Model matching inclusion for input/state asynchronous sequential machines with constraint on the length of control input sequences

In this paper, the model matching inclusion problem for input/state asynchronous sequential machines (ASMs) is studied in the framework of corrective control. The considered ASM receives the external input with various frequencies which hinder full use of inherent reachability of the machine. We elucidate the existence condition and design procedure for a state feedback corrective controller that makes the closed-loop system have the largest behavior contained by a given reference model. To demonstrate the practicality of the proposed control scheme, experimental studies on an asynchronous error detection and correction (EDAC) module are conducted by implementing the controller and machine on the field-programmable gate array (FPGA) system.     

Distributed fault-tolerant output regulation for heterogeneous linear multi-agent systems under actuator faults

This study investigates the distributed fault-tolerant output regulation for heterogeneous linear multi-agent systems in the presence of actuator faults. For the systems which are not the neighbors of exosystem, the distributed fixed-time observer is put forward to observe the state of exosystem. Note that it is dependent on the global information of network topology. To address this issue, the fully distributed adaptive fixed-time observer is further proposed. It can estimate not only the state of exosystem, but also the system matrix of exosystem. Based on the proposed observer, a novel fault-tolerant controller is developed to compensate for actuator faults. Moreover, it is proven that the proposed controller is effective to address the fault-tolerant output regulation problem by the Lyapunov stability theory. Finally, two illustrative examples are given to illustrate the feasibility of the main theoretical findings.     

Robust finite-time cooperative formation control of UGV-UAV with model uncertainties and actuator faults

This paper investigates the finite-time cooperative formation control problem for a heterogeneous system consisting of an unmanned ground vehicle (UGV) - the leader and an unmanned aerial vehicle (UAV) - the follower. The UAV system under consideration is subject to modeling uncertainties, external disturbance as well as actuator faults simultaneously, which is associated with aerodynamic and gyroscopic effects, payload mass, and other external forces. First, a backstepping controller is developed to stabilize the leader system to track the desired trajectory. Second, a robust nonsingular fast terminal sliding mode surface is designed for UAV and finite-time position control is achieved using terminal sliding mode technique, which ensures the formation error converges to zero in finite time in the presence of actuator faults and other uncertainties. Furthermore, by combining the radial basis function neural networks (NNs) with adaptive virtual parameter technology, a novel NN-based adaptive nonsingular fast terminal sliding formation controller (NN-ANFTSMFC) is developed. By means of the proposed adaptive control strategy, both uncertainties and actuator faults can be compensated without the prior knowledges of the uncertainty bounds and fault information. By using the proposed control schemes, larger actuator faults can be tolerated while eliminating control chattering. In order to realize fast coordinated formation, the expected position trajectory of UAV is composed of the leader position information and the desired relative distance with UGV, based on local distributed theory, in the three-dimensional space. The tracking and formation controllers are proved to be stable by the Lyapunov theory and the simulation results demonstrate the effectiveness of proposed algorithms.     

Robust stability analysis of formation control in local frames under time-varying delays and actuator faults

This paper investigates the robust stability of a multiagent system moving to a desired rigid formation in presence of unknown time-varying communication delays and actuator faults. Each agent uses relative position measurements to implement the proposed control method, which does not require common coordinate references. However, the presence of time delays in the measurements, which is inherent to the communication links between agents, has a negative impact in the control system performance leading, in some cases, to instability. Furthermore, the robust stability analysis becomes more complex if failures on actuators are taken into account. In addition, delays may be subject to time variations, depending on network load, availability of communication resources, dynamic routing protocols, or other environmental conditions. To cope with these problems, a sufficient condition based on Linear Matrix Inequalities (LMI) is provided to ensure the robust asymptotic convergence of the agents to the desired formation. This condition is valid for any arbitrarily fast time-varying delays and actuator faults, given a worst-case point-to-point delay. Finally, simulation results show the performance of the proposed approach.     

Robust cooperative output regulation of heterogeneous uncertain linear multi-agent systems by intermittent communication

In this paper, we study the robust cooperative output regulation problem of heterogeneous linear multi-agent systems with system uncertainties and directed communication topology. A robust distributed event-triggered control scheme is proposed based on the internal model principle. To avoid continuous monitoring of measurement errors for the event-triggering condition, a novel self-triggered control scheme is further proposed. Moreover, by introducing a fixed timer in the triggering mechanisms, Zeno behavior can be excluded for each agent. An example is finally provided to demonstrate the effectiveness of the proposed self-triggered control scheme.     

Robust quantized consensus of discrete multi-agent systems under input saturation

In this paper, we consider the quantized consensus problem of multiple discrete-time integrator agents which suffer from input saturation. As agents transmit state information through communication networks with limited bandwidth, the states of agents have to be quantized into a finite number of bits before transmission. To handle this quantized consensus problem, we introduce an internal time-varying saturation function into the controllers of all agents and ensure that the range of the state of each agent can be known in advance by its neighboring agents. Based on such shared state range information, we construct a quantized consensus protocol which implements a finite-bit quantization strategy to all states of agents and can guarantee the achievement of the asymptotic consensus under any given input saturation threshold. Such desired consensus can be guaranteed at as low bit rate as 1 bit per time step for each agent. Moreover, we can place an upper bound on the convergence rate of the consensus error of agents. We further improve that quantized consensus protocol to a robust version whose parameters are determined with only an upper bound on the number of agents and does not require any more global information of the inter-agent network. Simulations are done to confirm the effectiveness of our quantized consensus protocols.     

