A programming environment for real-time control of distributed multiple robotic systems

In recent years there has been great interest in robot software control architectures. However, although many interesting solutions have been presented, most of the research problems tackled related to a single robot perception, navigation and action in everyday environments. Instead, most of the practical applications of mobile robotics for service tasks in civilian environments consist of systems composed of multiple robots communicating with each other, with external sensing and actuating devices, and with external supervising workstations. RoboCup offers a great opportunity to deal with this problem. In fact the software architecture of a robot soccer player must allow successful intra-robot integration of the different activities (visual perception, path planning, strategy planning, motion control, etc.) spanning many different types of representation (raw sensor data, images, symbolic plans, etc.) and it must also guarantee successful inter-robot integration by supporting communication and cooperation. This paper focuses on this problem, presenting ETHNOS-IV - a programming environment for the design of a real-time control system composed of different robots, devices and external supervising or control stations - which has been successfully used within the Italian ART robot team in the RoboCup-99 competition. ETHNOS provides support from three main point of views which will be addressed in detail: inter-robot and intra-robot communication, realtime task scheduling, and software engineering and code reuse. Experimental results illustrating the advantages of this approach will also be presented.     

A distributed control scheme for multiple robotic vehicles to make group formations

This paper presents a novel distributed control scheme of multiple robotic vehicles. Each robotic vehicle in this scheme has its own coordinate system, and it senses its relative position and orientation to others, in order to make group formations. Although there exists no supervisor and each robotic vehicle has only relative position feedback from the others in the local area around itself, all the robotic vehicles are stabilized, which we have succeeded in proving mathematically only in the cases where the attractions between the robots are symmetrical. Each robotic vehicle especially has a two-dimensional control input referred to as a “formation vector” and the formation is controllable by the vectors. The validity of this scheme is supported by computer simulations.     

一种CMAC网络模型及其在机器人控制中的应用

小脑模型关节控制器（CMAC）具有学习算法简单、在线学习速度快的优点,非常适于机器人等复杂系统的自适应控制,本文阐述了CMAC的原理,证明了其收敛性,提出了一种适合于机器人轨迹跟踪控制的CMAC,并给出了仿真实验结果。     

基于特征线法的双曲型分布参数模型预测控制及其应用

本文针对双曲型分布参数系统提出基于特征线法的模型预测控制算法. 通过特征线变换将描述分布参数模型的偏微分方程转化为常微分方程; 进而求解得到分布参数系统状态变量的解析式; 离散化后作为预测模型用于模型预测控制. 以循环流化床烟气脱硫系统中SO2浓度控制为例, 进行仿真研究, 结果表明基于特征线法的模型预测控制算法可以实现对双曲型分布参数系统的有效控制, 并且该算法的控制效果优于目前工程应用的前馈反馈 控制策略.     

A privacy-aware access control model for distributed network monitoring

In this paper, we introduce a new access control model that aims at addressing the privacy implications surrounding network monitoring. In fact, despite its importance, network monitoring is natively leakage-prone and, moreover, this is exacerbated due to the complexity of the highly dynamic monitoring procedures and infrastructures, that may include multiple traffic observation points, distributed mitigation mechanisms and even inter-operator cooperation. Conceived on the basis of data protection legislation, the proposed approach is grounded on a rich in expressiveness information model, that captures all the underlying monitoring concepts along with their associations. The model enables the specification of contextual authorisation policies and expressive separation and binding of duty constraints. Finally, two key innovations of our work consist in the ability to define access control rules at any level of abstraction and in enabling a verification procedure, which results in inherently privacy-aware workflows, thus fostering the realisation of the Privacy by Design vision.     

