基于变结构思想的OGY同步控制器

为扩展混沌控制方法在混沌同步中的应用, 设计了一种基于变结构思想的Ott-Grebogi-Yorke(OGY)同步控制器. 基于变结构控制的思想, 将OGY混沌控制方法进行了扩展, 通过误差系统近似的线性模型寻找合适的稳定流形, 进而通过变结构控制器将误差系统的轨迹控制到稳定流形上面, 实现混沌系统的同步. 这种变结构控制策略使得OGY方法可以应用到混沌同步当中. H′enon映射的仿真结果验证了该控制策略的有效性.     

A test for stability robustness of linear time‐varying systems utilizing the linear time‐invariant ν‐gap metric

A stability robustness test is developed for internally stable, nominal, linear time‐invariant (LTI) feedback systems subject to structured, linear time‐varying uncertainty. There exists (in the literature) a necessary and sufficient structured small gain condition that determines robust stability in such cases. In this paper, the structured small gain theorem is utilized to formulate a (sufficient) stability robustness condition in a scaled LTI ν‐gap metric framework. The scaled LTI ν‐gap metric stability condition is shown to be computable via linear matrix inequality techniques, similar to the structured small gain condition. Apart from a comparison with a generalized robust stability margin as the final part of the stability test, however, the solution algorithm implemented to test the scaled LTI ν‐gap metric stability robustness condition is shown to be independent of knowledge about the controller transfer function (as opposed to the LMI feasibility problem associated with the scaled small gain condition which is dependent on knowledge about the controller). Thus, given a nominal plant and a structured uncertainty set, the stability robustness condition presented in this paper provides a single constraint on a controller (in terms of a large enough generalized robust stability margin) that (sufficiently) guarantees to stabilize all plants in the uncertainty set. Copyright © 2008 John Wiley & Sons, Ltd.     

Transparent autonomization in CORBA

Increasingly, software systems are constructed by integrating and composing multiple existing applications. The resulting complexity increases the need for self-management of the system. However, adding autonomic behavior to composite systems is difficult, especially when the constituent components are heterogeneous and they were not originally designed to support such interactions. Moreover, entangling the code for self-management with the code for the business logic of the original applications may actually increase the complexity of the systems, counter to the desired goal. In this paper, we address autonomization of composite systems that use CORBA, one of the first widely used middleware platforms introduced more than 17 years ago that is still commonly used in numerous systems. We propose a model, called Adaptive CORBA Template (ACT), that enables autonomic behavior to be added to CORBA applications automatically and transparently, that is, without requiring any modifications to the code implementing the business logic of the original applications. To do so, ACT uses “generic” interceptors, which are added to CORBA applications at startup time and enable autonomic behavior to be introduced later at runtime. We have developed ACT/J, a prototype of ACT in Java. We describe a case study in which ACT/J is used to introduce three types of autonomic behavior (self-healing, self-optimization, and self-configuration) to a distributed surveillance application.     

Multicriteria decisions on interdependent infrastructure transportation projects using an evolutionary-based framework

When evaluating transportation infrastructure projects and determining which of them will be carried out from a set of projects and given a budget constraint, several criteria need to be considered in the decision. Standard evaluation practices imply the aggregation of impacts into one utility function which is later optimized. Nevertheless these techniques used for translation of different measuring units into monetary terms are highly controversial. Multicriteria techniques can explicitly deal with different measuring units, however, they are not suitable to model interdependence relationships of projects that share a common characteristic (same route, location or target population, for instance). In this research we model this transportation planning problem, the multi-objective transportation infrastructure project selection problem (MTIPSP), as a constrained multi-objective optimization problem with quadratic objective functions, using a variation of the multi-objective 0–1 knapsack problem plus some additional constraints. Given the combinatorial nature of the problem, an evolutionary-based framework is used for the identification of Pareto solutions, and later, those with non-attractive properties are filtered using a Knee Identification Procedure. The final selection of the projects portfolio is made using a well known multicriteria decision aid method and including the decision makers’ preferences based on the existing context.     

NCTUns tool for wireless vehicular communication network researches

Several goals such as improving road safety and increasing transport efficiency are being pursued in intelligent transportation systems (ITS). Wireless vehicular communication is one technology to achieve these goals. Conducting vehicular experiments on the roads is an approach to studying the effectiveness of wireless vehicular communication. However, such an approach is costly, hard-to-control (repeat), dangerous, and infeasible when many vehicles and people are involved in the field trial. In contrast, the simulation approach does not have these problems. It is a very useful approach and complements the field trial approach. This paper presents NCTUns, an open source integrated simulation platform, for wireless vehicular communication network researches. This tool tightly integrates network and traffic simulations and provides a fast feedback loop between them. Therefore, a simulated vehicle can quickly change its driving behavior such as moving speed and direction when it receives a message from the wireless vehicular communication network. This capability is required by several novel ITS applications such as active collision avoidance systems. In this paper, we present the design, implementation, validation, and performance of this tool.     

