Doppler based adaptive control for LEO satellite communications systems

The modified positive position feedback (MPPF) controller, an active vibration control method that uses collocated piezoelectric actuator actuators and sensors, is developed using an adaptive controller. The adaptive mechanism consists of two main parts: (1) frequency adaptation and (2) adaptive controller. Frequency adaptation only tracks the frequency of vibrations using fast Fourier transforms. The obtained frequency is then fed to MPPF compensators and the adaptive controller. This provides a unique feature for MPPF by extending its domain of capabilities from controlling tonal vibrations to broadband disturbances. The adaptive controller mechanism consists of a reference model that is of the same order as the MPPF system and its compensators. The adaptive law provides the additional control force that is needed for controlling frequency changes caused by broadband vibrations. The experimental results show that the frequency adaptation method that is derived has worked quite well. The results also indicate that the MPPF can provide significant vibration reduction on a cantilever beam that is used throughout the experiments.

A fiber laser is easily applied for micro welding owing to the excellent beam quality. Furthermore, a fiber laser is expected to be a promising heat source for adaptive control since the peak power is variable within sub-micro-second period. The objective of the research was to develop a new laser system with inprocess monitoring and adaptive control for the stable production of sound welds in thin sheets. The bead-on–plate welding of 0.1 mm-thick stainless steels was performed with a 75 W fiber laser beam of 1,090 nm wavelength. The stability of bead widths of laser welds made with or without monitoring and adaptive control was investigated in welding the sheet on the plate with a hole which should affect heat conduction and transfer. It was revealed that the heat radiation signal was sensitive to the increase in the bead width according to the change from heat transfer process to heat-insulated process. Moreover, the peak power was adaptively controlled in the minimum 50 ms-short period in order to produce stable weld bead width regardless of the existence or absence of the heat transfer plate. Consequently, it was confirmed that the fiber laser was an excellent oscillator for laser micro welding as well as for adaptive control.

The planning and control of reaching movements requires the processing of many different types of information, including target location in three dimensions, the starting posture and orientation of the body relative to the target, external forces or loads to be surmounted, the spatial trajectory of movement, skeletomuscular mechanical and contractile properties, and reafferent signals generated by the movement. The neuronal discharge patterns of cells in several cortical regions during reaching movements have been compared in an attempt to define the parameters of movement encoded by their activity and thus their position within the hypothesized planning hierarchy. Observations from two specific areas, the primary motor cortex and the superior parietal cortex, are summarized. A task in which monkeys were trained to make reaching movements in different directions to displace a handle between targets on a target panel was used. The purpose was to identify the reference frame in which movement was encoded in each area, by controlling parameters of movement kinematics and dynamics. However, the specific parameters signaled by the cells were not identified

The Brassicaceae family (mustards or crucifers) includes Arabidopsis thaliana as one of the most important model species in plant biology and a number of important crop plants such as the various Brassica species (e.g. cabbage, canola and mustard). Moreover, the family comprises an increasing number of species that serve as study systems in many fields of plant science and evolutionary research. However, the systematics and taxonomy of the family are very complex and access to scientifically valuable and reliable information linked to species and genus names and its interpretation are often difficult. BrassiBase is a continuously developing and growing knowledge database (http://brassibase.cos.uni-heidelberg.de) that aims at providing direct access to many different types of information ranging from taxonomy and systematics to phylo- and cytogenetics. Providing critically revised key information, the database intends to optimize comparative evolutionary research in this family and supports the introduction of the Brassicaceae as the model family for evolutionary biology and plant sciences. Some features that should help to accomplish these goals within a comprehensive taxonomic framework have now been implemented in the new version 1.1.9. A 'Phylogenetic Placement Tool' should help to identify critical accessions and germplasm and provide a first visualization of phylogenetic relationships. The 'Cytogenetics Tool' provides in-depth information on genome sizes, chromosome numbers and polyploidy, and sets this information into a Brassicaceae-wide context.

The multiple-institutions-based collaborated researchers securely exchange information and data sharing to gain insight into complex, variable diseases from many different types of information in various institutions. A novel approach to biorepository management scheme for information integration is presented. It integrates a large number of data types through a unified standardization. Local biorepository is the largest collection of local data. Central biorepository that integrates of all the local biorepository information can be shared and is the largest available collection of shared information resources. The key point between central biorepository and local biorepository is in two ways: The integration of local biorepository data; local biorepository queries and downloads the data from the database system. This method realizes a good harvesting feature from local biorepository to central biorepository; local biorepository can also access database system to obtain data sharing in a distributed environment.