A distributed specification model and its prototyping

A specification model is described that is based on the finite-state machine but is distributed. The model allows the user to decompose a large system into separate views. Each view is a complete system in itself, and reveals how the whole system would behave as seen from a certain angle. Put together, the combined views present a complete picture of the whole system. The complexity of a large centralized system is thus distributed and subdued. The author offers a simple execution scheme for the model. Using a high-level state-transition language called SXL, constructs in the model are expressed as preconditions and postconditions of transitions. The execution scheme allows all the views in the model to proceed in a parallel but harmonious way, producing a working prototype for the modeled system     

Resource scheduling and load balancing in distributed robotic control systems

This paper describes the latest advances made to a software architecture designed to control multiple miniature robots. As the robots themselves have very limited computational capabilities, a distributed control system is needed to coordinate tasks among a large number of robots. Two of the major challenges facing such a system are the scheduling of access to system resources and the distribution of work across multiple workstations. This paper discusses solutions to these problems in the context of a distributed surveillance task.     

模糊CMAC及其在机器人轨迹跟踪控制中的应用

小脑模型关节控制器(CMAC)具有结构简单,学习快速的优点,但是它的空间划分方式不能在线进行调整,影响了其自适应能力的提高.本文将模糊理论引入CMAC,提出了一种能够反映人类小脑认知的模糊性和连续性的模糊小脑模型关节控制器(FCMAC).该控制器对CMAC的空间划分方式进行了模糊化处理,可通过BP学习算法对CMAC的空间划分方式进行在线调整,大大提高了CMAC的自适应能力.所提出的FCMAC被应用于机器人的轨迹跟踪控制系统以克服机器人系统中非线性和不确定性因素的影响.仿真实验结果表明,所提FCMAC与传统的CMAC相比性能上有了很大的改善.     

A robust distributed model predictive control algorithm

Although distributed model predictive control (DMPC) has received significant attention in the literature, the robustness of DMPC with respect to model errors has not been explicitly addressed. In this paper, a novel online algorithm that deals explicitly with model errors for DMPC is proposed. The algorithm requires decomposing the entire system into N subsystems and solving N convex optimization problems to minimize an upper bound on a robust performance objective by using a time-varying state-feedback controller for each subsystem. Simulations examples were considered to illustrate the application of the proposed method.     

一种分布式环境下基于角色的访问控制模型

针对访问控制模型在分布式系统下的局限性,提出一种分布式系统下的基于角色的访问控制模型。该模型以传统RBAC为基础,对其进行了扩展,一方面通过将角色扩展为职能角色和任务角色,另一方面为任务角色增加一个属性,用以标识该角色所赋予的主体属于本域还是外域,避免了采用对等角色直接进行角色分配的简单化处理。从而一方面有利于最小权限的实现,另一方面实现了对本域和外域的主体访问请求采用不同的策略,使基于角色的控制应用范围从集中式的控制领域扩展到分布式的控制领域,以适应不断发展的分布式环境系统的需求。     

Implementation of real-time distributed control for discrete event robotic systems using Petri nets

This article presents a systematic method of modeling and implementing real-time control for discrete-event robotic systems using Petri nets. Because, in complex robotic systems such as flexible manufacturing systems, the controllers are distributed according to their physical structure, it is desirable to realize real-time distributed control. In this article, the task specification of robotic processes is represented as a system control-level net. Then, based on the hierarchical approach, it is transformed into detailed subnets, which are decomposed and distributed into the local machine controllers. The implementation of real-time distributed control through communication between the system controller and the machine controllers on a microcomputer network is described for a sample robotic system. The proposed implementation method is sufficiently general, and can be used as an effective prototyping tool for consistent modeling, simulation, and real-time control of large and complex robotic systems.     

