Absolute stability analysis of sampled-data scaled bilateral teleoperation systems

Stability of a bilateral teleoperation system may be jeopardized by controller discretization, which has been shown to involve energy leaks. This paper proposes a novel approach to analyzing the absolute stability of sampled-data bilateral teleoperation systems consisting of discrete-time controllers and continuous-time master, slave, operator, and environment. The proposed stability analysis permits scaling and delay in the master and the slave positions and forces. The absolute stability conditions reported here impose bounds on the gains of the discrete-time controller, the damping terms of the master and the slave, and the sampling time. A design-related application of these results is in proper selection of various control parameters and the sampling rate for stable teleoperation under discrete-time control. To explore the trade-off between the control gains and the sampling time, it is studied that how large sampling times, which require low control gains for maintaining stability, can lead to unacceptable teleoperation transparency and human task performance in a teleoperated switching task. This shows that the effect of sampling time must be taken into account because neglecting it (as in the absolute stability literature) undermines both stability and transparency of teleoperation. The resulting absolute stability condition has been verified via experiments with two Phantom Omni robots.     

A design of bilateral teleoperation systems using composite adaptive controller

This paper presents a synchronization scheme of bilateral teleoperation systems using composite adaptive controller. To design a controller for bilateral teleoperation systems, all the parameters of the master and the slave robots need to be known. However, there exist parameter uncertainties in the robot manipulators. A composite adaptive controller is designed for convergence of states and parameters of the master and the slave robots in the presence of parameter uncertainties. Consequently, position and force tracking problems in free and contact motion are solved in a synchronized manner. Through a number of simulations, the superiority of the proposed method over existing works is illustrated. Furthermore, for the validation of utility of the proposed method in an actual embedded system, the algorithms are implemented and tested in FPGA-based hardware controller.     

Passivity-based control for bilateral teleoperation: A tutorial

This tutorial revisits several of the most recent passivity-based controllers for nonlinear bilateral teleoperators with guaranteed stability properties. These schemes, which include scattering–based, damping injection and adaptive controllers, ensure asymptotic stability in multiple situations that range from constant to variable time-delays, with or without scattering transformation and with or without position tracking capabilities. Although all controllers exploit the basic property of passivity of the teleoperators, they have been developed invoking various analysis and design tools, which complicates their comparison and relative performance assessment. The objective of this paper is to present a unified theoretical framework—based on a general Lyapunov–like function—that, upon slight modification, allows to analyze the stability of all the schemes.     

Synchronization of bilateral teleoperators with time delay

Bilateral teleoperators, designed within the passivity framework using concepts of scattering and two-port network theory, provide robust stability against constant delay in the network and velocity tracking, but cannot guarantee position tracking in general. In this paper we fundamentally extend the passivity-based architecture to guarantee state synchronization of master/slave robots in free motion independent of the constant delay and without using the scattering transformation. We propose a novel adaptive coordination architecture which uses state feedback to define a new passive output for the master and slave robots containing both position and velocity information. A passive coordination control is then developed which uses the new outputs to state synchronize the master and slave robots in free motion. The proposed algorithm also guarantees ultimate boundedness of the master/slave trajectories on contact with a passive environment. Experimental results are also presented to verify the efficacy of the proposed algorithms.     

A performance comparison of robust adaptive controllers: linear systems

We consider robust adaptive control designs for relative degree one, minimum phase linear systems of known high frequency gain. The designs are based on the dead-zone and projection modifications, and we compare their performance w.r.t. a worst case transient cost functional with a penalty on the ^∞ norm of the output, control and control derivative. We establish two qualitative results. If a bound on the ^∞ norm of the disturbance is known and the known a priori bound on the uncertainty level is sufficiently conservative, then it is shown that a dead-zone controller outperforms a projection controller. The complementary result shows that the projection controller is superior to the dead-zone controller when the a priori information on the disturbance level is sufficiently conservative.     