This paper presents an investigation of truck drivers' performance during right-hand turns performed in intersections with traffic lights in order to elicit the truck drivers' domain, decision-making processes, and the strategies used while executing the turns. To gain knowledge about this, a truck driving instructor was interviewed, and four truck drivers were observed and interviewed. This resulted in a cognitive work analysis with the phases work domain analysis, control task analysis and strategies analysis. Through this study it is indi- cated that many different types of information are sought using several brief glances in mirrors, and the results shows how the front and near-zone mirrors were never used by the participants during the observed right-hand turns. Controlling the vehicle was found to be mainly automatic, whereas their focus is on the orientation about surroundings. Lastly, the drivers' behavior is discussed in relation to change blindness, confirmation bias and schemes.

Predicting pronouns across languages from a language with less variation to one with much more is a hard task that requires many different types of information, such as morpho-syntactic information as well as lexical semantics and coreference. We assumed that continuous word spaces fed into a multi-layer perceptron enriched with morphological tags and coreference resolution would be able to capture many of the linguistic regularities we found. Our results show that the model captures most of the linguistic generalisations. Its macro-averaged F-score is among the top-3 systems submitted to the DiscoMT shared task reaching 56.5%.

An interdisciplinary study on monosubstituted benzene involving computation, statistics and chemistry

In the vast literature exploring learning, many studies have used paired-associate stimuli, despite the fact that real-world learning involves many different types of information. One of the most popular materials used in studies of learning has been a set of Swahili-English word pairs for which Nelson and Dunlosky (Memory 2; 325-335, 1994) published recall norms two decades ago. These norms involved use of the Swahili words as cues to facilitate recall of the English translation. It is unclear whether cueing in the opposite direction (from English to Swahili) would lead to symmetric recall performance. Bilingual research has suggested that translation in these two different directions involves asymmetric links that may differentially impact recall performance, depending on which language is used as the cue (Kroll & Stewart, Journal of Memory and Language 33; 149-174,1994). Moreover, the norms for these and many other learning stimuli have typically been gathered from college students. In the present study, we report recall accuracy and response time norms for Swahili words when they are cued by their English translations. We also report norms for a companion set of fact stimuli that may be used along with the Swahili-English word pairs to assess learning on a broader scale across different stimulus materials. Data were collected using Amazon's Mechanical Turk to establish a sample that was diverse in both age and ethnicity. These different, but related, stimulus sets will be applicable to studies of learning, metacognition, and memory in diverse samples.

Control methodologies of traffic signals have significantly improved during the recent past along with advancements in technology. Adaptive traffic signal control is the most recent and advanced control type of traffic signals. Adaptive control is able to efficiently relieve traffic congestion by continuously adjusting signal timings according to real-time traffic conditions. Conventional optimization methods such as integer programming, hill climbing, or descent gradient searching have been gradually overshadowed by genetic algorithms in many areas including traffic signal operation. The research presented in this article is distinct from previous studies in that it focuses on real-time adaptive signal optimization using genetic algorithms. The proposed adaptive signal system provides acyclic signal operation based on a rolling horizon real-time control approach. The algorithm was tested using microsimulation for on-line evaluation and comparison to fixed-time plans generated from the latest TRANSYT-7F version 9.7, which has a genetic optimization feature. The developed signal system consists of three major components including a genetic algorithm optimization module, an internal traffic simulation module, and a database management system all working in cooperation to optimize signal timings in real time. Using the pseudo on-line simulation platform, three testing scenarios for high, medium, and low level of traffic demands were conducted focusing on evaluating several important features of the proposed adaptive signal control system. The test results indicated that real-time genetic control outperformed fixed-signal timing plan in all scenarios based on total vehicle delay.

