Adaptive Inverse Dynamics Four-Channel Control of Uncertain Nonlinear Teleoperation Systems

Most of the methods to date on bilateral control of nonlinear teleoperation systems lead to nonlinear and coupled closed-loop dynamics, even in the ideal case of perfect knowledge of the master, the slave, the human operator and the environment. Consequently, the transparency of these closed-loop systems is difficult to study. In comparison, inverse dynamics controllers can deal with the nonlinear terms in the dynamics in a way that, in the ideal case, the closed-loop systems become linear and decoupled. In this paper, for multi-d.o.f. nonlinear teleoperation systems with uncertainties, adaptive inverse dynamics controllers are incorporated into the four-channel bilateral teleoperation control framework. The resulting controllers do not need exact knowledge of the dynamics of the master, the slave, the human operator or the environment. A Lyapunov analysis is presented to prove the transparency of the teleoperation system. Simulations are also presented to show the effectiveness of the proposed approach.     

模糊Delta算子系统的鲁棒稳定性分析与控制

研究一类由Delta算子描述的T-S型模糊系统的鲁棒稳定性与状态反馈控制设计问题。基于Delta域的Lyapunov稳定性理论，利用线性矩阵不等式(LMI)的方法，给出了不确定模糊Delta算子系统鲁棒稳定及存在状态反馈控制器使得闭环系统稳定的充分条件。这不仅将连续与离散不确定模糊系统的有关结果纳入Delta算子系统的统一框架中，也为Delta算子方法在非线性系统中的应用研究提供了一种有效途径。数值算例说明了该方法的有效性。     

Robust PID controller design for processes with stochastic parametric uncertainties

The stability and performance of a system can be inferred from the evolution of statistical characteristics of the system's states. Wiener's polynomial chaos can provide an efficient framework for the statistical analysis of dynamical systems, computationally far superior to Monte Carlo simulations. This work proposes a new method of robust PID controller design based on polynomial chaos for processes with stochastic parametric uncertainties. The proposed method can greatly reduce computation time and can also efficiently handle both nominal and robust performance against stochastic uncertainties by solving a simple optimization problem. Simulation comparison with other methods demonstrated the effectiveness of the proposed design method.     

From classic observability to a simple fuzzy observability for fuzzy discrete-event systems

In order to determine uncertainties from restricted available information, fuzzy discrete-event systems (FDESs), or fuzzy discrete-event dynamic systems (FDEDSs), were recently proposed. These frameworks include fuzzy states and events occurring simultaneously with different membership degrees. Fuzzy states and events have been used to describe uncertainties that occur often in practical problems, such as treatment planning for HIV/AIDS patients, sensory information processing for robotic control, and fault diagnosis problems. In order to measure information associated with FDESs or FDEDSs, the classical discrete event system (DES) observability has been turned into fuzzy observability for FDESs or FDEDSs. The newly proposed method allows ease of defining degrees of observability so that uncertainties in FDESs or FDEDSs can be dealt with effectively. This gives an opportunity to design better decision-making systems. To calculate the observability degree, a simple fuzzy observability checking method is introduced, and two examples are elaborated upon to illustrate the presented method. Finally, the newly proposed method is tested on a heating, ventilating, and air-conditioning (HVAC) system.     

A knowledge-based simulation environment for hierarchical flexiblemanufacturing

This article presents an approach to embedding expert systems within an object oriented simulation environment. The basic idea is to create classes of expert system models that can be interfaced with other model classes. An expert system shell is developed within a knowledge-based design and simulation environment which combines artificial intelligence and systems modeling concepts. In the given framework, interruptible and distributed expert systems can be defined as components of simulations models. This facilitates simulation modeling of knowledge-based controls for flexible manufacturing and many other autonomous intelligent systems. Moreover, the structure of a system can be specified using a recursive system entity structure (SES) and unfolded to generate a family of hierarchical structures using an extension of SES pruning called recursive pruning. This recursive generation of hierarchical structures is especially appropriate for design of multilevel flexible factories. The article illustrates the utility of the proposed framework within the flexible manufacturing context     

基于自抗扰控制的机器人定位策略

机器人定位即需根据传感器测量对自身位置进行估计. 由于机器人系统模型的复杂非线性, 工况环境中的不确定干扰, 定位结果不可避免地会受到系统内外扰动的影响. 现有的定位算法往往仅能依赖模型或传感配置以及算法自身的鲁棒性被动抗扰, 这使得定位系统的抗扰能力有限、应用场景受限. 本文基于自抗扰控制思想提出一种 能够主动补偿系统内外扰动的机器人定位策略. 该策略将系统中所有能够影响最终定位结果的不确定因素统一视为总扰动, 并设计扩张状态观测器实现对总扰动的观测, 在此基础上构建控制器补偿总扰动影响, 以使定位结果更加准确. 与传统的定位抗扰策略相比, 本文所提出的抗扰定位策略并不依赖于模型或特定的传感配置, 能够处理任意有界的扰动类型, 理论上能够成为定位抗干扰的终极解决路径. 最后, 基于李雅普诺夫理论证明了系统的稳定性. 仿真和实车实验验证了本文提出的基于自抗扰控制的机器人定位策略能够有效地观测系统总扰动, 并补偿扰动影响, 提高定位结果的准确度.     