Interactive and diagnostic uses of management control systems in IS projects: Antecedents and their impact on performance

We attempted to determine how formal management control systems (MCS) are used by project managers in IS development (ISD) contexts. This involved investigating the antecedents of two types of project MCS use (interactive and diagnostic), and their direct and moderated impact on project performance. PLS analysis of data collected in a survey of 93 projects indicated that project managers’ level of discretion positively affected their level of interactive use of project MCS but did not influence their diagnostic use. Our findings also showed that interactive use of MCS enhanced performance when task uncertainty (task novelty and complexity) of an ISD was high, but worsened it when task uncertainty was low. Finally, diagnostic use of MCS apparently increased project performance when an ISD task uncertainty was low, but did not reduce it when task uncertainty was high. Overall, these results were stable across different size projects.     

High-fidelity sliding mode control of a pneumatic haptic teleoperation system

For a pneumatic teleoperation system with on/off solenoid valves, sliding mode control laws for position and force ensuring low switching (open/close) activity of the valves are developed. Since each pneumatic actuator has two pneumatic chambers with a total of four on/off valves, 16 possible combinations (‘operating modes’) for the valves’ on/off positions exist, but only seven of which are both functional and unique. While previous work has focused on three-mode sliding-based position control of one pneumatic actuator, this paper develops the seven-mode sliding-based bilateral control of a teleoperation system comprising a pair of pneumatic actuators. The proposed bilateral sliding control schemes are experimentally validated on a pair of actuators utilizing position-position and force-position teleoperation architectures. The results demonstrate that leveraging the additional modes of operation leads to more efficient and smoother control of the pneumatic teleoperation system. It was found that viscous friction forces were crippling haptic feedback in the position-position architecture. Through the use of force sensors, the force-position architecture was able to compensate for the heavy viscous friction forces.     

Noise tolerant iterative learning control for a class of continuous-time systems

The paper proposes a noise tolerant iterative learning control (ILC) for a class of linear continuous-time systems, which achieves high-precision tracking for uncertain plants by iteration of trials in the presence of heavy measurement noise. The robustness against measurement noise is achieved through (i) projection of continuous-time I/O signals onto a finite-dimensional parameter space, (ii) using error data of all past iterations via an integral operation in the learning law and (iii) noise reduction by H² optimization subject to a specified convergence speed of the ILC.     

A comparison between optimization algorithms applied to synchronization of bilateral teleoperation systems against time delay and modeling uncertainties

The goal of this paper is to achieve optimal performance for synchronization of bilateral teleoperation systems against time delay and modeling uncertainties, in both free and contact motions. Time delay in bilateral teleoperation systems imposes a delicate tradeoff between the conflicting requirements of stability and transparency. To this reason, in this paper, population-based optimization algorithms are employed to tuning the proposed controller parameters. The performance of tuned controllers is compared with the gains obtained by Cuckoo Optimization Algorithm (COA), Biogeography-Based Optimization (BBO), Imperialist Competitive Algorithm (ICA), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization with continuous domain (ACOR), Self-adaptive Differential Evolution with Neighborhood Search (SaNSDE), Adaptive Differential Evolution with Optional External Archive (JADE), Differential Evolution with Ensemble of Parameters and mutation strategies (EPSDE) and Cuckoo Search (CS). Through numerical simulations, the validity of the proposed method is illustrated. It is also shown that the COA algorithm is able to solve synchronization problem with high performance in stable transparent bilateral teleoperation systems.     

Towards models of tasks and task complexity in supervisory control applications

Dynamic task environments in supervisory control situations differ from those traditionally investigated in problem-solving research in that (1) several task goals exist in parallel, (2) task goals change dynamically as die behaviour of the technical process changes, and (3) information required to accomplish task goals changes across time. In the present work, it is suggested that such dynamic task environments can be described using two types of task goal networks, namely a control task goal (CTG) network and an information processing goal (IPG) network. CTG networks are generated by analysis of the operational states required to produce the commodity for which a technical system has been designed. For example, such analyses can be performed using approaches such as Mitchell's operator function model or canonical means-end analyses. IPG networks are generated by using the recenUy proposed functional information and knowledge acquisition (FIKA) modelling technique. Two examples from different domains illustrate how these task goal networks can be used to describe dynamic task environments. Finally, two different ways of using the task modelling approach are briefly discussed.     

