Dynamics of control on digital platforms

Digital platforms are supraorganizational entities that use digital technology to facilitate interactions between diverse actors, leading to novel forms of organisation and accompanying forms of control. The current Information Systems (IS) literature, however, struggles to describe control on digital platforms in a way that does justice to the dynamic character of the phenomenon. Taking this as an opportunity, we follow the enactment of control over time and across parties in a hybrid ethnographic study of the social commerce platform Poshmark. Specifically, we conceptualise the dynamics of control as changes in the means of control—formal or informal—and the sources of control—operator or participants—over time. Tracking these conceptual dimensions, we identify the distinct ways control has changed on Poshmark. Synthesising these findings into four dynamics of control, we show that control on digital platforms is rarely static due to aggregate effects arising from the operator and from participant interactions with each other through the digital features deployed on the platform. Based on these insights, our study contributes to the IS literature on control by broadening the conception of control on digital platforms. The theoretical and practical insights generated in this paper thereby lay the foundation for the systematic study of the dynamics of control that are unique to platform environments.     

An SRWNN-based approach on developing a self-learning and self-evolving adaptive control system for motion platforms

In this paper, a self-recurrent wavelet neural network (SRWNN)-based indirect adaptive control architecture is modified for performing speed control of a motion platform. The transient behaviour of the original learning algorithm has been improved by modifying the learning rate updates. The contribution of the proposed modification has been verified via both simulations and experiments. Moreover, the performance of the proposed architecture is compared with robust RST designs performed on a similar benchmark system, to show that via adaptive nonlinear control, it is possible to obtain a fast step response without degrading the robustness of a multi-body mechanical system. Finally, the architecture is further improved so as to possess structural learning for populating the SRWNNs automatically, rather than employing static network structures, and simulation results are provided to show the performance of the proposed structural learning algorithm.     

数字式坦克炮控系统的设计及其关键技术探讨

针对炮控系统采用模拟控制存在离散性大、温漂严重、信息传输困难等问题,以某坦克为研究对象,设计了基于DSP的数字式炮控系统,并探讨了系统内部网络构建、系统PWM驱动控制、多模态自适应控制、系统控制器参数在线整定与可靠性设计等关键技术,最后对所研制的数字式炮控系统样机各项性能进行了试验验证,为进一步改善炮控系统性能和促进坦克电子综合化的发展奠定基础。     

饱和系统鲁棒控制及其在飞行控制中的应用

给出一种饱和系统鲁棒稳定性的分析和设计方法.通过对不确定系统的H∞优化过程的分析,并根据其反馈控制原理,按全部和部分输入超过限制分别考虑不同指标下的优化计算问题,得到了输入受限制条件下的3种Riccati方程.飞行控制器设计和仿真结果表明,采用该方法可给出满意的控制效果.     

Event-triggered adaptive tracking control for nonlinear systems with input saturation and unknown control directions

This article is concerned with event-triggered adaptive tracking control design of strict-feedback nonlinear systems, which are subject to input saturation and unknown control directions. In the design procedure, a smooth nonlinear function is employed to approximate the saturation function so that the controller can be designed under the framework of backstepping. The Nussbaum gain technique is employed to address the issue of the unknown control directions. A predetermined time convergent performance function and a nonlinear mapping technique are introduced to guarantee that the tracking error can converge in the predetermined time with a fast convergence rate and a high accuracy. Then the event-triggered adaptive prescribed performance tracking control strategy is proposed, which not only ensures the boundedness of all the closed-loop signals and the convergence of tracking error but also reduces the communication burden from the controller to the actuator. At last, the simulation study further tests the availability of the proposed control strategy.     

具有输入输出约束的无人直升机预设性能安全跟踪控制

针对无人直升机姿态与高度系统存在未知外部干扰、输入饱和、姿态与高度约束等问题, 本文提出一种具 有输入输出约束的预设性能安全跟踪控制方法. 首先, 针对无人直升机的姿态与高度约束, 通过设计一类边界保护 算法, 构建了新的安全期望跟踪信号. 为了保证系统对于安全期望跟踪信号的跟踪性能, 将预设性能函数与边界保 护算法进行结合, 并对跟踪误差进行转换. 针对系统的输入饱和现象, 使用Sigmoid函数进行逼近; 同时, 针对饱和函 数的逼近误差与未知外部干扰构成的复合干扰, 采用参数自适应方法对其上界进行逼近. 然后, 结合反步控制方法 设计了安全跟踪控制器, 并通过Lyapunov稳定性理论证明了闭环系统所有信号的收敛性, 保证了无人直升机的安全 跟踪性能. 最终, 通过数值仿真验证了所提控制方法的有效性.     

