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Control Engineering Practice
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#1Matthieu Lucke (Imperial College London)H-Index: 1
#2Anna StiefH-Index: 2
Last.Nina F. Thornhill (Imperial College London)H-Index: 31
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Abstract Classification-based methods for fault detection and identification can be difficult to implement in industrial systems where process measurements are subject to noise and to variability from one fault occurrence to another. This paper uses statistical alarms generated from process measurements to improve the robustness of the fault detection and identification on an industrial process. Two levels of alarms are defined according to the position of the alarm threshold: level-1 alarms (lo...
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#1Pedro Santos (University of Valladolid)H-Index: 1
#2Jose Luis Pitarch (University of Valladolid)H-Index: 8
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Abstract Nonlinear model predictive control (NMPC) has increased popularity thanks to the availability of black-box models, systematically obtained from plant data via machine-learning procedures. Although this may be a good approach in the medium term, pure data-driven models quickly become outdated with changes in the process operation, so re-identification (training) routines are periodically required. Moreover, if the NMPC includes any economic objective to drive the process to a more effici...
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#1Gianmario Rinaldi (UNIPV: University of Pavia)H-Index: 2
#2Antonella Ferrara (UNIPV: University of Pavia)H-Index: 35
Abstract This paper deals with the design and the experimental-based assessment of a scheme to identify the relative degree of a system in order to correctly design the controller. The system is assumed to have an unknown dynamics, and the output is measured in a discrete-time fashion. Provided that a prescribed input signal is applied, it is proven that a set of inequalities holds only for the r th time derivative of the output, where r is the relative degree. A practical algorithm for the rela...
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#1Bingbing Shen (ZJU: Zhejiang University)
#2Le Yao (ZJU: Zhejiang University)H-Index: 2
Last.Zhiqiang Ge (ZJU: Zhejiang University)H-Index: 33
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Abstract Probabilistic latent variable regression models have recently caught much attention in the process industry, particularly for soft sensor applications. One of the main challenges for those models is how to effectively extract nonlinear features for latent variable regression. This paper proposes a nonlinear probabilistic latent variable regression (NPLVR) model based on the features extracted by variational auto-encoder. To extend the NPLVR model from shallow to deep structure, a hierar...
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#1Binh Minh Nguyen (UTokyo: University of Tokyo)H-Index: 6
#2Shinji Hara (Chu-Dai: Chuo University)H-Index: 1
Last.Hori Yoichi (UTokyo: University of Tokyo)H-Index: 38
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Abstract A proper dynamical model with the physical interconnection is necessary to accurately capture the slip phenomena of in-wheel-motored vehicles, since the wheels interact with each other through the vehicle body to make up the vehicle motion. Considering the uptrend in the number of in-wheel-motors, this paper proposes a way to effectively model the slip phenomena as a multi-agent dynamical system. A hierarchical LQR for time-varying interconnected system, which can significantly reduce t...
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#1Rinat Landman (Aalto University)H-Index: 3
#2Sirkka-Liisa Jämsä-Jounela (Aalto University)H-Index: 18
Abstract Industrial processes are often subjected to abnormal events such as faults or external disturbances which can easily propagate via the process units. Establishing causal dependencies among process measurements has a key role in fault diagnosis due to its ability to identify the root cause of a fault and its propagation path. This paper proposes a hybrid nonlinear causal analysis based on nonparametric multiplicative regression (NPMR) for identifying the propagation of an oscillatory dis...
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#1Vanja Ranogajec (University of Zagreb)H-Index: 3
#2Joško Deur (University of Zagreb)H-Index: 19
Last.H. Eric Tseng (Ford Motor Company)H-Index: 15
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Abstract In advanced automatic transmissions (ATs) with a high number of gears, a multi-step, double-transition downshifts (DTS) occur, in which typically two pairs of clutches change their state. This paper proposes different definitions of piecewise linear control profiles for performing such downshifts, which are determined based on insights gained by utilizing previously developed AT control trajectory optimization method. Optimal values of control profiles parameters are determined by using...
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#1Ronghuai Qi (UW: University of Waterloo)H-Index: 1
#2Amir Khajepour (UW: University of Waterloo)H-Index: 32
Last.William Melek (UW: University of Waterloo)H-Index: 17
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Abstract This paper presents an underactuated mobile manipulator (UMM) and focuses on solving modeling, tracking, and vibration- and balance-control problems. Although the study has been directed at warehousing applications, the developed techniques are general and can be applied to other applications. The derivation of equations of motion of the UMM, disturbance analysis, and model validation are investigated to reveal the actual system dynamics. Additionally, a simple but effective strategy is...
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#1Wilian M. dos Santos (USP: University of São Paulo)H-Index: 6
#2Adriano A. G. Siqueira (USP: University of São Paulo)H-Index: 12
Abstract This paper proposes an optimal impedance controller for robot-aided rehabilitation of walking, aiming to increase the patient’s activity during the therapy. In an online procedure, the joint torques produced by the patient during the gait is estimated using the generalized momenta-based disturbance observer and the Extended Kalman filter algorithm. At the same time, a model predictive control is performed to obtain the instantaneous optimal stiffness parameters of the robot’s impedance ...
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#1Chao Shang (THU: Tsinghua University)H-Index: 11
#2Hongquan Ji (SDUST: Shandong University of Science and Technology)H-Index: 3
Last.Huang Dexian (THU: Tsinghua University)H-Index: 22
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Abstract In process industries, it is necessary to conduct fault diagnosis after abnormality is found, with the aim to identify root cause variables and further provide instructive information for maintenance. Contribution plots along with multivariate statistical process monitoring are standard tools towards this goal, which, however, suffer from the smearing effect and high diagnostic complexity on large-scale processes. In fact, process variables tend to be naturally grouped, and in this work...
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