A distributed task planning system for computer-integrated manufacturing systems

A formal mathematical framework for a distributed task planning method suitable for computerintegrated manufacturing systems is proposed. All pertinent algorithms are derived. A detailed timing analysis associated with primitive actions and activities (complex tasks) execution is presented. A formal language is designed for event tracking and error specification. Based on the derived language, an error recovery mechanism (automaton) is proposed. A case study demonstrates the applicability of the presented method with and without error occurrences.Dr Kokinaki is currently Science and Engineering Research Centre, De Montfort University, UK.     

Improving transient performance in tracking control for linear multivariable discrete-time systems with input saturation

In this paper, we present a composite nonlinear feedback (CNF) control technique for linear discrete-time multivariable systems with actuator saturation. The CNF control law serves to improve the transient performance of the closed-loop system by adding an additional nonlinear feedback. The linear feedback can be designed to yield a quick response at the initial stage, then the nonlinear feedback is introduced to smooth out overshoots when the system output approaches the target reference. As such, the resulting closed-loop system typically has very fast transient response and small overshoots. The goal of this work is to complete the theory for general discrete-time systems. The technique is applied to a magnetic-tape-drive servo system design and yields a huge improvement in settling time compared to that of a purely linear controller.     

Job performance through mobile enterprise systems: The role of organizational agility,location independence,and task characteristics

This study examines how organizational workers improve their perceived job performance through the use of Mobile Enterprise Systems (MES), while also investigating the impact of perceived organizational agility and location independence on technology acceptance of MES. This study also tests the moderating role of task characteristics (task significance and feedback) on the relationship between MES usage and perceived job performance. Based on the extant technology acceptance model (TAM), we proposed an extended TAM and conducted a large-scale survey among organizational workers who use MES in their workplace across industries. Our findings suggest that both positive attitude toward MES and a high level of habitual MES usage are positively associated with perceived job performance, and that task characteristics positively moderate the relationship between habitual usage (attitude toward MES) and perceived job performance. More importantly, we also found that organizational agility is positively associated with both perceived ease of use and perceived usefulness, while location independence is positively associated with perceived ease of use. The present findings provide us with a deeper understanding of how organizational workers utilize MES and how they improve their perceived job performance through the use of MES. Based on these findings, we discuss further implications and limitations.     

Presence and task performance: an approach in the light of cognitive style

The paper highlights the relationship between each of four bi-polar dimensions of personality cognitive style, such as extraversion–introversion, sensing–intuition, thinking–feeling and judging–perceiving, and the level of sense of presence experienced. Findings indicate that individuals who are more sensitive, more feeling or more introverted experience a higher level of presence. While not reaching statistical significance, differing cognitive styles appear to impact on task performance. The apparent negative relationship discovered between sense of presence and task performance should be considered in the light of task characteristics. We discuss the implications of these findings and how they contribute to an understanding of the complex relationship that exists between presence and task performance and how this subsequently ought to influence the design of virtual environments.     

Robust performance control of uncertain nonlinear systems: A self-tuning approach

The problem of output regulation with a guaranteed H^∞ performance, besides robust stability, for a class of feedback linearizable nonlinear systems via self-tuning controllers is investigated. The H^∞ performance consists of the desired disturbance attenuation and internal finite L²-gain stability. We show that, under the perturbations of matched parametric uncertainties, the sufficient condition for the existence of a self-tuning controller reduces to the solvability of a single Hamilton-Jacobi-Isaacs inequality (or algebraic Riccati equation) which indicates that the design can be performed as if the system uncertainties were absent. Under certain situations, the sufficient condition is also necessary. Once a solution of this nonlinear differential inequality (or algebraic equation) is available, a desired self-tuning controller with gradient-type parameter estimator can easily be constructed. The present work falls into the category of singular nonlinear H^∞ control since the desired H^∞ performance does not require any penalty on control input variables. The results also provide an immediate application to H^∞ self-tuning model reference control in linear systems under full state measurement.     

一种离散时间系统变结构控制的新方法

研究离散时间系统变结构控制问题,提出一种新的离散变结构趋近律.利用该趋近律设计的离散变结构控制器,不仅能大幅度削弱抖振,使系统运动最终趋干原点不存在稳态振荡,而且可使系统的准滑动模态保持步步穿越切换面的基本属性,有效地改善了控制品质,提高了系统的鲁棒性.仿真结果验证了该方法的有效性与合理性.     