Robust control scheme for uncertain semi-Markov jump systems subject to digital communication constraint and incomplete sojourn-time information

This paper deals with the robust control problem for networked uncertain semi-Markov jump systems over digital communication channel, where some complicated factors are considered in this framework, such as false data injection attacks, incomplete sojourn-time information, and actuator fault. In network environment, these problems frequently occurred: (1) Data must be quantified before it is transmitted via digital communication channels, and (2) there is always the risk of cyber-attack. Traditional controllers are not effective to solve the robust control design issue of uncertain semi-Markov jump systems since the signal quantization and cyber-attack will degrade control performance evidently. Then, a resilient controller is designed to guarantee the stable running of system with incomplete sojourn-time information and the system resiliency to unsecure shared data. With the help of Lyapunov stability theory, sufficient conditions are derived in the form of linear matrix inequality, which can determine the gains of the resilient controller. Finally, the simulation examples about single-machine infinite-bus power system are given to explain the effectiveness and feasibility of the proposed control approach.     

Tracking control for sampled‐data systems with uncertain time‐varying sampling intervals and delays

In this paper, a solution to the approximate tracking problem of sampled‐data systems with uncertain, time‐varying sampling intervals and delays is presented. Such time‐varying sampling intervals and delays can typically occur in the field of networked control systems. The uncertain, time‐varying sampling and network delays cause inexact feedforward, which induces a perturbation on the tracking error dynamics, for which a model is presented in this paper. Sufficient conditions for the input‐to‐state stability (ISS) of the tracking error dynamics with respect to this perturbation are given. Hereto, two analysis approaches are developed: a discrete‐time approach and an approach in terms of delay impulsive differential equations. These ISS results provide bounds on the steady‐state tracking error as a function of the plant properties, the control design and the network properties. Moreover, it is shown that feedforward preview can significantly improve the tracking performance and an online extremum seeking (nonlinear programming) algorithm is proposed to online estimate the optimal preview time. The results are illustrated on a mechanical motion control example showing the effectiveness of the proposed strategy and providing insight into the differences and commonalities between the two analysis approaches. Copyright © 2009 John Wiley & Sons, Ltd.     

Global output feedback control for nonlinear cascade systems with unknown output functions and unknown control directions

This paper investigates the output feedback control for the uncertain nonlinear system with the integral input‐to‐state stable (iISS) cascade subsystem, which allow not only the unknown control direction but also the unknown output function. The unknown output function only needs to have a generalized derivative (which may not be derivable), and the upper and lower bounds of the generalized derivative need not to be known. To deal with the challenge raised by the unknown output function and the unknown control direction, we choose a special Nussbaum function with a faster growth rate to ensure the integrability for the derivative of the selected Lyapunov function. Then, a dynamic output feedback controller is designed to drive the system states to the origin while keeping the boundedness for all other closed‐loop signals. Moreover, via some appropriate transformations, the proposed control scheme is extended to deal with more general uncertain nonlinear cascade systems with quantized input signals. Finally, two simulation examples are given to show the effectiveness of the control scheme.     

Improved prescribed performance control for nonlinear systems with unknown control direction and input dead-zone

In view of the input dead-zone, unknown control direction and difficulty in satisfying the prescribed performance that suffered in practical systems, an improved prescribed performance-based adaptive control scheme is stressed for uncertain nonlinear systems in this paper. Firstly, by adopting a characteristic function, the input dead-zone is linearized to a model with bounded perturbation. To settle the “computation complexity” issue, an adaptive controller is built via command filter design method, where the fuzzy logic systems are introduced to approximate the unknown nonlinearities. Meanwhile, the Nussbaum function is brought in controller design to counter the hardship of unknown control direction. Besides, the tracking error can be restricted in the prescribed boundary in finite time with the improved performance function. The presented control approach can not only ensure the finite-time convergence property of tracking error and the boundedness of all signals in the closed-loop system, but also easily implement in engineering. Finally, the simulation examples confirm the validity of the designed control scheme.     

