Search results

In this paper, two omni‐directional mobile vehicles are designed and controlled implementing distributed mechatronics controllers. Omni‐directionality is the ability of mobile vehicle to move instantaneously in any direction. It is achieved by implementing Mecanum wheels in one vehicle and conventional wheels in another vehicle. The control requirements for omni‐directionality using the two above‐mentioned methods are that each wheel must be independently driven, and that all the four wheels must be synchronized in order to achieve the desired motion of each vehicle.

Distributed mechatronics controllers implementing Controller Area Network (CAN) modules are used to satisfy the control requirements of the vehicles. In distributed control architectures, failures in other parts of the control system can be compensated by other parts of the system. Three‐layered control architecture is implemented for; time‐critical tasks, event‐based tasks, and task planning. Global variables and broadcast communication is used on CAN bus. Messages are accepted in individual distributed controller modules by subscription.

Increase in the number of distributed modules increases the number of CAN bus messages required to achieve smooth working of the vehicles. This requires development of higher layer to manage the messages on the CAN bus.

The limitation of the research is that analysis of the distributed controllers that were developed is complex, and that there are no universally accepted tool for conducting the analysis. The other limitation is that teh mathematical models of the mobile robot that have been developed need to be verified.

In the design of omni‐directional vehicles, reliability of the vehicle can be improved by modular design of mechanical system and electronic system of the wheel modules and the sensor modules.

The paper tries to show the advantages of distributed controller for omni‐directional vehicles. To the author's knowledge, that is a new concept.

This paper aims to investigate the distributed coordinated fuzzy tracking problems for multiple mechanical systems with nonlinear model uncertainties under a directed communication topology.

The dynamic leader case is considered while only a subset of the follower mechanical systems can obtain the leader information. First, this paper approximates the system uncertainties with finite fuzzy rules and proposes a distributed adaptive tracking control scheme. Then, this paper makes a detailed classification of the system uncertainties and uses different fuzzy systems to approximate different kinds of uncertainties. Further, an improved distributed tracking strategy is proposed. Closed-loop systems are investigated using graph theory and Lyapunov theory. Numerical simulations are performed to verify the effectiveness of the proposed methods.

Based on fuzzy control and adaptive control theories, the desired distributed coordinated tracking control strategies for multiple uncertain mechanical systems are developed.

Compared with most existing literature, the proposed distributed tracking algorithms use fuzzy control and adaptive control techniques to cope with system nonlinear uncertainties of multiple mechanical systems. Moreover, the improved control strategy not only reduces fuzzy rules but also has higher control accuracy.

The chapter describes the basics of developed high-level spatial grasp technology (SGT) and its spatial grasp language (SGL) allowing us to create and manage very large distributed systems in physical, virtual and executive domains in a highly parallel manner and without any centralized resources. Main features of SGT with its self-evolving and self-spreading spatial intelligence, recursive nature of SGL and organization of its networked interpreter will be briefed. Numerous interpreter copies can be installed worldwide and integrated with other systems or operate autonomously and collectively in critical situations. Relation of SGT, with capability of holistic solutions in distributed systems, to the gestalt psychology and theory, showing unique qualities of human mind and brain to directly grasp the whole of different phenomena, will be explained too, with SGT serving as an attempt to implement the notion of gestalt for distributed applications.

This paper aims to analyze the key factors influencing the synchronization performance of distributed motion control system and to improve the synchronization performance for peripherals control of this system.

This paper deals with the software synchronization problems of distributed motion control system based on real-time Ethernet. First, combined with communication and control tasks, the key factors affecting synchronization performance of system are analyzed. Then, aiming at key factors and considering the synchronization of system bus, protocol conversion and task scheduling, a software synchronization method based on CANopen protocol and real-time Ethernet is proposed. Finally, the feasibility of this method is verified by establishing distributed motion control system and testing the synchronization performance of terminal control signals of slaves.

Based on this method, the results show that the synchronization accuracy for peripherals control of all slaves could be about 100 ns.

This research provides high-precision synchronization method, which could lay a foundation for the application of distributed motion control system in the field of assembly automation, such as multi-axis assembly robots control.

