The article describes the uses of multi-input/multi-output systems, with the aim of assessment of structural changes and stability in the Russian transport sector. Empirical input-output data for the period between th...
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The article describes the uses of multi-input/multi-output systems, with the aim of assessment of structural changes and stability in the Russian transport sector. Empirical input-output data for the period between the years 2000 and 2014 are used. A basic model and overview of the literature are given. The article summarizes the assessment of structural changes and stability. The author gives his own vision of a state of the Russian transport sector. The analysis is carried out for the transport sector as a whole as well as for the various transport modes. Analytical and quantitative results are presented. Assessments of the dynamics of several key economic indicators of the Russian transport sector based on the model calculations are discussed. The indicators were compared based on World input-output Database (WIOD) version 2016. It is shown that the share of intermediate goods and services in the transport sector's gross output fell, while the share of final goods increased from 2000 to 2014. But the share of air transport in the transport sector's gross output as a whole was stable in 2000-2014. Copyright (C) 2021 The Authors.
Iterative learning control (ILC) is an adequate control approach to handle various types of cyclic control tasks. However, when in each iteration the calculation of the control trajectory requires the solution of a hi...
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Iterative learning control (ILC) is an adequate control approach to handle various types of cyclic control tasks. However, when in each iteration the calculation of the control trajectory requires the solution of a high dimensional constrained quadratic program, the algorithm is bound to be infeasible for real-time applications with very small cycle lengths in the order of milliseconds due to the prohibitively large computational cost. In this contribution, an approach is presented to reduce the computational burden to solve an optimization-based iterative learning control that is restricted to a binary domain by orders of magnitude. The method is suitable for control trajectories that contain only few 1's, but a large number of 0's in each iteration for a specific class of problems, e.g., for cyclic firing synchronization of combustion tubes. The presented setup is tested experimentally at an acoustic mock-up of an annular pulse detonation combustor to determine an appropriate fire synchronization. More specifically, it is used to adjust the firing pattern of multiple simulated combustion tubes in order to reduce pressure fluctuations measured downstream in an annular plenum, which is a prerequisite to apply such a new thermodynamically efficient combustion process in a real gas turbine. Copyright (C) 2020 The Authors.
The article describes the uses of multi-input/multi-output systems, with the aim of assessment of structural changes and stability in the Russian transport sector. Empirical input-output data for the period between th...
详细信息
The article describes the uses of multi-input/multi-output systems, with the aim of assessment of structural changes and stability in the Russian transport sector. Empirical input-output data for the period between the years 2000 and 2014 are used. A basic model and overview of the literature are given. The article summarizes the assessment of structural changes and stability. The author gives his own vision of a state of the Russian transport sector. The analysis is carried out for the transport sector as a whole as well as for the various transport modes. Analytical and quantitative results are presented. Assessments of the dynamics of several key economic indicators of the Russian transport sector based on the model calculations are discussed. The indicators were compared based on World input-output Database (WIOD) version 2016. It is shown that the share of intermediate goods and services in the transport sector’s gross output fell, while the share of final goods increased from 2000 to 2014. But the share of air transport in the transport sector’s gross output as a whole was stable in 2000-2014.
Inversion-based feedforward control is a basic method of tracking controls. The aim of this paper is to design MIMO multirate feedforward controller that improves continuous-time tracking performance in MIMO LTI syste...
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Inversion-based feedforward control is a basic method of tracking controls. The aim of this paper is to design MIMO multirate feedforward controller that improves continuous-time tracking performance in MIMO LTI systems considering not only on-sample but also intersample behavior. Several types of MIMO multirate feedforward controllers are designed and evaluated in terms of the 2-norm of the control inputs. The approach is compared with a conventional MIMO single-rate feedforward controller in simulations. The approach improves the intersample behavior through the optimal selection of inputmultiplicities with MIMO multirate system inversion.
Iterative learning control (ILC) is an adequate control approach to handle various types of cyclic control tasks. However, when in each iteration the calculation of the control trajectory requires the solution of a hi...
