The energetic structure of multi-body dynamic systems

Dynamic systems containing particles and rigid bodies capable of movement in two- or three-dimensions may be represented by equations of motion in several basic forms. In all cases geometric nonlinearities are involved and terms arise in the equations which are difficult to understand and interpret. The equations often conceal the basic structure of the dynamic model of the system since only combinations of parameters and combined effects of various constraints finally appear.In this paper the basic relations for the dynamic elements as well as the transformations among internal forces and velocities are depicted using bond graphs. The energetic structure of the system is thus exhibited in multiport form. This aids in the exploration of alternative equation formulation and in understanding of the assumptions involved in any particular equation set. Further, a bond graph model is easily coupled with nonmechanical dynamic models through force or motion generators.     

Consensus of second-order multi-agent systems with disturbances generated by nonlinear exosystems under switching topologies

In this paper, we consider the consensus of second-order multi-agent systems with exogenous disturbances generated by some nonlinear exosystems under switching topologies. Firstly, a dynamic gain technique based disturbance observer is proposed to estimate the disturbances generated by some nonlinear exosystems. Secondly, based on the proposed disturbance observer, consensus protocol is further proposed. A rigorous consensus analysis is performed. Finally, numerical simulation results are provided to show the effectiveness of the proposed results.     

Stability of switching linear systems with switching signals driven by stochastic processes

This paper presents conditions to assure the exponential stability in probability for autonomous switching linear systems. The switching signal acting on the autonomous system produces intervals that follow independent, identically distributed stochastic processes—the stability then follows by verifying simple-to-check linear matrix inequalities.     

B支持动态合作的分散型工作流系统/B

在合作项目或新产品的开发中,多个工作组共同合作完成一项工程并为共同合作提供工程所需要的专业技术、人力资源、数据等,整个合作过程可以被看作为一个动态的工作流,分散型合作工作流系统实现了动态工作流模型并有效地支持分布在不同地理位置上的多个工作组之间的合作,注册在不同主机上的工作组共同合作完成一项工程并通过HTTP协议进行通信。本文给出了一种新型的分散型工作流系统,通过本系统采用的网络地址查询方式,工作组之间可以快速高效地进行通信,每个工作组负责对其所要执行的工作任务进行合理分配,节约了人力资源,组内成员之间、组外成员之间的通信,确保了网络的安全。     

Multi-agent containment control with random link failures over dynamic cooperative networks

In this contribution, the containment control problem for a team of agents with discrete-time second-order dynamics over dynamic cooperative networks is discussed, where data from the controller to the actuator may be lost randomly and it is described by a random variable obeying Bernoulli distribution. A random-based distributed controller is designed by using the information from neighbors. Based on the hybrid tools of graph theory and nonnegative matrix, it is shown that the implementation of containment control is related to the dynamic cooperative networks and the successful rate of information transmission. Finally, a simulation is carried out to demonstrate the result in this paper.     

Further stability results for random nonlinear systems with stochastic impulses

In this paper, the global asymptotic stability in probability and the exponential stability in $m$th moment are investigated for random nonlinear systems with stochastic impulses, whose occurrence is determined by a Poisson process. The stochastic disturbances in the impulsive random nonlinear systems are driven by second-order processes, which have bounded mean power. Firstly, the improved Lyapunov approaches for the global asymptotic stability in probability and the exponential stability in $m$th moment are established for impulsive random nonlinear systems based on the uniformly asymptotically stable function. Secondly, the improved results are further extended to the impulsive random nonlinear systems with Markovian switching. Finally, two examples are provided to verify the feasibility and effectiveness of the obtained results.     

General synchronization criteria for nonlinear Markovian systems with random delays

It is well known that control of Markovian systems is a difficult problem. This paper considers synchronization control of Markovian coupled nonlinear systems with random delays. A new control scheme is proposed. Sufficient conditions in terms of linear matrix inequalities (LMIs) are obtained such that the coupled system can be asymptotically synchronized onto an isolated system. The synchronization criteria include classical mode-dependent and mode-independent results as special cases. The design method of the control gains is also given. Compared with mode-dependent and mode-independent control methods, our results are more practical and have lower conservatism, respectively. Numerical simulations are given to verify the effectiveness of the theoretical results.     

