the proceedings contain 168 papers. the topics discussed include: detection and estimation of moving obstacles for a UAV;optimal startup operation of a pressure swing adsorption;model reference based tuning for fracti...
the proceedings contain 168 papers. the topics discussed include: detection and estimation of moving obstacles for a UAV;optimal startup operation of a pressure swing adsorption;model reference based tuning for fractional-order 2 DoF PI controllers with a robustness consideration;extension of the DO-MPC development framework to real-time simulation studies;control of multi-chamber continuous fluidized bed spray granulation;a polytopic invariant set based iterative learning model predictive control;and advanced nonlinear multi-layer processcontrol for autotrophic cultivations.
A novel built-in test (BIT) design method for fault detection mid isolation (FDI) is presented, in which the test information extracted is maximized using parametric sensitivities derived by a system model. Two case s...
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ISBN:
(纸本)9781510828643
A novel built-in test (BIT) design method for fault detection mid isolation (FDI) is presented, in which the test information extracted is maximized using parametric sensitivities derived by a system model. Two case studies are presented to demonstrate this approach. the first test focuses on fouling identification in an aircraft heat exchanger, in the presence of uncertain system inputs. the second example expands this method to a subsystem of an aircraft environmental control system (ECS) to calculate optimal conditions for component FDI. (C) 2016, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
In process industry, such as chemical, pulp and paper or petrochemical industry there are plenty of processes that require multivariable control. Classical control structures that handle this, for example cascade cont...
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In process industry, such as chemical, pulp and paper or petrochemical industry there are plenty of processes that require multivariable control. Classical control structures that handle this, for example cascade control, feedforward, ratio control, and parallel control have been used at least since the 1930s. Today, much focus in academia is on model predictive control (MPC). In this paper we discuss the comparative advantages and disadvantages of classical control structures and MPC. We also briefly discuss some related topics in plant-wide control. (C) 2016, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
In this work an approach for thawing blocks of foodstuff, in particular fish, is introduced. the functional principle is based on plate freezer technology, which has been used in industry for decades. the aim of this ...
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In this work an approach for thawing blocks of foodstuff, in particular fish, is introduced. the functional principle is based on plate freezer technology, which has been used in industry for decades. the aim of this work is to describe the temperature dynamics of this thawing process by means of partial differential equations (PDEs) and controlthe boundary conditions in an optimal way. the PDE describing the temperature dynamics is based on the diffusion equation with state-dependent parameter functions. (C) 2016, ifac (International Federationof Automatic control) Hosting by Elsevier Ltd. All rights reserved.
In multi-modular process architectures with independent but interacting sub systems, identification may not he the first choice at hand for closed loop control. A robust relay-based PID autotuning strategy is presente...
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In multi-modular process architectures with independent but interacting sub systems, identification may not he the first choice at hand for closed loop control. A robust relay-based PID autotuning strategy is presented and validated on a quadruple tank system with non-minimum phase dynamics. the controller ensures a specified closed loop robustness, which is of great, benefit to the overall performance. the experimental results suggest that the proposed method fulfils the robustness requirement and performs well in various operating conditions of the testbench. (C) 2016, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
this paper concerns the model predictive control applied to tie systems with bounded uncertainties. these systems are described by a state-space model with uniformly distributed states and outputs with unknown bounds ...
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this paper concerns the model predictive control applied to tie systems with bounded uncertainties. these systems are described by a state-space model with uniformly distributed states and outputs with unknown bounds of respective distributions. the model matrices are assumed to be known. the approximate estimation of states and noise bounds is based on the Bayesian approach. A state-space generalised predictive control is selected as a suitable target, model predictive control strategy. the proposed concept of the above mentioned estimation within generalised predictive control is illustrated by representative comparative simulation examples. (C) 2016, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
Current Optimization and Model Predictive control practices for batch processes are implemented using two models, one for determining the optimal trajectories and another identified around those trajectories for contr...
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Current Optimization and Model Predictive control practices for batch processes are implemented using two models, one for determining the optimal trajectories and another identified around those trajectories for control purposes. Here we use the recently developed Dynamic Response Surface Modeling methodology from which the optimal trajectories and the local linear or nonlinear state-space models for control purposes are obtained. Because concentration measurements at each batch run are very infrequent, this might be the most attractive way to obtain a dynamic model for control purposes. (C) 2016, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
Isolation of plant vide faults in large-scale complex systems is particularly challenging. A methodology to detect and isolate faults is proposed, detecting the faulty variables using univariate control charts and the...
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Isolation of plant vide faults in large-scale complex systems is particularly challenging. A methodology to detect and isolate faults is proposed, detecting the faulty variables using univariate control charts and the causality information between them to indicate the source. the clustering of faulty variables uses univariate analysis to avoid the smearing effect brought by multivariate analysis. the variable where the fault took place is indicated, handling fault novelties in a very natural manner. the proposed method is discussed and illustrated through its application to the Tennessee Eastman process and to routine operating data from a thermoelectric power plant. (C) 2016, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
A detailed physical model has been developed for an industrial 350 kt/year low-density: polyethylene tubular reactor and implemented in a proprietary non-linear Model Predictive control framework to control product qu...
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A detailed physical model has been developed for an industrial 350 kt/year low-density: polyethylene tubular reactor and implemented in a proprietary non-linear Model Predictive control framework to control product quality during grade transitions. the controller is now at the end of the commissioning phase and is regularly used during transitions. Improved transition control reduces the amount of off-spec product, which improves the profit of the plant as well as the consistency during transitions compared to the manual transition control scheme used previously. (C) 2016, ifac (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.
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