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Iterative learning control (ILC) is an adequate control approach to handle various types of cyclic control tasks. However, when in each iteration the calculation of the control trajectory requires the solution of a high dimensional constrained quadratic program, the algorithm is bound to be infeasible for real-time applications with very small cycle lengths in the order of milliseconds due to the prohibitively large computational cost. In this contribution, an approach is presented to reduce the computational burden to solve an optimization-based iterative learning control that is restricted to a binary domain by orders of magnitude. The method is suitable for control trajectories that contain only few 1’s, but a large number of 0’s in each iteration for a specific class of problems, e.g., for cyclic firing synchronization of combustion tubes. The presented setup is tested experimentally at an acoustic mock-up of an annular pulse detonation combustor to determine an appropriate fire synchronization. More specifically, it is used to adjust the firing pattern of multiple simulated combustion tubes in order to reduce pressure fluctuations measured downstream in an annular plenum, which is a prerequisite to apply such a new thermodynamically efficient combustion process in a real gas turbine.
Perfect tracking control method using multirate feedforward control is a very effective control method in high-precision positioning systems since this method provides zero tracking error for a nominal plant at every ...
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Perfect tracking control method using multirate feedforward control is a very effective control method in high-precision positioning systems since this method provides zero tracking error for a nominal plant at every reference sampling point theoretically. When we design a multirate feedforward controller for a multi-inputmulti-output system, it is known that several types of controllers can be designed depending on how to select inputmultiplicities. Although multirate feedforward controllers provide perfect tracking at every reference sampling point theoretically, intersample behavior is different. In this paper, we propose the stable state trajectory generation method and the guideline to design an optimal multi-inputmulti-outputmultirate feedforward controller considering the 2-norm of control input and improve the intersample behavior. The effectiveness of the proposed method is verified in the simulation. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
In this paper we develop a method for learning nonlinear system models with multiple outputs and inputs. We begin by modeling the errors of a nominal predictor of the system using a latent variable framework. Then usi...
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In this paper we develop a method for learning nonlinear system models with multiple outputs and inputs. We begin by modeling the errors of a nominal predictor of the system using a latent variable framework. Then using the maximum likelihood principle we derive a criterion for learning the model. The resulting optimization problem is tackled using a majorization-minimization approach. Finally, we develop a convex majorization technique and show that it enables a recursive identification method. The method learns parsimonious predictive models and is tested on both synthetic and real nonlinear systems. (C) 2018 Elsevier Ltd. All rights reserved.
Present work provides the robust suboptimal control algorithm for an output stabilization of a linear mum-inputmulti-output (MIMO) plant with uncertainties. The algorithm combines robust control provided by auxiliary...
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ISBN:
(纸本)9781538634356
Present work provides the robust suboptimal control algorithm for an output stabilization of a linear mum-inputmulti-output (MIMO) plant with uncertainties. The algorithm combines robust control provided by auxiliary loop method for disturbances compensation and optimal control in the form of the linear quadratic regulator. In current research, plant is presented in form of linear interval model. This reflects plant parametric uncertainty and possibility to use the proposed method to control a nonlinear plant amenable to the interval linearization. The latter is used in the experimental illustration of the algorithm performance on the Twin Rotor MIMO System laboratory platform.
This papers presents a new heuristic multiobjective optimization procedure based on Kalman filtering. The novel approach is compared to the well-known Nondominated Sorting Genetic Algorithm version II with the Zitzler...
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This papers presents a new heuristic multiobjective optimization procedure based on Kalman filtering. The novel approach is compared to the well-known Nondominated Sorting Genetic Algorithm version II with the Zitzler...
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This papers presents a new heuristic multiobjective optimization procedure based on Kalman filtering. The novel approach is compared to the well-known Nondominated Sorting Genetic Algorithm version II with the Zitzler, Deb and Thiele test suite showing favorable results for the Kalman based solution. Further improvement on the proposed algorithm is made with respect to the learning factor, which is set to be time-dependent, improving the algorithm in most cases and diminishing the number of control parameters. The proposed multiobjective optimization algorithm is interesting due to its convergence and coverage quality, its computational complexity and few parameters to be adjusted. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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