Multicriteria decision making under uncertainty: An advanced ordered weighted averaging operator for planning electric power systems

In this study, an advanced ordered weighted averaging (AOWA) operator is proposed for tackling multicriteria decision making (MCDM) problems under uncertainties. The AOWA incorporates techniques of interval theory and a center of gravity (COG) method within a traditional ordered weighted averaging (OWA) operator. It can deal with the uncertain inputs under optimistic and pessimistic conditions without knowing their distribution information and linguistic important degrees of all inputs in MCDM systems. The results obtained help decision makers select the optimal alternative according to their optimism degrees. A case study of planning electric power problems is provided for demonstrating the applicability of the proposed method. The results indicate that reasonable solutions have been generated for both discrete intervals and linguistic inputs. For all criteria under consideration, corrective alternatives can be undertaken sensitively under various optimism degrees and thus can help resolve the conflicts in electric power systems under uncertainties.     

Robust H∞ filtering for a class of Markovian jump systems with time‐varying delays based on delta operator approach

In this paper, the robust H_∞ filtering problem for a class of discrete Markovian jump systems with time‐varying delays and linear fractional uncertainties is investigated based on delta operator approach. Based on Lyapunov‐Krasovskii functional in delta domain, new delay‐dependent sufficient conditions for the solvability of this problem are presented in terms of linear matrix inequalities (LMIs). When these LMIs are feasible, an explicit expression of a desired jump H_∞ filter is given. The proposed method can unify some previous related continuous and discrete systems into the delta operator systems framework. Numerical examples are given to illustrate the effectiveness of the developed techniques. © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Ecological models of human performance based on affordance,emotion and intuition

This paper proposes a complementary approach to Rasmussen's taxonomy of the human skill-, rule-, and knowledge-based performance models by combining the ecological concept of affordances with the neural concepts of human emotion and intuition. The classical cognitive engineering framework is extended through the neuro-ecological approach, including personal human attributes important in exercising control over the work environment. The proposed affordance-, emotion-, and intuition-based models correspond to the three types of human performance, namely: learning, adaptive and tuning control, respectively. The new framework is not a predictive model of the operator behaviour, but rather it describes the processes of neuro-ecological control of the human environment.     

Random matrix theory for modeling uncertainties in computational mechanics

This paper deals with data uncertainties and model uncertainties issues in computational mechanics. If data uncertainties can be modeled by parametric probabilistic methods, for a given mean model, a nonparametric probabilistic approach can be used for modeling model uncertainties. The first part is devoted to random matrix theory for which we summarize previous published results and for which two new ensembles of random matrices useful for the nonparametric models are introduced. In a second part, the nonparametric probabilistic approach of random uncertainties is presented for linear dynamical systems and for nonlinear dynamical systems constituted of a linear part with additional localized nonlinearities. In a third part, a new method is proposed for estimating the parameters of the nonparametric approach from experiments. Finally, examples with experimental comparisons are given.     

Robust stability of MIMO nonlinear uncertain systems using operator-based right coprime factorisation

In this paper, a class of multi-input–multi-output (MIMO) nonlinear systems with uncertainties is considered by using operator-based right coprime factorisation. First, based on proposed quotient operators, coupling effect of the MIMO nonlinear systems is discussed. Second, based on the operator-based right coprime factorisation approach, sufficient conditions for guaranteeing robust stability of the MIMO nonlinear systems with uncertainties are proposed by using a new unimodular operator. Finally, a simulation example is shown to illustrate the proposed design scheme for the MIMO nonlinear systems with uncertainties.     

Assisted teleoperation in changing environments with a mixture of virtual guides

Haptic guidance is a powerful technique to combine the strengths of humans and autonomous systems for teleoperation. The autonomous system can provide haptic cues to enable the operator to perform precise movements; the operator can interfere with the plan of the autonomous system leveraging his/her superior cognitive capabilities. However, providing haptic cues such that the individual strengths are not impaired is challenging because low forces provide little guidance, whereas strong forces can hinder the operator in realizing his/her plan. Based on variational inference, we learn a Gaussian mixture model (GMM) over trajectories to accomplish a given task. The learned GMM is used to construct a potential field which determines the haptic cues. The potential field smoothly changes during teleoperation based on our updated belief over the plans and their respective phases. Furthermore, new plans are learned online when the operator does not follow any of the proposed plans or after changes in the environment. User studies confirm that our framework helps users perform teleoperation tasks more accurately than without haptic cues and, in some cases, faster. Moreover, we demonstrate the use of our framework to help a subject teleoperate a 7 DoF manipulator in a pick-and-place task.     

