Notice of Retraction: Dynamic modeling of wood drying process based on SLSSVM

Zhang, Dongyan; Cao, Jun; Sun, Liping

doi:10.1109/iccsit.2010.5565025

Cited by 3 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One of the common drawbacks of the existing models is the complexity of the introduced models that makes it difficult to use as control engineering applications [4], [6], [7]. Additionally, the existing models are not able to cover properties of the drying process such as changes in the air flow direction and air speed which can be considered as a second common drawback among them [4], [6], [7].…”

Section: Introductionmentioning

confidence: 99%

“…The presented model has high complexity with many parameters that are not always explicitly known. In [7], the authors use an online dynamic model based on sparse Least Squares Support Vector Machines (LSSVM) with strong coupling and nonlinear features.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, the existing models are not able to cover properties of the drying process such as changes in the air flow direction and air speed which can be considered as a second common drawback among them [4], [6], [7]. In order to have a suitable and straightforward model which can cover different characteristics of the drying process with less complexity, compared to [4], [6], [7] for instance, in this paper we firstly simplify the existing mathematical models [4] in different ways and secondly convert the obtained equations to a state space realization. We augment the model and propose a switching state space realization that can cover three different modes corresponding to the fan operation.…”

Section: Introductionmentioning

confidence: 99%

“…During the last decades, a big effort have been made to develop the mathematical models of the wood drying process [1]- [7]. For example in [4], the authors present a mathematical model for the wood drying process which is based on heat and mass transfer equations.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

State Space Realization of Wood Drying Process: Modeling, Simulation and Evaluation in Reality

Delshad

Gustafsson

2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

View full text Add to dashboard Cite

The modeling of a wood drying process using a state space realization is considered. Based on balance equations for energy and mass in the air gap between the timbers, on the wood surface and within the wood, a state space realization consisting of linear and nonlinear parts is proposed which can describe the moisture content and temperature behavior of timber inside a drying kiln. Finally, the proposed state space realization is illustrated with a simulation and achieved results are evaluated by real measurements.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

State Space Realization of Wood Drying Process: Modeling, Simulation and Evaluation in Reality

Delshad

Gustafsson

2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

View full text Add to dashboard Cite

show abstract

RBF based sliding mode control method for lumber drying system

Zhou¹,

Wang²

2019

WFS

View full text Add to dashboard Cite

Lumber is an indispensable raw material for people's daily life. Drying process is a crucial stage in lumber manufacture. As to ensure a suitable and usable end product of lumber, most of its MC must be removed by drying. Improving the quality of lumber drying requires efficient control scheme. This article presents a design of radical basis function (RBF) neural network-based sliding mode controller for lumber drying system. RBF neural network is introduced to optimize the conventional sliding mode controller. The proposed strategy has been theoretically and experimentally investigated to demonstrate the applicability for lumber drying process. Comparative study of conventional sliding mode control (SMC) scheme and proposed control scheme is also presented. It was found that the control performance of RBF-based sliding mode controller was superior to the conventional sliding mode controller in computer simulation. Furthermore, in the field conditions, time and energy consumption reduction were noticed with RBF-based sliding mode controller compared with conventional SMC strategy using the same drying schedule, although the drying quality using the two control methods were similar.

show abstract

System Identification of Wood Drying Process Based on ARMAX Model

Zhou¹,

Zhang²,

Bao-fu³

et al. 2019

View full text Add to dashboard Cite

This article presents system identification of wood drying process based on ARMAX model. Temperature and equivalent moisture content are considered as inputs, and moisture content of the wood sample during drying is taken as output of the system. The comparative study of RLS and FF-RLS to identify the system parameters is presented. Simulation results are presented to validate the efficacy of the ARMAX model for wood drying process.

show abstract

Notice of Retraction: Dynamic modeling of wood drying process based on SLSSVM

Cited by 3 publications

References 5 publications

State Space Realization of Wood Drying Process: Modeling, Simulation and Evaluation in Reality

State Space Realization of Wood Drying Process: Modeling, Simulation and Evaluation in Reality

RBF based sliding mode control method for lumber drying system

System Identification of Wood Drying Process Based on ARMAX Model

Contact Info

Product

Resources

About