Leader-following consensus of multi-agent systems with connectivity-mixed attacks and actuator/sensor faults

This study investigates the leader-following consensus issue of multi-agent systems subject to simultaneous connectivity-mixed attacks, actuator/sensor faults and disturbances. Connectivity-mixed attacks are remodeled into connectivity-maintained and connectivity-paralyzed topologies in a switched version, and actuator/sensor faults are established with unified incipient-type and abrupt-type characteristics. Then, unknown input observer-based decoupling and estimation are incorporated to achieve unknown state and fault observations with the normalized technique, and the leader-following consensus-based compensation to faults, resilience to attacks and robustness to disturbances are also realized with the neighboring output information and sensor fault estimation through the distributed framework. Criteria of achieving exponential leader-following consensus of multi-agent systems under cyber-physical threats are derived with dual attack frequency and activation rate indicators. Simulation example is conducted to exemplify the validation and merits of the proposed leader-following consensus algorithm.     

Stability and L2-gain analysis of switched input delay systems with unstable modes under asynchronous switching

We consider the stability and L₂-gain analysis problem for a class of switched linear systems. We study the effects of the presences of input delay and switched delay in the feedback channels of the switched linear systems with an external disturbance. By contrast with the most of the contributions available in literatures, we do not require that all the modes of the switched system are stable when input delay appears in the feedback input. By reaching a compromise among the matched-stable period, the matched-unstable period, and the unmatched period and permitting the increasing of the multiple Lyapunov functionals on all the switching times, the solvable conditions of exponential stability and weighted L₂-gain are developed for the switched system under mode-dependent average dwell time scheme (MDADT). Finally, numerical examples are given to illustrate the effectiveness of the proposed theory.     

Adaptive leaderless consensus control of a class of strict feedback nonlinear systems with guaranteed transient performance under actuator faults

The problem of adaptive leaderless consensus control of a class of uncertain strict feedback nonlinear systems with guaranteed transient performance is investigated in this paper. The system model is a class of strict feedback nonlinear systems with parametric uncertainty, actuator fault and external disturbance. How to guarantee the transient performance of consensus error is involved. To solve this problem, the consensus is transmitted into stabilization of a new variable. Ultimately the consensus errors will asymptotically converge to zero and faster than a given exponentially converging variable. Finally, simulation results show the effectiveness of proposed control scheme.     

高校人文社科投入与产出互动关系研究—基于PVAR模型的估计

本文首先采用TOPSIS对科技产出进行评价,得到唯一的产出变量,然后采用面板数据、面板向量自回归模型分析科技投入与产出的互动关系。结果表明,中国高校人文社科研究投入产出的互动关系效应比较明显,形成良性正反馈效应。科研经费、研发人员全时当量与与科研产出之间存在双向格兰杰因果关系。科研人员数是科研产出的格兰杰原因,而科研产出只在滞后1期的情况下,才是科研人员数的格兰杰原因。无论是脉冲响应函数,还是方差分解,各变量除自身外,都是科研产出的影响最大,说明了科研产出对科技投入存在较大的互动作用。对科技产出贡献最大的是科技人员数量,其次是研发人员全时当量,最后是科研经费,最后对原因进行了分析。     

Robust simultaneous fault detection and control for a class of nonlinear stochastic switched delay systems under asynchronous switching

This paper concerns the simultaneous fault detection and control (SFDC) problem for a class of nonlinear stochastic switched systems with time-varying state delay and parameter uncertainties. The switching signal of detector/controller unit (DCU) is assumed to be with switching delay, which results in the asynchronous switching between the subsystems and DCU. By constructing a switching strategy depending on the state and switching delays, new sufficient conditions expressed by a set of linear matrix inequalities (LMIs) is derived to design DCU gains. This problem is formulated as an H_∞ optimization problem and both mean square exponential stability and fault detection of augmented system are considered. A numerical example is finally exploited to verify the effectiveness and potential of the achieved scheme.     

基于C~2GS~2模型的企业科技投入产出绩效评价研究

试图运用系统运筹学的思想,选择合适的科技投入绩效评价指标,建立C2GS2评价模型,提出一种企业科技投入产出评价的新方法.     

新发展理念下北京市创新主体投入结构产出效率动态分析

本文运用BCC模型对2005-2016年间北京市企业、高校、科研机构的专利产出效率进行测算和评价,并构建出同时包含企业、高校与科研机构在内的虚拟变量模型对三者的专利产出效率差异性进行了稳健性分析,然后通过DEA-malquist指数方法将三者的效率分别进行分解,探究其效率的动态变化情况及原因,最后利用灰色关联分析模型探究这三大创新主体各自的内部投入结构对专利产出效率的影响。研究结果表明综合专利产出效率从高至低依次为企业、高校、科研机构。企业、高校与科研机构的效率总体上均在逐年提高,但企业R&D效率的提高主要来自于技术进步,高校与科研机构的效率提高是技术进步效应和规模效率降低的复合作用效果。三者各自的内部投入结构的专利产出效应存在较大的差异。对此,对三大主体创新效率的提高,从动态优化的角度提出了政策建议。     

基于DEA模型的科技金融投入产出相对效率分析——以广东省为例

科技金融是实现广东省创新驱动发展,自主创新能力提升的重要引擎。在建立科技金融投入产出效率评价指标体系的基础上,采用数据包络分析法,首先将2014年广东省的科技金融结合效率同全国其他省市对比,进行初步评价;然后对2000—2014年广东省自身科技金融结合效率作进一步研究,挖掘其存在的问题。研究结果表明,一味地扩大金融投入并不能有效提高科技产出,深化管理体制改革,推进市场化进程,优化科技金融内部结构才能实现科技金融的协调发展。