Robust performance analysis for uncertain negative‐imaginary systems

Negative‐imaginary systems are important in engineering practice as this class of systems appears quite often in practical problems, for example, lightly damped flexible structures with collocated position sensors and force actuators. In this paper, an analytical framework for robust performance of uncertain negative‐imaginary systems is proposed. The results are obtained by transforming negative‐imaginary systems into a bounded‐real framework via the positive‐real property. This paper deals with all the significant technical difficulties that appear due to the transformation and the punctured j ω‐axis frequency condition of negative‐imaginary systems. The problem is equivalently cast into a structured singular value condition that gives a quantitative performance test for this class of systems. This result also gives an analytical framework for robust stability when the perturbations are mixture of bounded‐real and negative‐imaginary uncertainties. A numerical example is presented to show the usefulness of the proposed methods. Copyright © 2011 John Wiley & Sons, Ltd.     

基于定量反馈理论的时滞系统自抗扰控制参数整定

工业过程对象普遍存在时滞、模型参数不确定性和外部扰动多等特点,传统Smith预估控制方法难以设计出满足期望性能的鲁棒控制器.针对模型参数不确定性和外部扰动,本文采用自抗扰控制技术进行估计和补偿.针对系统存在时滞的特点,本文提出改进Smith预估器结构,提升扩张状态观测器对于扰动估计的实时性.在此基础上,本文以一阶时滞系统为例提出了控制器参数整定方法.首先根据最优参数选取准则确定预估器模型,然后在等效模型框架下采用定量反馈理论整定自抗扰控制器参数,确保控制系统达到预期性能指标.在仿真实验中,将所提出方法与几种常见时滞系统控制方法进行比较,通过设定值跟踪、抗扰及蒙特卡罗实验验证了所提出方法具有良好抗扰能力与鲁棒性.     

Ecological models of human performance based on affordance,emotion and intuition

This paper proposes a complementary approach to Rasmussen's taxonomy of the human skill-, rule-, and knowledge-based performance models by combining the ecological concept of affordances with the neural concepts of human emotion and intuition. The classical cognitive engineering framework is extended through the neuro-ecological approach, including personal human attributes important in exercising control over the work environment. The proposed affordance-, emotion-, and intuition-based models correspond to the three types of human performance, namely: learning, adaptive and tuning control, respectively. The new framework is not a predictive model of the operator behaviour, but rather it describes the processes of neuro-ecological control of the human environment.     

网络靶场攻防场景设计框架

随着网络威胁的暴露范围越来越广,开发新的工具来改进网络防御是一个重大挑战。网络防御中最重要的问题是人员技能培训,网络靶场就是用于此目的。它提供用于训练和对抗比赛的虚拟环境。本文用VDSL语言定义了一个定制的网络环境,并实现了一个框架,允许将网络靶场场景转换为Prism模型。这样就可以进行训练和赛事结果的定量分析并可以对这个框架进行持续优化。     

Uncertainty quantification of MEMS using a data-dependent adaptive stochastic collocation method

This paper presents a unified framework for uncertainty quantification (UQ) in microelectromechanical systems (MEMS). The goal is to model uncertainties in the input parameters of micromechanical devices and to quantify their effect on the final performance of the device. We consider different electromechanical actuators that operate using a combination of electrostatic and electrothermal modes of actuation, for which high-fidelity numerical models have been developed. We use a data-driven framework to generate stochastic models based on experimentally observed uncertainties in geometric and material parameters. Since we are primarily interested in quantifying the statistics of the output parameters of interest, we develop an adaptive refinement strategy to efficiently propagate the uncertainty through the device model, in order to obtain quantities like the mean and the variance of the stochastic solution with minimal computational effort. We demonstrate the efficacy of this framework by performing UQ in some examples of electrostatic and electrothermomechanical microactuators. We also validate the method by comparing our results with experimentally determined uncertainties in an electrostatic microswitch. We show how our framework results in the accurate computation of uncertainties in micromechanical systems with lower computational effort.     

Supply chain ontology: Review, analysis and synthesis

In an environment where supply chains compete against supply chains, information sharing among supply chain partners using information systems is a competitive tool. Supply chain ontology has been proposed as an important medium for attaining information systems interoperability. Ontology has its origin in philosophy, and the computing community has adopted ontology in its language. This paper presents a study of state of the art research in supply chain ontology and identifies the outstanding research gaps. Six supply chain ontology models were identified from a systematic review of literature. A seven point comparison framework was developed to consider the underlying concepts as well as application of the ontology models. The comparison results were then synthesised into nine gaps to inform future supply chain ontology research. This work is a rigorous and systematic attempt to identify and synthesise the research in supply chain ontology.     

在Eclipse上建立流程图编辑器

Eclipse是一个可扩展的开发环境,利用Eclipse插件开发技术可以开发自己的开发工具,并无缝地集成到Eclipse统一环境下,有着统一的外观,操作和系统资源管理.利用GEF框架可以开发出流程图编辑器.该流程图编辑器可以集成于Eclipse统一环境下,为其它系统服务.