Mitigating information asymmetry to acquire venture capital financing for digital startups in China: The role of weak and strong signals

This paper addresses how weak and strong signals affect venture capital funding acquired by digital startups at their early stage in various industries of China. We also articulate the interaction mechanism of these strong and weak signals by demonstrating their complementary or substitutive effects in alleviating information asymmetry on startup quality, which can help digital startups secure venture capital financing. Drawing on signalling theory and institutional legitimacy theory, we introduce application (app) downloads as a novel strong signal that can reduce market legitimacy concerns, and previous-round venture capitalist reputation as a traditional strong signal that mitigates regulatory legitimacy concerns. We treat founders' startup and IT experience as weak signals, as they provide rhetorical and indirect information indicating a startup's potential to establish regulatory and market legitimacy. The study empirically investigates our hypotheses using data of 163 digital startups in various industries of China. Results confirm the positive relationships between strong signals and venture capital funding secured by a digital startup. Furthermore, signals of similar strength are found to complement each other's effects in certain situations, while strong signals can reduce the effects of weak signals on a digital startup's financing performance under specific conditions that create these mixed effects. Implications for digital startup research and practice as well as limitations and suggestions for future research are discussed.     

商用航空发动机生产管控的数字孪生模式探索

【】针对商用航空发动机研制时间周期长、复杂程度高的特点,面向型号研制阶段需求,及规模化批量生产转型的潜在需求,以知识可重用、适航规范质量管理为基础,研究基于数字孪生的生产管控模式,从生产管控的质量、设备、计划、物流等环节,明确物理与信息系统映射模型框架,通过物理环节与信息系统的连接和交互,为型号研制提供更加实时、高效的服务,为规模化批量生产构建生产管理、现场组织技术架构。     

Robust approximation-free prescribed performance control for nonlinear systems and its application

This paper presents a robust prescribed performance control approach and its application to nonlinear tail-controlled missile systems with unknown dynamics and uncertainties. The idea of prescribed performance function (PPF) is incorporated into the control design, such that both the steady-state and transient control performance can be strictly guaranteed. Unlike conventional PPF-based control methods, we further tailor a recently proposed systematic control design procedure (i.e. approximation-free control) using the transformed tracking error dynamics, which provides a proportional-like control action. Hence, the function approximators (e.g. neural networks, fuzzy systems) that are widely used to address the unknown nonlinearities in the nonlinear control designs are not needed. The proposed control design leads to a robust yet simplified function approximation-free control for nonlinear systems. The closed-loop system stability and the control error convergence are all rigorously proved. Finally, comparative simulations are conducted based on nonlinear missile systems to validate the improved response and the robustness of the proposed control method.     

Predicting secondary school teachers’ acceptance and use of a digital learning environment: A cross-sectional study

In this study, secondary school teachers’ acceptance of a digital learning environment (DLE) was investigated. Questionnaires were taken on three times (T1/T2/T3) during the same school year, with the Unified Theory of Acceptance and Use of Technology (UTAUT) as theoretical framework. Next to questionnaires, user-logs were collected during the entire school year. A total of 72 teachers completed a questionnaire on at least one occasion: 64 teachers responded at T1, 41 at T2, and 55 at T3. We first investigated which factors influence teachers’ acceptance of a DLE. The main predictors of DLE acceptance were performance expectancy and social influence by superiors to use the DLE. Effort expectancy and facilitating conditions were of minor importance. We then investigated how well the amount of final observed use could be predicted, and found that at T1 about one third, at T2 about one fourth and at T3 about half of the variance in observed use was predicted by attitude, behavioral intention and self-reported frequency of use. Our study showed that to maximize use of a DLE, its usefulness should be demonstrated, while school boards or principals should strongly encourage teachers to (start to) use the DLE.     

参考轨迹更新的点到点迭代学习控制算法优化及应用

针对受非重复扰动作用的离散线性系统的输出跟踪控制问题,提出一种基于参考轨迹更新的点到点迭代学习控制算法.首先通过构建性能指标函数对控制器进行范数优化,并给出相应的收敛性条件,使得系统输出能够跟踪上更新后参考轨迹处的期望点.其次,当系统输出端受到某批次非重复扰动的影响时,进一步通过引入拉格朗日乘子算法构造多目标性能指标函数,以优化鲁棒迭代学习控制器,达到提高收敛速度和跟踪精度的目的.最后将该算法应用于电机驱动的单机械臂控制系统中,仿真结果验证了算法的合理性和有效性.     

