917 resultados para terminal sliding mode control systems


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Professor Norman Macintosh has long been a leading, and at times a dissonant, voice in critical accounting studies, exhibiting an intellectual dexterity seldom encountered in the accounting academy. His work ranges from the application of traditional organizational theories within work organizations to poststructural renderings of capital market exigencies. Here, we consider and extend Professor Macintosh's work contemplating the morality embedded within, and propagated by, management accounting and control systems (macs). We begin with Macintosh (1995) employing structuration theory in investigating the ethics of profit manipulation within large, decentralized corporations. The work highlights the fundamental dialectical contradictions within these work organizations, demonstrates the indeterminacy of traditional ethical reasoning, and shows the extent to which macs provide legitimating underpinnings for management action. We propose to extend the conversation using the tools provided in Macintosh's subsequent work: a Levinasian ethic (Macintosh et al., 2009), and heteroglossic accounting (Macintosh, 2002)—both emerging from his poststructuralist predilections. A Levinasian perspective provides an ontologically grounded ethic, and heteroglossic accounting calls for multiple accountings representing alternative moral voices. A critical dialogic framework is proposed as a theoretic for imagining heteroglossic accounting that takes pluralism seriously by recognizing the reality of irresolvable differences and asymmetric power relationships associated with assorted moral perspectives.

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This paper reports a case study conducted in Quinta da Aveleda, one of
the three largest Portuguese wine companies. Our aim was to explore the
relationship established between a newly implemented Balanced Scorecard
(BSC) and the elements of the Management Control System (MCS) in the
organization. Thus, two specific objectives were pursued. Firstly, to identify
the influences (barriers, opportunities) of the existing MCS on the implementation
of the BSC. Secondly, to identify the impacts the BSC implementation
was able to exert on the configuration of the organization’s MCS.
We found that the budgeting process, the planning system, the information
infrastructure, and the organizational structure and culture were the elements
of the previous MCS that influenced the BSC implementation process.
Eventually, the BSC implementation led to important changes in the budgeting,
planning, reporting systems and processes. In order to explain these
findings, we briefly explored the main issues and factors accounting for the
scope and nature of the BSC’s impacts on Quinta da Aveleda. These issues
and factors were the mobilized organizational resources, the implementation
approach, the communication, and the organizational support.

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In this short paper, we present an integrated approach to detecting and mitigating cyber-attacks to modern interconnected industrial control systems. One of the primary goals of this approach is that it is cost effective, and thus whenever possible it builds on open-source security technologies and open standards, which are complemented with novel security solutions that address the specific challenges of securing critical infrastructures.

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The IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003) was organized under the auspices of the recently founded IFAC Technical Committee on Cognition and Control, and it was the first IFAC event specifically devoted to this theme. Recognizing the importance of soft-computing techniques for fields covered by other IFAC Technical Committees, ICONS 2003 was a multi-track Conference, co-sponsored by four additional Technical Committees: Computers for Control, Optimal Control, Control in Agriculture, and Modelling, Identification and Signal Processing. The Portuguese Society for Automatic Control (APCA) hosted ICONS 2003, which was held at the University of Algarve, Faro, Portugal.

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Multilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large field of applications. In control and signal processing applications, MLPs are mainly used as nonlinear mapping approximators. The most common training algorithm used with MLPs is the error back-propagation (BP) alg. (1).