Linear quadratic gaussian optimization approach for signal-to-noise ratio constrained control over network

The research area of control over networks has attracted great interest in recent years. Inserted in this research area is the study of control feedback limitations imposed by the presence of a communication channel. In this paper we analyze the fundamental limitations in control feedback stabilizability imposed by a class of Signal-to-Noise Ratio (SNR) constrained communication channels. We solve the SNR constrained control over network problem as a linear quadratic Gaussian (LQG) optimization with loop transfer recovery (LTR). If the communication channel is located on the feedback path then the LTR is said to be performed at the output. Vice versa, if the communication channel is on the control path, then the recovery is said to be performed at the input. In the present paper we address both cases, namely the LQG optimization with LTR at the output and the LQG optimization with LTR at the input to solve an LTI SNR constrained problem. We then explore the link between these two solutions.     

Multisensor switching control strategy with fault tolerance guarantees

In this paper we propose a novel fault tolerant multisensor switching strategy for feedback control. Each sensor of the proposed multisensor scheme has an associated state estimator which, together with a state feedback gain, is able to individually stabilise the closed-loop system. At each instant of time, the switching strategy selects the sensor-estimator pair that provides the best closed-loop performance, as measured by a control-performance criterion. We establish closed-loop stability of the resulting switching scheme under normal (fault-free) operating conditions. More importantly, we show that closed-loop stability is preserved in the presence of faulty sensors if a set of conditions on the system parameters (such as bounds on the sensor noises, maximum and minimum values of the reference signal, etc.) is satisfied. This result enhances and broadens the applicability of the proposed multisensor scheme since it provides guaranteed properties such as fault tolerance and robust closed-loop stability under sensor fault. The results are applied to the problem of automotive longitudinal control.     

Analysis of light propagation characteristic in the aero-optic flow field of cone-headed vehicle with side window

Aero-optic imaging deviation research is carried out for infrared-guided vehicle with cone-head side window, with a focus on the propagation characteristics of light in an aero-optic flow field. When the light entering the aero-optic flow field from the free-stream should be close to the normal, numerous data indicate that the light is refracted away from the normal. This paper divides the aero-optic flow field into two parts and uses the gas density distribution in the aero-optic flow field to ...     

A stick-slip piezoelectric actuator with an integrated sensing unit for the measurement and active control of the contact force

Output characteristics of the stick-slip piezoelectric actuators are intrinsically affected by the contact force between the driving foot and the mover. Therefore, it would be quite meaningful to measure and control the contact force. In this study, by integrating a group of strain gauges into the driving compliant mechanism, a stick-slip piezoelectric actuator with measured contact force was proposed. The main structural parameters of the driving compliant mechanism were designed and analyzed. Through experiments, the sensing unit was calibrated, and the results showed that it had good linearity, and the noise level was 3.5 mN. The contact force was measured by the sensing unit, and accordingly, the relationship between the contact force and the stepping characteristic was explored. It was shown that the change in contact force would lead to the evolution in stepping characteristic, which finally resulted in the motion nonlinearity of the actuator in large stroke output. Accordingly, by actively controlling the contact force, a method was proposed to tune the stepping characteristic. The comparative results demonstrated that this method could significantly improve the motion linearity of the actuator in large stroke output under various preloads and even very rough surface.     

Parameter identification and position control for helical hydraulic rotary actuators based on particle swarm optimization

It is difficult to obtain an accurate mathematical model in electro-hydraulic servo control system, due to the nonlinear factors such as dead zone, saturation, flow coefficient, and friction. Hence, a parameter identification algorithm, combining recursive least squares (RLS) with modified nonlinear particle swarm optimization (NPSO) algorithm, is proposed. On this basis, another improved NPSO algorithm is also put forward, aiming at searching for the optimal proportional–integral (PI) controller gain of the nonlinear hydraulic system while giving comprehensive consideration to the system performance indexes. The system identification experiments and position tracking control are conducted, respectively. As indicated by the comparison with the least squares (LS), RLS, PSO, and RLS–LPSO results, the proposed method shows higher identification and control accuracy.