International Journal of Adaptive Control and Signal ProcessingVolume 35, Issue 11 p. 2328-2328 RETRACTION STATEMENTFree Access Retraction: SCRIM drive system using adaptive backstepping control and mended recurrent Romanovski polynomials neural network with reformed particle swarm optimization This article retracts the following: Retracted: SCRIM drive system using adaptive backstepping control and mended recurrent Romanovski polynomials neural network with reformed particle swarm optimization Chih-Hong Lin, Kuo-Tsai Chang, Volume 33Issue 5International Journal of Adaptive Control and Signal Processing pages: 802-828 First Published online: April 10, 2019 First published: 12 October 2021 https://doi.org/10.1002/acs.3341AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat The above article from the International Journal of Adaptive Control and Signal Processing, published online on 10 April 2019 in Wiley Online Library (wileyonlinelibrary.com) and in Volume 33, pp. 802–828, has been retracted by agreement between the journal Editor in Chief, Mike Grimble, and John Wiley & Sons Ltd. The retraction has been agreed due to major overlap with a previously published article from the same group of authors. REFERENCE 1 Lin C-H, Chang K-T. SCRIM drive system using adaptive backstepping control and mended recurrent Romanovski polynomials neural network with reformed particle swarm optimization. Int J Adapt Control Signal Process. 2019; 33(5): 802- 828. https://doi.org/10.1002/acs.2990Wiley Online LibraryWeb of Science®Google Scholar Volume35, Issue11November 2021Pages 2328-2328 ReferencesRelatedInformation

The negative impacts of microgrids (µGs) on the load frequency highlight the importance of implementing a robust, efficient, and adaptable controller to ensure stability. This work introduces an adaptive load frequency control (LFC) for an isolated µG that includes a PV system and electric vehicles (EVs), which have a significant impact on frequency. This control utilizes a combination of sine cosine optimization (SCO) and balloon effect identifier (BEI) algorithms. The controller presented in this work transforms the LFC process into an optimization problem that is highly compatible with various random situations encountered in the control process. The suggested control method is a novel approach by utilizing SCO+BEI for adaptive LFC application, resulting in a highly efficient response. The effectiveness of the proposed adaptive controller is assessed under the conditions of 17 MW variable load, system parameters uncertainties, and installed PV systems of 6 MW. MATLAB / Simulink package is rummage-sale as a digital test environment. According to simulation results, the proposed adaptive controller succeeds in regulating the frequency and power of an islanded µG. To measure the efficiency of the proposed control scheme, a comparison between other control techniques (such as adaptive controller using Jaya+BEI and classical integral controller) is done. The findings of the studied scenarios assured that the not compulsory control method using (SCO+BEI) has an obvious superiority over other control methods in terms of frequency solidity in case of random load instabilities and parameter uncertainties. Finally, it can be said that the proposed controller can better ensure the safe operation of the µGs.

This paper investigates the feasibility of adaptive control scheme for vibration suppression of flexible beam. The dynamic model of the flexible cantilever beam using finite element modeling is derived. Adaptive vibration controllers are good candidates for problems where parameters of a plant are unknown or there are uncertainties in a system. Parameters of adaptive controllers are adjusted on-line to achieve the best performance. Two adaptive vibration control schemes: adaptive feedforward control scheme using least mean square algorithm and model reference adaptive control algorithm are developed to suppress the vibration. Computer simulations are performed to verify the effectiveness of the proposed adaptive vibration control schemes and demonstrate their applications in vibration control.

In this paper, we introduce a direct fractional order adaptive control design based on model reference adaptive control (MRAC) structure for a class of commensurate fractional order linear systems with an arbitrary relative degree, and whose parameters are unknown. By generalising the application of standard direct MRAC strategy to plants described by fractional order models, we develop a fractional adaptive control scheme (FOMRAC) based on the output feedback. We also define an adaptation control law ensuring the stability of the closed-loop system and the good tracking of the reference trajectory. The asymptotic stability of the fractional order control system is proven using an extension of the Lyapunov theorem. Simulation results show the effectiveness of the proposed control method even for plants with model parametric variations and additive noises.

In this paper the problem of adaptively controlling a hydraulic system with uncertainties is considered. An adaptive controller is derived to control actuator force with unknown valve flow coefficients and fluid parameters. This is subsequently cascaded into a position controller which uses RBF networks to compensate for the effects of friction in the system. In contrast to conventional adaptive controllers, the controller is augmented with a further layer that adaptively determines the optimal architecture for the RBF networks using the Minimum Message Length costing criterion. This provides an automated method of determining when it is no longer advantageous to increase the network size. Stability results are presented, and simulation demonstrates the ability of the MML criterion to determine when a suitable fit has been achieved.