In distributed motion control system, many factors affect the synchronization performance. At present, there is no synchronization method that could comprehensively consider these factors. This paper not only analyzes the key factors influencing the synchronization performance of system but also proposes a synchronization method. Therefore, the method proposed in this paper has certain theoretical value and engineering significance.

This monograph defines distributed intelligence and discusses the relationship of distributed intelligence to data base, justifications for using the technique, and the approach to successful implementation of the technique. The approach is then illustrated by reference to a case study of experience in Birds Eye Foods. The planning process by which computing strategy for the company was decided is described, and the planning conclusions reached to date are given. The current state of development in the company is outlined and the very real savings so far achieved are specified. Finally, the main conclusions of the monograph are brought together. In essence these conclusions are that major savings are achievable using distributed intelligence, and that the implementation of a company data processing plan can be made quicker and simpler by its use. However, careful central control must be maintained so as to avoid fragmentation of machine, language skills, and application taking place.

This paper aims to develop an adaptable control architecture for electrohydraulic humanoid robots (HYDROïD) that emulate the functionality of the human nervous system. The developed control architecture overcomes the limitations of classical centralized and decentralized systems by distributing intelligence across controllers.

The proposed solution is a distributed real-time control architecture with robot operating system (ROS). The joint controllers have the intelligence to make decisions, dominate their actuators and publish their state. The real-time capabilities are ensured in the master controller by using a Preempt-RT kernel beside open robot control software middleware to operate the real-time tasks and in the customized joint controllers by free real-time operating systems firmware. Systems can be either centralized, where all components are connected to a central unit or decentralized, where distributed units act as interfaces between the I/Os and the master controller when the master controller is without the ability to make decisions.

The proposed architecture establishes a versatile and adaptive control framework. It features a centralized hardware topology with a master PC and distributed joint controllers, while the software architecture adapts based on the task. It operates in a distributed manner for precise, force-independent motions and in a decentralized manner for tasks requiring compliance and force control. This design enables the examination of the sensorimotor loop at both low-level joint controllers and the high-level master controller.

It developed a control architecture emulating the functionality of the human nervous system. The experimental validations were performed on the HYDROïD. The results demonstrated 50% advancements in the update rate compared to other humanoids and 30% in the latency of the master processor and the control tasks.

The chapter offers complete details of the latest SGL version particularly suitable for dealing with large security systems and emerging crisis situations. It describes main types of constants representing information, physical matter or both and five very different and specific types of variables operating in fully distributed spaces and even being mobile themselves when serving spreading algorithms. Also given full repertoire of the language operations, called rules, which can be arbitrarily nested and carry different navigation, creation, processing, assignment, control, verification, context, exchange, transference, echoing, timing and other loads. The rules equally operate with local and remote values, process both, matter and distributed networked knowledge, and can express active graph-based patterns navigating, matching, conquering and changing distributed environments. Elementary programming examples in SGL are also provided.

During recent years, in the field of real‐time instrumentation and process control, there has been a trend away from centralized control system. Distributed control by using fieldbus technology is only the first step to application of intelligence in the field devices. Compares centralized systems with the distributed systems, differentiates the conventional LANs from the fieldbus technology and reviews the related technology and the current status of the international fieldbus standards. Describes some of the standard fieldbuses. Highlights the advantages of using fieldbuses in the real‐time process control and discusses what are the points to be considered before selecting a fieldbus. Highlights fieldbus‐based design development methodology involved in order to build a real‐time industrial distributed control system (RIDCS). Presents a case study with the LonWorks Technology; a fieldbus category system.

Proper function of landing gear plays a crucial role in the safe operation of an airplane. Traditional landing gear control system utilizes centralized control technology. The relatively heavy wire harness and low reliability accompanied with this technology make it logical to transfer from traditional control to real‐time distributed control. This paper aims to look into a new landing gear control system based on time‐triggered architecture (TTA).

In this paper, a new landing gear control system based on TTA is proposed. The reliability of the proposed system is investigated using a combination of Markov analysis and MIL‐HDBK‐217 methods.

The results show that by integration of TTP/C and TTP/A technologies, the advantages of both are achieved. A very high level of reliability is obtained. This increases the confidence when adopting distributed landing gear control technology.

The paper presents a new landing gear control system based on TTA, the reliability of which is very high.