Asymptotic and interval observer for quality monitoring in drinking water distribution systems is derived in this paper. It produces robust interval bounds on the estimated state variables of the water quality. Solvin...
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Asymptotic and interval observer for quality monitoring in drinking water distribution systems is derived in this paper. It produces robust interval bounds on the estimated state variables of the water quality. Solving two differential equations generates the bounds; hence the numerical efficiency is sufficient for on-line monitoring of the water quality. The observer is applied to example water network and tight bounds-estimates are obtained.
In this paper, we propose a new iterative learning control(ILC) scheme, which is devoted to dealing with unknown parameters that are both time varying and iteration *** particular, we consider iteration-varying parame...
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In this paper, we propose a new iterative learning control(ILC) scheme, which is devoted to dealing with unknown parameters that are both time varying and iteration *** particular, we consider iteration-varying parameters that are generated by a second-order internal model. By incorporating the internal model into the parametric learning law, the ILC scheme can handle more generic nonlinear systems and more generic parametric uncertainties, comparing with existing ILC schemes that are first order in essence. We further explore the conditions under which the new ILC scheme can guarantee learning convergence. Utilizing the information of previous two iterations and the method of composite energy function(CEF),we are able to derive pointwise convergence along the time axis and asymptotic convergence along the iteration axis.
In order to successfully perform object manipulation, humanoid robots must be equipped with tactile sensors. However, the limited space that is available in robotic fingers imposes severe design constraints. In we pre...
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In order to successfully perform object manipulation, humanoid robots must be equipped with tactile sensors. However, the limited space that is available in robotic fingers imposes severe design constraints. In we presented a small prototype fingertip which incorporates a capacitive pressure system. This paper shows an improved version, which has been integrated on the hand of the humanoid robot iCub. The fingertip is 14.5 mm long and 13 mm wide. The capacitive pressure sensor system has 12 sensitive zones and includes the electronics to send the 12 measurements over a serial bus with only 4 wires. Each synthetic fingertip is shaped approximately like a human fingertip. Furthermore, an integral part of the capacitive sensor is soft silicone foam, and therefore the fingertip is compliant. We describe the structure of the fingertip, their integration on the humanoid robot iCub and present test results to show the characteristics of the sensor.
The CAN protocol was originally introduced for distributed automotive applications in the 1980s, and is still widely used by the industry today. CAN provides the basis for many cost-effective distributed systems, and ...
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The CAN protocol was originally introduced for distributed automotive applications in the 1980s, and is still widely used by the industry today. CAN provides the basis for many cost-effective distributed systems, and since its first inception has proved to be a continuous area of research. One major drawback that can severely limit the applicability of CAN in data-intensive real-time applications is related to the wired-AND nature of the physical layer that is used to manage message arbitration; a side effect of this is that it acts to severely limit both the maximum transmission speed and bus length of a given CAN network. This paper is concerned with over-clocking a CAN network to improve the data rate and information throughput, whilst simultaneously maintaining the priority-driven arbitration mechanism that is a major beneficial feature of the protocol. The paper will first describe briefly an already existing implementation of an overclocked CAN-controller done by the authors in a previous work. The paper then presents an analysis as to its expected performance in real-time applications. Specifically, the paper discusses the calculation of message transmission times, investigates the effects of the technique on message transmission jitter, and potential effects on the expected bit error rate.
Multivariable time delay processes are difficult to control due to the input-output interactions, as well as multiple time delays that complicate the controller design process. The proposed method presented in this pa...
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Multivariable time delay processes are difficult to control due to the input-output interactions, as well as multiple time delays that complicate the controller design process. The proposed method presented in this paper consists of a dynamic decoupling strategy - compared to the more general used steady state decoupling techniques - and a delay time compensation (DTC) structure in which the controller is designed based on the Extended Prediction Self Adaptive control (EPSAC) approach. The main concern regarding the proposed method is directed towards the possible lack of robustness against time delay variations - a problem that is frequently encountered in DTC structures. Moreover, the decoupling technique implemented consists in adding supplementary time delay to some input channels of the MIMO process, which may result in a worsening of the robustness problems. The simulations presented show that the proposed method can ensure robust stability and robust performance even for significant time delay variations.
Service-Oriented Architecture (SOA) has attracted substantial research effort over the past decade. In service-based systems, where multiple services providing the same functionality are available, it is necessary to ...
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Service-Oriented Architecture (SOA) has attracted substantial research effort over the past decade. In service-based systems, where multiple services providing the same functionality are available, it is necessary to select the appropriate services to be used in service composition to provide better quality of service (QoS) for service consumers. In order to select the best service composition for concurrent service requests, we present an adaptive control strategy which performs service selection based on the historical usage information of all the candidate services. A case study of a data stream management system is presented to validate the effectiveness of the adaptive control strategy, and examine the effect of the concurrency level on the process of the strategy's decision.
Predictive techniques based on neural networks are investigated in an adaptive structure for on-line control of a process exhibiting nonlinearities and typical disturbances. The method proposed consists of a novel ide...
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Predictive techniques based on neural networks are investigated in an adaptive structure for on-line control of a process exhibiting nonlinearities and typical disturbances. The method proposed consists of a novel identification technique based on extended memory adaptation (BMA) and an efficient implementation of the predictive control based on a nonlinear programming method. A forced circulation evaporator was chosen as a realistic nonlinear case study for the techniques discussed in the paper.
controlsystems behavior can be analyzed taking into account a large number of parameters: Performances, reliability, availability, security. Each control system presents various security vulnerabilities that affect i...
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We study the distributed average consensus problem in multi-agent systems with directed communication links that are subject to quantized information flow. The goal of distributed average consensus is for the agents, ...
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We study the distributed average consensus problem in multi-agent systems with directed communication links that are subject to quantized information flow. The goal of distributed average consensus is for the agents, each associated with some initial value, to obtain the average (or some value close to the average) of these initial values. In this paper, we present and analyze a distributed averaging algorithm which operates exclusively with quantized values (specifically, the information stored, processed and exchanged between neighboring agents is subject to deterministic uniform quantization) and relies on event-driven updates (e.g., to reduce energy consumption, communication bandwidth, network congestion, and/or processor usage). We characterize the properties of the proposed distributed averaging protocol and show that its execution, on any time-invariant and strongly connected digraph, will allow all agents to reach, in finite time, a common consensus value that is equal to the quantized average. We conclude with comparisons against existing quantized average consensus algorithms that illustrate the performance and potential advantages of the proposed algorithm.
In this paper, we present a novel decision-making framework to characterize the communication status of a distributed multi-agent system. The theoretical package dropout probability (PDP) in communication is formulate...
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