bases applied to automatic control of anaesthesia during surgery. We perform experimental simulations using a nonfixed patient model and signal noise to account for environmental and patient drug interaction uncertainties. The simulations evaluate the performance of the SOFLCs in their ability to control anesthetic delivery rates for maintaining desired physiological set points for muscle relaxation and blood pressure during a multistage surgical procedure. The performances of the SOFLCs are evaluated by measuring the steady state errors and control stabilities which indicate the accuracy and precision of control task. Two sets of comparisons based on using expert derived and extracted rule-bases are implemented as Wilcoxon signed-rank tests. Results indicate that type-2 SOFLCs outperform type-1 SOFLC while handling the various sources of uncertainties. SOFLCs using the extracted rules are also shown to outperform those using expert derived rules in terms of improved control stability.

Self-organising disturbance attenuation in unidirectionally coupled synchronised systems

This paper proposes a self-organising networked controller for disturbance attenuation in multi-agent systems. A disturbance affecting a single agent has some effect on all neighbouring agents through the communication network. To avoid large disturbance effects, the proposed self-organising controller switches off the communication whenever the effect of the disturbance on the corresponding agent exceeds a given bound. As a consequence, the structure of the networked controller is adjusted to the current disturbance. It is proved that the proposed controller bounds the effect of arbitrary disturbances on all undisturbed agents. The results are illustrated by their application to a robot formation.

Congestion control for a fair packet delivery in WSN: from a complex system perspective.

In this work, we propose that packets travelling across a wireless sensor network (WSN) can be seen as the active agents that make up a complex system, just like a bird flock or a fish school, for instance. From this perspective, the tools and models that have been developed to study this kind of systems have been applied. This is in order to create a distributed congestion control based on a set of simple rules programmed at the nodes of the WSN. Our results show that it is possible to adapt the carried traffic to the network capacity, even under stressing conditions. Also, the network performance shows a smooth degradation when the traffic goes beyond a threshold which is settled by the proposed self-organized control. In contrast, without any control, the network collapses before this threshold. The use of the proposed solution provides an effective strategy to address some of the common problems found in WSN deployment by providing a fair packet delivery. In addition, the network congestion is mitigated using adaptive traffic mechanisms based on a satisfaction parameter assessed by each packet which has impact on the global satisfaction of the traffic carried by the WSN.

Swarm Intelligence Based Self-organizing QoS Framework for Ever-changing Future Networks

We consider a new QoS framework for a wide range of multimedia services in ever-changing networks where traffic is dynamic and network topologies frequently change. In this paper, for such networks, we propose a new self-organizing QoS framework called AntQoS, which is inspired by recent works on ant colony optimization. Compared with previous QoS frameworks, AntQoS provides two quite promising capabilities: 1) the self-organized network QoS (not pre-defined QoS), which autonomously reconfigures itself by promptly adapting to changing network environments such as sudden arrivals of highly bursty traffic, and 2) the self-organized network controls, which autonomously resolve the network congestion and intrinsically resist the multiple network failures. These two promising capabilities enable the proposed AntQoS framework to efficiently and reliably support a wide range of multimedia services with various quality demands. Especially, these capabilities are provided by making use of swarm intelligence of artificial ants without any supervised control. For this purpose, AntQoS employs one single artificial ant colony on an ever-changing network; a number of artificial ants in the employed colony explore network and measure or gather the status information about the networks. Based on the gathered information, AntQoS organizes and maintains a small number of virtual sub colonies named QoS colonies. The QoS colony is an intelligent virtual colony to be capable of searching the path which guarantees the given quality demands of flows. In addition, it is autonomously generated, maintained, and deleted for promptly adapting to the ever-changing network status. Simulation results demonstrate that AntQoS successfully supports various multimedia services with diverse delay requirements while increasing the network throughput by approximately 20% compared to the well-known IntServ frameworks. Simulation results also show that AntQoS autonomously redistributes the congested traffic and resists the unexpected network failures.

Parametric Design of Coupled Adaptive Self-Organizing Sliding-Mode Fuzzy Controller in a Valve-Controlled Folding Machine

The double-axial valve-controlled folding machine is a coupled system. This paper proposes a coupled adaptive self-organizing sliding-mode fuzzy controller (CASOSMFC) to improve its level control performance. CASOSMFC has two basic single-axial sliding-mode fuzzy controllers, self-learning fuzzy rule mechanisms, adaptive laws, coupled controllers and regulators. Then, base on variety parameters to study their parametric effects individually. Experimental results indicate that the learning rate can reduce error of steady state to improve the tracking performance. Adaptive law improves tracking error. Coupled controllers and regulators improve synchronous error.

Sliding-Mode Fuzzy Control Using in a Double-Axial Pump-Controlled Folding Machine

The double-axial pump-controlled folding machine is a coupled system and has significant structural interaction. This paper proposes a coupled adaptive self-organizing sliding-mode fuzzy controller (CASOSMFC) to improve its level control performance. CASOSMFC is associated with two basic single-axial sliding-mode fuzzy controllers, self-learning fuzzy rule mechanisms, adaptive laws, coupled controllers and regulators. Different loadings are used to simulate different working pieces and variety coupled intensity folding processes. Experimental results indicate that CASOSMFC applied in the folding machine has excellent level control performance and has strong robustness to different coupled intensity.

Technical note: Advantages of the self-organizing controller for high-pressure sterilization equipments

A study of a self-organizing controller is implemented in a way that response to controlled system follows the desired given by the model. The self-organizing controller has proven to be a valuable tool in sterilization equipment in order to verify the capacity of the response to any change in the pressure or temperature. Basically, this type of controller is based on the Self-Organizing Map (SOM) that is a neural network algorithm of unsupervised learning. The new ideas include clustering visualization, interactive training and one-dimension arrays.

A Design Approach for Controlled Self-Organization-Based Sensor Networks Focused on Control Timescale

Many researches on network control with a design principle of self-organization have been studied for large-scale networks. Since self-organized control is based on local interactions between system elements, it has high scalability, adaptability, and robustness; however, the management of the whole system is very difficult. In order to solve this problem, a controlled self-organization scheme has been proposed, which aims for desired system behavior by controlling a part of self-organized nodes. Although there are many practical proposals on the scheme, no design approach for it has ever been investigated. In this paper, we propose and evaluate a design approach for the network based on controlled self-organization, paying attention to the control timescale. Through computer simulations, we show the adaptability and stability of the proposed design approach.

ROBUSTNESS OF GUIDED SELF-ORGANIZATION AGAINST SENSORIMOTOR DISRUPTIONS

Self-organizing processes are crucial for the development of living beings. Practical applications in robots may benefit from the self-organization of behavior, e.g., to increase fault tolerance and enhance flexibility, provided that external goals can also be achieved. We present results on the guidance of self-organizing control by visual target stimuli and show a remarkable robustness to sensorimotor disruptions. In a proof of concept study an autonomous wheeled robot is learning an object finding and ball-pushing task from scratch within a few minutes in continuous domains. The robustness is demonstrated by the rapid recovery of the performance after severe changes of the sensor configuration.