Search results for "Control and Systems Engineering"
showing 10 items of 994 documents
Adaptive Control Design for Underactuated Cranes With Guaranteed Transient Performance: Theoretical Design and Experimental Verification
2022
For antiswing control of underactuated cranes, how to guarantee the converging speed of cranes through control design is essential but still remains unsolved. In this paper, the adaptive antiswing control for underactuated gantry cranes with guaranteed transient performance under unmodeled dynamics and external disturbances is investigated. To sovle this problem, a set of filters are proposed to make the backstepping technique applicable for the control of crane systems. Then through variable transformation the position error and swing angel could be guaranteed converging to the origin with a given exponential speed. Hardware experiments are conducted to show that the proposed scheme achiev…
Adaptive backstepping based consensus tracking of uncertain nonlinear systems with event-triggered communication
2021
Abstract This paper investigates the consensus tracking problem for a class of uncertain high-order nonlinear systems with parametric uncertainties and event-triggered communication. Under a directed communication condition, a totally distributed adaptive backstepping based control scheme is presented. Specifically, a decentralized triggering condition is adopted in this paper such that continuous monitoring of neighboring states, as required in some existing results, can be avoided. Besides, to handle the non-differentiability problem of virtual controllers, which arises from the utilization of neighboring states collected only at the triggering instants, the virtual controllers in each re…
Robust fault tolerant tracking controller design for vehicle dynamics: A descriptor approach
2015
Abstract In this paper, an active Fault Tolerant Tracking Controller (FTTC) scheme dedicated to vehicle dynamics system is proposed. To address the challenging problem, an uncertain dynamic model of the vehicle is firstly developed, by considering the lateral forces nonlinearities as a Takagi–Sugeno (TS) representation, the sideslip angle as unmeasurable premise variables and the road bank angle as an unknown input. Subsequently, the vehicle dynamic states with the sensor faults are jointly estimated by a descriptor observer on the basis of the roll rate and the steering angle measures. Then a fault tolerant tracking controller is synthesized and solutions are proposed in terms of Linear Ma…
“Anti-Bayesian” flat and hierarchical clustering using symmetric quantiloids
2017
A myriad of works has been published for achieving data clustering based on the Bayesian paradigm, where the clustering sometimes resorts to Naive-Bayes decisions. Within the domain of clustering, the Bayesian principle corresponds to assigning the unlabelled samples to the cluster whose mean (or centroid) is the closest. Recently, Oommen and his co-authors have proposed a novel, counter-intuitive and pioneering PR scheme that is radically opposed to the Bayesian principle. The rational for this paradigm, referred to as the “Anti-Bayesian” (AB) paradigm, involves classification based on the non-central quantiles of the distributions. The first-reported work to achieve clustering using the A…
Developing a Tool Point Control Scheme for a Hydraulic Crane Using Interactive Real-time Dynamic Simulation
2010
This paper describes the implementation of an interactive real-time dynamic simulation model of a hydraulic crane. The user input to the model is given continuously via joystick and output is presented continuously in a 3D animation. Using this simulation model, a tool point control scheme is developed for the specific crane, considering the saturation phenomena of the system and practical implementation. This paper describes the implementation of an interactive real-time dynamic simulation model of a hydraulic crane. The user input to the model is given continuously via joystick and output is presented continuously in a 3D animation. Using this simulation model, a tool point control scheme…
Toward Self-Supervised Feature Learning for Online Diagnosis of Multiple Faults in Electric Powertrains
2021
This article proposes a novel online fault diagnosis scheme for industrial powertrains without using historical faulty or labeled training data. The proposed method combines a one-class support vector machine (SVM) based anomaly detection and supervised convolutional neural network (CNN) algorithms to online detect multiple faults and fault severities under variable speeds and loads. The one-class SVM algorithm is to derive a score for defining faults or health classes in the first stage, and the resulting health classes are used as the training data for the CNN-based classifier in the second stage. Within this framework, the self-supervised learning of the proposed CNN algorithm allows the…
A Study on scale factor in distributed differential evolution.
2011
This paper proposes the employment of multiple scale factor values within distributed differential evolution structures. Four different scale factor schemes are proposed, tested, compared and analyzed. Two schemes simply employ multiple scale factor values and two also include an update logic during the evolution. The four schemes have been integrated for comparison within three recently proposed distributed differential evolution structures and tested on several various test problems. Numerical results show that, on average, the employment of multiple scale factors is beneficial since in most cases it leads to significant improvements in performance with respect to standard distributed alg…
Statistical validation of simulation models of observable systems
2003
In this paper, for validating computer simulation models of real, observable systems, an uniformly most powerful invariant (UMPI) test is developed from the generalized maximum likelihood ratio (GMLR). This test can be considered as a result of a new approach to solving the Behrens‐Fisher problem when covariance matrices of two multivariate normal populations (compared with respect to their means) are different and unknown. The test is based on invariant statistic whose distribution, under the null hypothesis, does not depend on the unknown (nuisance) parameters. The sample size and threshold of the UMPI test are determined from minimization of the weighted sum of the model builder's risk a…
Sensitivity of SHG-FROG for the characterization of ultrahigh-repetition-rate telecommunication laser sources
2004
International audience; We analyze experimentally the sensitivity of second-harmonic generation frequency-resolved optical gating (SHG-FROG) for the complete intensity and phase characterization of both a sinusoidal beat signal and a train of 1.3 ps pulses at a repetition rate of 160 GHz at 1550 nm. Using a commercially-available optical spectrum analyzer in the SHG-FROG set-up, incident pulses with energies of only 125 and 190 fJ, which correspond to the beat signal and the 1.3 ps pulse train, respectively, have been accurately characterized.
Using SOM and PCA for analysing and interpreting data from a P-removal SBR
2008
This paper focuses on the application of Kohonen self-organizing maps (SOM) and principal component analysis (PCA) to thoroughly analyse and interpret multidimensional data from a biological process. The process is aimed at enhanced biological phosphorus removal (EBPR) from wastewater. In this work, SOM and PCA are firstly applied to the data set in order to identify and analyse the relationships among the variables in the process. Afterwards, K-means algorithm is used to find out how the observations can be grouped, on the basis of their similarity, in different classes. Finally, the information obtained using these intelligent tools is used for process interpretation and diagnosis. In the…