Modeling and fuzzy sliding decoupling control of looper multivariable system

Li, Boqun; Fan, Xuan; Zhang, Daqing; Jiang, Guanjie

doi:10.1109/ccdc.2016.7531400

Cited by 5 publications

(2 citation statements)

References 2 publications

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“…The tension changes of the rolled piece are one of the main reasons for the thickness changes. If the tension exceeds the limitation, it will directly lead to the deterioration of production quality and the phenomenon of steel drawing or stacking [26]. Therefore, it is of great significance to strictly control the tension in the rolling processes.…”

Section: Application To Looper Control Systemmentioning

confidence: 99%

An Output Probabilistic Constrained Optimal Control Algorithm Based on Multivariable MAC and its Application in Looper Control System

2019

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Most actual industrial processes are multivariable and constrained complex systems. The state and output of the system also have uncertainty due to the existence of random disturbances. The output of the system is easier to be measured than the state and can more intuitively reflect the running state of the system. Considering the limitations of industrial equipment and the benefits of production, it is generally allowed to have a small portion of the output that can exceed the constraints. As a result, the outputs can be represented as corresponding single probabilistic constraints. In this paper, therefore, an output probabilistic constrained optimal control algorithm based on multivariable model algorithm control (MMAC) is proposed. First, the feedback correction link of the MMAC algorithm is improved, and the predicted outputs are corrected by taking the weighted average of the errors. Then, assuming that the disturbances obey Gaussian distribution, the output probabilistic constraints are transformed into deterministic ones. Next, the optimal control problem is solved as a quadratic programming (QP) problem after combining them with the performance index function of the MMAC. Finally, the proposed algorithm is applied to the looper control system in hot strip rolling process and compared with the single MMAC algorithm to verify its effectiveness. INDEX TERMS Uncertainty, MMAC, output probabilistic constraints, feedback correction, looper control system.

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Section: Application To Looper Control Systemmentioning

confidence: 99%

An Output Probabilistic Constrained Optimal Control Algorithm Based on Multivariable MAC and its Application in Looper Control System

2019

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“…The strong coupling primarily exists between the pitch angle and roll angle of the dual-ducted SUAV. This paper intends to adopt a neural network decoupling control algorithm of two-channel open-loop decoupled, and from the perspective of practical engineering concerned, the algorithm is relatively simple, reliable, and easy to implement [7][8].…”

Section: Neural Network Decoupling Controller Designmentioning

confidence: 99%

Neural Networks Attitude Decoupling Controller Design of Dual-Ducted SUAV Based on ADRC System

Gao

Wang

Tao

et al. 2014

AMR

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This dual-ducted SUAV is a nonlinear and strong coupling of multiple-input and multiple-output system, and particularly between the pitch and roll channels channel coupling is strong, in order to implement effective control, it must be decoupled. The traditional methods are difficult to achieve effective control of the strong coupling of multivariable systems. Neural network which has a strong learning ability, is able to learn from the sample and can adapt to changing learning condition. Thus, the neural network can be used to simulate the learning process of operator, and operating characteristics information of objects can be excavated from the measured data, and accordingly change the parameters of the controller and decoupling network. This paper presents a attitude control algorithm of the dual-ducted SUAV which combine ADRC algorithms with neural network decoupling control algorithm, to design a SUAV decoupling controller. The simulation results showed that the attitude control channels between the pitch and roll were independently of each other, indicating a good solution to decouple the coupling between the pitch and roll channels based on neural network algorithm.

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Performance Improvement in Hot Strip Rolling Mills by Improving Looper System

Hemakumar

Prasad

2018

2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI)

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Modeling and fuzzy sliding decoupling control of looper multivariable system

Cited by 5 publications

References 2 publications

An Output Probabilistic Constrained Optimal Control Algorithm Based on Multivariable MAC and its Application in Looper Control System

An Output Probabilistic Constrained Optimal Control Algorithm Based on Multivariable MAC and its Application in Looper Control System

Neural Networks Attitude Decoupling Controller Design of Dual-Ducted SUAV Based on ADRC System

Performance Improvement in Hot Strip Rolling Mills by Improving Looper System

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