Networked feedback control for nonlinear systems with random varying delays

This paper discusses the controller synthesis problem of a nonlinear networked controlled system subject to delays in the measurement and actuation channels. The communication through the network also suffers non-stationary packet dropouts. The bounded nonlinearities in the plant state satisfy Lipschitz conditions. A Lyapunov function is developed for the closed-loop system considering dynamic output feedback and the resulting stabilization conditions are drawn in the form of linear matrix inequalities to ensure that the system is exponentially stable in the mean-square sense. The developed conditions are represented in the form of a convex optimization problem and the results are tested by simulation on a quadruple-tank process.     

Event-triggered controller design for positive T-S fuzzy systems with random time-delay

This paper is concerned with the design of event-triggered controller for positive Takagi-Sugeno (T-S) fuzzy systems with a random time-delay. The random time-delay is described as a Markov process. A controller switched at different event-triggered instant is proposed. By constructing a new event-triggered instant-dependent linear co-positive Lyapunov function, the design criteria of event-triggered controller is derived to ensure the positivity and stability of the closed-loop system. These criteria can be solved by linear programming (LP) technique. A positive lower bound on the inter-execution time is ensured, which means that there is Zeno-free phenomenon. Finally, the simulation has demonstrated the effectiveness and merit of the proposed results.     

需求函数为非线性的按订单生产企业动态定价的特性研究

按订单生产企业面对市场需求的变化,通常采用不同的策略来达到既定的目的。本文在需求函数为非线性的条件下,通过研究按订单生产企业动态定价模型,得出其定价的两个结论:在一定条件下,(1)价格是产量的增函数;(2)价格是剩余时间的增函数。     

An alternative data-driven fault detection scheme for dynamic processes with deterministic disturbances

This paper proposes an alternative fault detection (FD) scheme, in which the so-called residual signals are generated by means of a projection of process input data. This is the major difference to the existing model-based and data-driven FD schemes, where residual generator is realized based on the process input and output relationship/dynamics. Moreover, this way of residual generation avoids the parameter identification procedure and also allows us to address deterministic disturbances (unknown inputs), which be paid often less attention by data-driven FD methods. In this fashion, the FD issue reduces to detect change of a random matrix. Since it is difficult to directly measure this change, so the trace of a matrix is adopted as the evaluation function. Furthermore, the threshold can be set by considering the boundedness of disturbance. The effectiveness of the proposed method is verified by a simulation study on an inverted pendulum system.     

Resilient sampled-data control design for singular networked systems with random missing data

This paper proposes an active resilient control strategy for singular networked control systems with external disturbances and missing data scenario based on sampled-data scheme. To characterize the missing data scenario, a stochastic variable satisfying Bernoulli distributed white sequence is introduced. Based on this scenario, in this paper, two different models are proposed. For both the models, by using Lyapunov–Krasovskii functional approach, which fully uses the available information about the actual sampling pattern, some sufficient conditions in terms of linear matrix inequalities (LMIs) are separately obtained to guarantee that the resulting closed-loop system is admissible and strictly dissipative with a prescribed performance index. In particular, Jensen’s and Wirtinger based integral inequalities are employed to simplify the integral terms which appeared in the derivation of stabilization results. Then, if the obtained LMIs are feasible, the corresponding parameters of the designed resilient sampled-data controller are determined. Finally, two numerical examples are presented to demonstrate the effectiveness of the proposed control design technique.     