A high performance algorithm for static task scheduling in heterogeneous distributed computing systems

Effective task scheduling is essential for obtaining high performance in heterogeneous distributed computing systems (HeDCSs). However, finding an effective task schedule in HeDCSs requires the consideration of both the heterogeneity of processors and high interprocessor communication overhead, which results from non-trivial data movement between tasks scheduled on different processors. In this paper, we present a new high-performance scheduling algorithm, called the longest dynamic critical path (LDCP) algorithm, for HeDCSs with a bounded number of processors. The LDCP algorithm is a list-based scheduling algorithm that uses a new attribute to efficiently select tasks for scheduling in HeDCSs. The efficient selection of tasks enables the LDCP algorithm to generate high-quality task schedules in a heterogeneous computing environment. The performance of the LDCP algorithm is compared to two of the best existing scheduling algorithms for HeDCSs: the HEFT and DLS algorithms. The comparison study shows that the LDCP algorithm outperforms the HEFT and DLS algorithms in terms of schedule length and speedup. Moreover, the improvement in performance obtained by the LDCP algorithm over the HEFT and DLS algorithms increases as the inter-task communication cost increases. Therefore, the LDCP algorithm provides a practical solution for scheduling parallel applications with high communication costs in HeDCSs.     

Robust control of linear discrete-time systems

Given a linear discrete-time system with additive disturbances, a general methodology for designing a stable control algorithm is shown. The approach is Lyapunov-based with certain liberty of tailoring the candidate function for a given problem. Comparison to the existing solutions based on a variable structure approach is given.     

Discrete-time neural network output feedback control of nonlinear discrete-time systems in non-strict form

An adaptive neural network (NN)-based output feedback controller is proposed to deliver a desired tracking performance for a class of discrete-time nonlinear systems, which are represented in non-strict feedback form. The NN backstepping approach is utilized to design the adaptive output feedback controller consisting of: (1) an NN observer to estimate the system states and (2) two NNs to generate the virtual and actual control inputs, respectively. The non-causal problem encountered during the control design is overcome by using a dynamic NN which is constructed through a feedforward NN with a novel weight tuning law. The separation principle is relaxed, persistency of excitation condition (PE) is not needed and certainty equivalence principle is not used. The uniformly ultimate boundedness (UUB) of the closed-loop tracking error, the state estimation errors and the NN weight estimates is demonstrated. Though the proposed work is applicable for second order nonlinear discrete-time systems expressed in non-strict feedback form, the proposed controller design can be easily extendable to an nth order nonlinear discrete-time system.     

Understanding the attitudes,knowledge sharing behaviors and task performance of core developers: A longitudinal study

ContextPrior research has established that a few individuals generally dominate project communication and source code changes during software development. Moreover, this pattern has been found to exist irrespective of task assignments at project initiation.ObjectiveWhile this phenomenon has been noted, prior research has not sought to understand these dominant individuals. Previous work considering the effect of team structures on team performance has found that core communicators are the gatekeepers of their teams’ knowledge, and the performance of these members was correlated with their teams’ success. Building on this work, we have employed a longitudinal approach to study the way core developers’ attitudes, knowledge sharing behaviors and task performance change over the course of their project, based on the analysis of repository data.MethodWe first used social network analysis (SNA) and standard statistical analysis techniques to identify and select artifacts from ten different software development teams. These procedures were also used to select central practitioners among these teams. We then applied psycholinguistic analysis and directed content analysis (CA) techniques to interpret the content of these practitioners’ messages. Finally, we inspected these core developers’ activities as recorded in system change logs at various points in time during systems’ development.ResultsAmong our findings, we observe that core developers’ attitudes and knowledge sharing behaviors were linked to their involvement in actual software development and the demands of their wider project teams. However, core developers appeared to naturally possess high levels of insightful characteristics, which became evident very early during teamwork.ConclusionsProject performance would likely benefit from strategies aimed at surrounding core developers with other competent communicators. Core developers should also be supported by a wider team who are willing to ask questions and challenge their ideas. Finally, the availability of adequate communication channels would help with maintaining positive team climate, and this is likely to mitigate the negative effects of distance during distributed developments.