The use of multiobjective optimization procedures for control tuning has been constantly explored, presenting satisfactory results, and generating significant contributions to control engineering. In this way, the fie...
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The use of multiobjective optimization procedures for control tuning has been constantly explored, presenting satisfactory results, and generating significant contributions to control engineering. In this way, the field of robust control can benefit significantly from the integration of multiobjective optimization design procedures for robust Proportional-Integral-Derivative (RPID) controller synthesis, enabling innovative solutions to complex control challenges. Due to this fact, this paper explores an approach to utilize multiobjective optimization algorithms in a simplified procedure, considering uncertain systems in the form of interval plants with uncertain poles, the Kharitonov theorem is used to obtain a region of stability as search space for the multiobjective algorithm, being the optimization process performed over a nominal system model. Two numerical cases and a flexible actuator model were used to demonstrate the procedure for RPI synthesis, resulting in robustly stable controllers with optimized performance over error and control signal effort measures.
The first open invited track in multi-objective optimisation for control systems was organised in 2017 with the idea of exchanging ideas and research about how those techniques are valuable for control engineers. Give...
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The first open invited track in multi-objective optimisation for control systems was organised in 2017 with the idea of exchanging ideas and research about how those techniques are valuable for control engineers. Given that control engineering problems are generally multi-objective problems, multi-objective optimisation offers an interesting approach via the simultaneous optimisation of all design objectives. Controller tuning is not except from this. In this paper we perform a review and analysis of the literature, limited to the IFAC environment, to appreciate and detect new tendencies in controller tuning applications via multi-objective optimisation. Time window under consideration is from 2015 to date, coinciding with a previous review on the topic, as well as the emigration of IFAC proceedings to Elsevier.
This article presents a system for tracking the position of objects within a smart home to support a robot assistant in pick-and-place tasks. The current system is capable of estimating the position of an object using...
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ISBN:
(纸本)9781479902255
This article presents a system for tracking the position of objects within a smart home to support a robot assistant in pick-and-place tasks. The current system is capable of estimating the position of an object using the signal strength received by a mobile device in a ZigBee sensor network. Received strength signal indication measurements were done in laboratory for applying a estimation method. Two models were utilized (a) log-distance path loss - model in which signal lost has a random influence with log-normal distribution, and (b) free space decay law - based on the decay law for a signal on a open space. Experiments with satisfactory results were done with a public dataset to benchmark our data.
Context: The technical debt (TD) concept describes a tradeoff between short-term and long-term goals in software development. While it is highly useful as a metaphor, it has utility beyond the facilitation of discussi...
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ISBN:
(纸本)9781450318488
Context: The technical debt (TD) concept describes a tradeoff between short-term and long-term goals in software development. While it is highly useful as a metaphor, it has utility beyond the facilitation of discussion, to inspire a useful set of methods and tools that support the identification, measurement, monitoring, management, and payment of TD. Objective: This study focuses on the identification of TD. We evaluate human elicitation of TD and compare it to automated identification. Method: We asked a development team to identify TD items in artifacts from a software project on which they were working. We provided the participants with a TD template and a short questionnaire. In addition, we also collected the output of three tools to automatically identify TD and compared it to the results of human elicitation. Results: There is little overlap between the TD reported by different developers, so aggregation, rather than consensus, is an appropriate way to combine TD reported by multiple developers. The tools used are especially useful for identifying defect debt but cannot help in identifying many other types of debt, so involving humans in the identification process is necessary. Conclusion: We have conducted a case study that focuses on the practical identification of TD, one area that could be facilitated by tools and techniques. It contributes to the TD landscape, which depicts an understanding of relationships between different types of debt and how they are best discovered. Copyright 2013 ACM.
In this work, is developing a method for obtaining the point of impact of a rocket by telemetry data and a Slant Range device. The trajectory data was obtained from a real flight path by merging the angular components...
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In this paper autotuning and self-tuning methods for Dynamic Matrix Control (DMC) are presented with application to single-input single-output (SISO) processes which can be approximated by a first-order-plus-dead-time...
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In this paper autotuning and self-tuning methods for Dynamic Matrix Control (DMC) are presented with application to single-input single-output (SISO) processes which can be approximated by a first-order-plus-dead-time model. In order to validate the method a nonlinear control valve system described by a Wiener process is simulated. This process was identified by a Hammerstein model and controlled by DMC with output compensator. The proposed tuning methods have its performance compared to another standard method found in literature, showing more conservative results regarding smoothness of the control action while maintaining adequate performance on set-point tracking.
This article delves into the significance of urban digital twins in generating synthetic data specifically tailored for individuals with disabilities. It explores how this data can be effectively utilized to construct...
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Injection Molding (IM) is considered to be the most important process for mass-producing plastic products. One of the biggest challenges facing injection molders is to determine the best settings for the controllable ...
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ISBN:
(纸本)1887706372
Injection Molding (IM) is considered to be the most important process for mass-producing plastic products. One of the biggest challenges facing injection molders is to determine the best settings for the controllable process variables (CPVs). Selecting the proper settings is crucial because the behavior of the polymeric material during shaping is highly influenced by the process variables. The difficulty of optimizing an IM process is that the performance measures (PMs), such as surface quality or cycle time that characterize the adequacy of the part for its intended purpose usually show conflicting behavior. Furthermore, in actual molding, the CPVs will vary over some range during molding. This inconsistency of the process variables will lead to variability in the PMs. In high precision manufacturing, in particular for micro and nano scale components and devices, this variability needs to be minimized, and if possible eliminated. Thus, the variability in the PMs needs to be included in the optimization problem. The aim of this work is to demonstrate a method based on CAE, statistical testing, artificial neural networks (ANNs), and data envelopment analysis (DEA) to find the optimal compromises between multiple PMs and their variability to prescribe the values for the CPVs in IM. We present an example where the optimization is carried out in two phases. Phase one uses the PMs that are significantly affected by the injection gate location in order to prescribe two possible injection gates. Phase two of the optimization uses Data Envelopment Analysis (DEA) to find a PM-based efficient frontier for each injection gate considering process variability. These two efficient frontiers are then compared to select the best location. Other possible applications are discussed.
In competitive segments like automobile and bus manufacturing industries, quality of vehicles need to be improved constantly to meet internal and external market demands. Compliance with international standard regulat...
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This working-in-progress paper aims to present a three-dimensional reconstruction using aerial images in different environments. The experiments were conducted with aircraft in both external and internal settings, sta...
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