A review on model reference adaptive control of robotic manipulators

The accuracy of the motion control for robotic mechanisms will have an effect on their overall performance. Under the condition where the robotic end-effector carries different loads, the motions for each joint of robotic mechanisms change depending on different payload masses. Conventional control systems possess the potential issue that they cannot compensate the load variation effect. Adaptive control, especially the model reference adaptive control (MRAC), has therefore been put forward to handle the above issue. Adaptive control is generally divided into three categories, model reference, self-tuning and gain-scheduled. In this study, the authors only focus on the model-reference approach. To the best of the authors’ knowledge, very few recent research articles can be found in the area of MRAC especially for robotic mechanisms since robotic system is a highly nonlinear system, and it is difficult to guarantee the stability of MRAC in such system. This study presents a review and discussion on the MRAC of robotic mechanisms and some issues of MRAC for robotic mechanisms are also demonstrated. This study can provide a guideline for upcoming research in the field of MRAC for robotic mechanisms.     

情感智能的球磨机系统内模控制研究

针对球磨机系统控制过程中存在的多变量、强耦合、模型时变性的特点,提出基于情感智能的内模控制方案,采用大脑情感学习模型(BEL模型)对球磨机模型进行在线辨识,根据辨识结果设计BEL控制器,建立球磨机的BEL内模控制系统。仿真结果表明该控制方法跟踪快、解耦性能好,控制品质优于传统的解耦控制方法,能够较好地解决球磨机多变量、时变性、耦合性等问题。     

Robust distributed model predictive control

This paper presents a formulation for distributed model predictive control (DMPC) of systems with coupled constraints. The approach divides the single large planning optimization into smaller sub-problems, each planning only for the controls of a particular subsystem. Relevant plan data is communicated between sub-problems to ensure that all decisions satisfy the coupled constraints. The new algorithm guarantees that all optimizations remain feasible, that the coupled constraints will be satisfied, and that each subsystem will converge to its target, despite the action of unknown but bounded disturbances. Simulation results are presented showing that the new algorithm offers significant reductions in computation time for only a small degradation in performance in comparison with centralized MPC.     

An imaginary robot model and double-PD control for redundant robotic systems

The theory and applications of an imaginary robot model with a double-PD control law for redundant robotic systems are presented. The imaginary robot model is based on a special Riemannian metric decomposition for general nonlinear dynamic systems. This model offers an effective way for reducing nonlinear feedback formulation while preserving the linearized system equation. The developed procedure is also applicable to redundant robots. A three-dimensional redundant robot main-frame having three revolute joints plus a prismatic joint is used in the paper to illustrate the design procedure based on the imaginary robot model with the double-PD control scheme. The entire dynamic control algorithm is also verified by a simulation study on the four-joint three-dimensional robot arm.     

Models,feedback control,and open problems of 3D bipedal robotic walking

The fields of control and robotics are working toward the development of bipedal robots that can realize walking motions with the stability and agility of a human being. Dynamic models for bipeds are hybrid in nature. They contain both continuous and discrete elements, with switching events that are governed by a combination of unilateral constraints and impulse-like forces that occur at foot touchdown. Control laws for these machines must be hybrid as well. The goals of this paper are fourfold: highlight certain properties of the models which greatly influence the control law design; overview the literature; present two control design approaches in depth; and indicate some of the many open problems.     

Object-oriented and distributed approach for programming robotic manufacturing cells

Flexible manufacturing systems (FMS) are essential for small/medium batch and job shop manufacturing. These types of production systems are used to manufacture a considerable variety of products with medium/small production volumes. Therefore, the manufacturing platforms supporting these types of production must be flexible and organized in flexible manufacturing cells (FMC). Programming FMCs remains a difficult task and is an actual area of research and development. This paper reports an object-oriented approach developed for FMC programming. The work presented was first thought for application in industrial robot manipulators, and later extended to other FMC equipments just by putting the underlying ideas in a general framework. Initially, the motivation for this work was to develop means to add force control to a standard industrial robot manipulator. This problem requires remote access to the robot controller, remote programming and monitoring, as also is required to program and monitor any other FMC equipment. The proposed approach is distributed based on a client/server model and runs on Win32 platforms, i.e., Microsoft Windows and Windows NT. Implementation for the special case of industrial robot manipulators is presented, along with some application examples used for educational, research and industrial purposes.