The Experts below are selected from a list of 150276 Experts worldwide ranked by ideXlab platform
Jie Zhang - One of the best experts on this subject based on the ideXlab platform.
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Iterative learning control of batch processes based on time varying Perturbation Models
Journal of Tsinghua University, 2008Co-Authors: Jie Zhang, J Nguyen, Z XiongAbstract:This paper presents an iterative learning control technique for batch processes based on time varying Perturbation Models.Linear Perturbation Models for product quality,linearized around the nominal trajectories, are identified from process operational data using principal component regression (PCR) and partial least squares (PLS) regression.Model-plant mismatches are addressed by adding Model prediction errors from the previous batch to the Model predictions for the current batch.Thus,the Perturbation Model is updated in a batch-wise manner.After completion of each batch,a batch-wise Perturbation Model is identified linearized around the control trajectory for that batch.The regression analyses to correlate the control actions with the results for various stages of a batch to obtain more accurate Models.Simulations show that the control performance based on PCR and PLS Models is better than that based on a multiple linear regression Model.
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Integrated tracking control strategy for batch processes using a batch-wise linear time-varying Perturbation Model
IET Control Theory & Applications, 2007Co-Authors: Zhihua Xiong, Jie Zhang, Xiafu WangAbstract:An integrated batch-to-batch control and within-batch online control strategy for tracking product quality trajectories in batch processes is proposed. On the basis of a batch-wise linear time-varying Perturbation Model, iterative learning control (ILC) is implemented for batch-to-batch control and the convergence of tracking errors under ILC is guaranteed. Within a batch, a predictive Model is constructed by directly partitioning the linear time-varying Model according to time, then batch Model predictive control with shrinking horizons is applied online to reduce the effects of Model-plant mismatch and/or unknown disturbances. By properly combining these two control methods, the integrated control strategy can complement both methods to obtain good performance. The proposed strategy is demonstrated on a simulated batch polymerisation process, and the results show that the performance can be improved quite significantly under the integrated control strategy than only under ILC, especially when disturbances occur.
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product quality trajectory tracking in batch processes using iterative learning control based on time varying Perturbation Models
Industrial & Engineering Chemistry Research, 2003Co-Authors: Zhihua Xiong, Jie ZhangAbstract:A run-to-run Model-based iterative learning control (ILC) strategy for the tracking control of product quality in batch processes is proposed. A linear Perturbation Model for product quality, linea...
Aristides M. Bonanos - One of the best experts on this subject based on the ideXlab platform.
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Algebraic Model for thermocline thermal storage tank with filler material
Solar Energy, 2015Co-Authors: Evgeny V. Votyakov, Aristides M. BonanosAbstract:Abstract A recent Perturbation Model (Votyakov and Bonanos, 2014) is solved with an algebraic approximation. Results are in agreement with independent numerical results of Yang and Garimella (2010). The algebraic Model reveals several scaling ratios as well as a non-monotonic behavior of the thermocline thickness as a function of fluid Reynolds number.
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a Perturbation Model for stratified thermal energy storage tanks
International Journal of Heat and Mass Transfer, 2014Co-Authors: Evgeny V. Votyakov, Aristides M. BonanosAbstract:Abstract A single phase Perturbation Model has been developed for the characterization of the behavior of packed-bed thermocline thermal energy storage tanks, derived from the one-dimensional two-phase energy equations. The non-dimensional parameters governing the problem have been identified and separated into two groups, those related to the fluid and solid-filler material thermo-physical properties ( β , γ ), and those relating to the process flow (Peclet and Biot numbers). A series expansion solution for the Perturbation Model is derived. The new Perturbation Model is an improvement over the current one-phase Models as it more accurately captures the effect of the diffusion term, and allows for a direct comparison with the two-phase Model.
Zhihua Xiong - One of the best experts on this subject based on the ideXlab platform.