A distributed control system and its application to a board mill

A distributed microcomputer-based automation system, which has been applied to a new board mill is described. The automation system used was based on several independent data processing units with dedicated functions. The data processing units were interconnected with serial buses which used HDLC communication protocol. The operating stations were based on a colour visual display unit which made a new type of control room concept possible. The substations and the buses are backed up by standbys to ensure a sufficiently high availability as maintenance staff were unavailable outside normal working hours. The board mill where the system was applied for the first time called for special solutions, which made a digital distributed system the natural choice. A short account of the experience with the system is also given.     

Integrated fault estimation and fault‐tolerant control for stochastic systems with Brownian motions

This paper presents an integrated robust fault estimation and fault‐tolerant control technique for stochastic systems subjected to Brownian parameter perturbations. The augmented system approach, unknown input observer method, and optimization technique are integrated to achieve robust simultaneous estimates of the system states and the means of faults concerned. Meanwhile, a robust fault‐tolerant control strategy is developed by using actuator and sensor signal compensation techniques. Stochastic linear time‐invariant systems, stochastic systems with Lipschitz nonlinear constraint, and stochastic systems with quadratic inner‐bounded nonlinear constraint are respectively investigated, and the corresponding fault‐tolerant control algorithms are addressed. Finally, the effectiveness of the proposed fault‐tolerant control techniques is demonstrated via the drivetrain system of a 4.8 MW benchmark wind turbine, a 3‐tank system, and a numerical nonlinear model.     

基于LMI的约束系统H∞控制及其滚动优化实现

在LMI优化框架下,讨论有时域硬约束线性系统的H_∞控制问题.首先提出了一种基于LMI优化的状态反馈方法,并给出了闭环系统保证H_∞性能和满足时域硬约束的条件.在此基础上,融合预测控制的滚动优化原理讨论了一种滚动时域H_∞性能控制方法.通过对H_∞性能指标γ的在线最小化,闭环系统能实时协调控制性能要求和硬约束,并充分利用有限的控制能力提高控制性能.     

A mid-ranging control strategy for non-stationary processes and its application to dissolved oxygen control in a bioprocess

In this study a modified mid-ranging strategy is proposed where the controller for the secondary manipulated variable uses its own output as its setpoint, possibly with an offset and/or re-scaling. This modification allows the manipulated variables to increase in unison so that the mid-ranging advantage of utilizing the fast dynamics of the primary controller to regulate the process can be achieved also in non-stationary processes, while not adding complexity to the controller. The proposed control strategy has been implemented in pilot-scale (500 l) industrial bioprocesses where it is used to control the dissolved oxygen level by manipulating agitator speed and aeration rate. The controller is demonstrated to perform well in these, outperforming a reference controller which has previously been shown to give satisfactory control performance. It is also shown in similar experiments that the strategy can easily be adapted to control dissolved oxygen in bioprocesses where the feed rate is controlled using an extremum-seeking controller. The proposed strategy is generally applicable to non-stationary processes where a mid-ranging approach is suitable.     

A low‐complexity design for distributed containment control of networked pure‐feedback systems and its application to fault‐tolerant control

This paper addresses a low‐complexity distributed containment control problem and its extension to fault‐tolerant control for networked nonlinear pure‐feedback systems under a directed graph. The multiple dynamic leaders are neighbors of only a subset of the followers described by completely non‐affine multi‐input multi‐output pure‐feedback dynamics. It is assumed that all followers' nonlinearities are heterogeneous and unknown. The proposed containment controller is implemented by using only error surfaces integrated by performance bounding functions and does not require any differential equations for compensating uncertainties and faults. Thus, compared with the previous containment control approaches for multi‐agent systems with unknown non‐affine nonlinearities, the distributed containment control structure is simplified. In addition, it is shown that the proposed control scheme can be applied to the fault‐tolerant containment control problem in the presence of unexpected system and actuator faults, without reconstructing any control structure. It is shown from Lyapunov stability theorem that all followers nearly converge to the dynamic convex hull spanned by the dynamic leaders and the containment control errors are preserved within certain given predefined bounds. Copyright © 2016 John Wiley & Sons, Ltd.