Iterative learning control for linear delay systems with deterministic and random impulses

This paper investigates convergence of iterative learning control for linear delay systems with deterministic and random impulses by virtute of the representation of solutions involving a concept of delayed exponential matrix. We address linear delay systems with deterministic impulses by designing a standard P-type learning law via rigorous mathematical analysis. Next, we extend to consider the tracking problem for delay systems with random impulses under randomly varying length circumstances by designing two modified learning laws. We present sufficient conditions for both deterministic and random impulse cases to guarantee the zero-error convergence of tracking error in the sense of Lebesgue-p norm and the expectation of Lebesgue-p norm of stochastic variable, respectively. Finally, numerical examples are given to verify the theoretical results.     

Distributed dynamic state estimation with parameter identification for large-scale systems

In this paper, we consider a distributed dynamic state estimation problem for time-varying systems. Based on the distributed maximum a posteriori (MAP) estimation algorithm proposed in our previous study, which studies the linear measurement models of each subsystem, and by weakening the constraint condition as that each time-varying subsystem is observable, this paper proves that the error covariances of state estimation and prediction obtained from the improved algorithm are respectively positive definite and have upper bounds, which verifies the feasibility of this algorithm. We also use new weighting functions and time-varying exponential smoothing method to ensure the robustness and improve the forecast accuracy of the distributed state estimation method. At last, an example is used to demonstrate the effectiveness of the proposed algorithm together with the parameter identification.     

Distributed bipartite consensus for multi-agent systems with dynamic event-triggered mechanism

This paper address the distributed bipartite consensus problem of multi-agent systems (MASs) under undirected and directed topologies with dynamic event-triggered (DET) mechanism. The relationship among agents not only collaborative interaction but also competitive interaction are taken into account. A novel DET control protocol is raised with internal dynamic variables to guarantee that each agent can reach the bipartite consensus. Compared with the existing static triggering laws, the introduced DET strategy can significantly enlarge the interval time between two triggering instants. In addition, continuous information transmission in either controller updating or between agent and its neighbors is not demanded, which implies that the communication frequency can be extremely decreased. It is also proven that Zeno behavior does not occur. Finally, two numerical examples verify the validity of the presented theoretical results.     

Continuous fixed-time convergent regulator for dynamic systems with unbounded disturbances

This paper presents a novel continuous fixed-time convergent control law for dynamic systems in the presence of unbounded disturbances. A continuous fixed-time convergent control is designed to drive all states of a multi-dimensional integrator chain at the origin for a finite pre-established (fixed) time, using a scalar input. The fixed-time convergence is established and the uniform upper bound of the settling time is computed. The designed control algorithm is applied to fixed-time stabilization of two mechatronic systems, a cart inverted pendulum and a single machine infinite bus turbo generator with main steam valve control.     

Reliable control for networked control systems with probabilistic actuator fault and random delays

In this paper, the reliable control design is considered for networked control systems (NCSs) against probabilistic actuator fault with different failure rates, measurements distortion, random network-induced delay and packet dropout. A new distribution-based fault model is proposed, which also contains the probability distribution information of the random delay and packet dropout. By using Lyapunov functional and new technique in dealing with time delay, stability and stabilization criteria are derived in terms of linear matrix inequalities. The provided numerical example and vertical takeoff and landing (VTOL) aircraft system illustrate that: firstly, using the distribution information of the delay, the maximum effective delay bound (MEDB) can be greatly improved, secondly, the proposed reliable controller can stabilize the NCSs with probabilistic actuator fault and measurements distortion, which may be unstable under the controller designed without considering the unreliable cases.     

Bond graph fluid line models for inclusion with dynamic systems simulations

A procedure is presented whereby the control volume equations for one-dimensional, compressible gas dynamics are cast into first-order, state variable form. These equations are interpreted using causal bond graphs. The resulting bond graph is shown to reduce to the classic I-C chain under acoustic constraints and to a more recently developed model of low speed thermal energy transport subject to associated constraints.Through example it is demonstrated that the control volume bond graph is easily coupled to an overall system model and thus can be digitally simulated as part of the overall nonlinear state space representation. The result is that a very accurate gas dynamic model can be coupled with an overall dynamic system model without requiring a prohibitively large number of equations.