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iterative learning control for automatic train operation with discrete gears
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS), 2019Co-Authors: Hua Chen, Zhihua XiongAbstract:In the traditional iterative learning control (ILC) for automatic train operation (ATO), control inputs are usually continuous signals. In this paper, a practical ILC is presented to carry out the train operation by discrete traction or braking force. The train motion dynamic Model is described by linear time-varying Perturbation Model along with the reference trajectories, which can be identified by the historical data. The ILC based on the Perturbation Model can be easily used to the case with the continuous control signals because the updating law of the ILC can be derived theoretically. Then the proposed ILC method is extended to the case with discrete gears by transforming the ILC with discrete control signals into a well-defined mixed integer programming (MIP) problem. The proposed method has been illustrated on the simulation case. Simulation results show that the method can not only track the reference trajectories to a fine accuracy but also restrict the gear shift frequency of the operation process, which is helpful to improve the ride comfort index of the whole train operation.
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Integrated tracking control strategy for batch processes using a batch-wise linear time-varying Perturbation Model
IET Control Theory & Applications, 2007Co-Authors: Zhihua Xiong, Jie Zhang, Xiafu WangAbstract:An integrated batch-to-batch control and within-batch online control strategy for tracking product quality trajectories in batch processes is proposed. On the basis of a batch-wise linear time-varying Perturbation Model, iterative learning control (ILC) is implemented for batch-to-batch control and the convergence of tracking errors under ILC is guaranteed. Within a batch, a predictive Model is constructed by directly partitioning the linear time-varying Model according to time, then batch Model predictive control with shrinking horizons is applied online to reduce the effects of Model-plant mismatch and/or unknown disturbances. By properly combining these two control methods, the integrated control strategy can complement both methods to obtain good performance. The proposed strategy is demonstrated on a simulated batch polymerisation process, and the results show that the performance can be improved quite significantly under the integrated control strategy than only under ILC, especially when disturbances occur.
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product quality trajectory tracking in batch processes using iterative learning control based on time varying Perturbation Models
Industrial & Engineering Chemistry Research, 2003Co-Authors: Zhihua Xiong, Jie ZhangAbstract:A run-to-run Model-based iterative learning control (ILC) strategy for the tracking control of product quality in batch processes is proposed. A linear Perturbation Model for product quality, linea...
Evgeny V. Votyakov - One of the best experts on this subject based on the ideXlab platform.
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Algebraic Model for thermocline thermal storage tank with filler material
Solar Energy, 2015Co-Authors: Evgeny V. Votyakov, Aristides M. BonanosAbstract:Abstract A recent Perturbation Model (Votyakov and Bonanos, 2014) is solved with an algebraic approximation. Results are in agreement with independent numerical results of Yang and Garimella (2010). The algebraic Model reveals several scaling ratios as well as a non-monotonic behavior of the thermocline thickness as a function of fluid Reynolds number.
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a Perturbation Model for stratified thermal energy storage tanks
International Journal of Heat and Mass Transfer, 2014Co-Authors: Evgeny V. Votyakov, Aristides M. BonanosAbstract:Abstract A single phase Perturbation Model has been developed for the characterization of the behavior of packed-bed thermocline thermal energy storage tanks, derived from the one-dimensional two-phase energy equations. The non-dimensional parameters governing the problem have been identified and separated into two groups, those related to the fluid and solid-filler material thermo-physical properties ( β , γ ), and those relating to the process flow (Peclet and Biot numbers). A series expansion solution for the Perturbation Model is derived. The new Perturbation Model is an improvement over the current one-phase Models as it more accurately captures the effect of the diffusion term, and allows for a direct comparison with the two-phase Model.
Xiafu Wang - One of the best experts on this subject based on the ideXlab platform.
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Integrated tracking control strategy for batch processes using a batch-wise linear time-varying Perturbation Model
IET Control Theory & Applications, 2007Co-Authors: Zhihua Xiong, Jie Zhang, Xiafu WangAbstract:An integrated batch-to-batch control and within-batch online control strategy for tracking product quality trajectories in batch processes is proposed. On the basis of a batch-wise linear time-varying Perturbation Model, iterative learning control (ILC) is implemented for batch-to-batch control and the convergence of tracking errors under ILC is guaranteed. Within a batch, a predictive Model is constructed by directly partitioning the linear time-varying Model according to time, then batch Model predictive control with shrinking horizons is applied online to reduce the effects of Model-plant mismatch and/or unknown disturbances. By properly combining these two control methods, the integrated control strategy can complement both methods to obtain good performance. The proposed strategy is demonstrated on a simulated batch polymerisation process, and the results show that the performance can be improved quite significantly under the integrated control strategy than only under ILC, especially when disturbances occur.