A Petri Net Neural Network Robust Control for New Paste Backfill Process Model

  title={A Petri Net Neural Network Robust Control for New Paste Backfill Process Model},
  author={Xuehui Gao and Xinyan Hu},
  journal={IEEE Access},
In mining industries, the backfill becomes more and more important due to the environment protection concern. But most backfill investigations focus on the underground model and backfill materials. In this research, the paste backfill process based on the process control is investigated and a new paste backfill process model is proposed according to the Torricelli’s law and Bernoulli principle. In order to deal with the unknown nonlinear function of the proposed backfill model, a Petri net(PN… 
The New Paste Backfill Model and Control Based on The Centrifugal Pump and Permanent Magnet Synchronous Motor
The paste backfill mining becomes more important since the urgency of the reducing pollution, saving energy and improving technology in the mining. Most researches focus on the paste material itself
A New Nonlinear Active Disturbance Rejection Control for the Cable Car System to Restrain the Vibration
A new nonlinear active disturbance rejection control (ADRC) is proposed to restrain the vibration of the cable car, derived by a linear-invariant two-mass-spring system.


Robust Petri Fuzzy-Neural-Network Control for Linear Induction Motor Drive
  • R. Wai, Chia-Chin Chu
  • Engineering, Computer Science
    IEEE Transactions on Industrial Electronics
  • 2007
A robust Petri-fuzzy-neural-network (PFNN) control strategy applied to a linear induction motor (LIM) drive for periodic motion based on the model-free control design to retain the decoupled control characteristic of the FLC system is investigated.
Multiphysics Model for Consolidation Behavior of Cemented Paste Backfill
AbstractIn underground mining practices, cemented paste backfill (CPB), a mixture of tailings, cement, and water, is widely adopted to fill extracted stopes. During and after the filling of the
Neural-Network-Based Adaptive Funnel Control for Servo Mechanisms With Unknown Dead-Zone
An adaptive funnel control scheme for servo mechanisms with an unknown dead-zone is proposed by using an improved funnel function in a dynamic surface control procedure and an adaptive funnel controller is proposed to guarantee that the output error remains within a predefined funnel boundary.
Adaptive robust finite-time neural control of uncertain PMSM servo system with nonlinear dead zone
An adaptive robust finite-time neural control scheme is proposed for uncertain permanent magnet synchronous motor servo system with nonlinear dead-zone input based on a fast terminal sliding mode control principle, and the singularity problem in the initial TSMC is circumvented by modifying the terminal sliding manifold.
Modeling of pressure on retaining structures for underground fill mass
Abstract To retain fresh cemented paste backfill (CPB) (a large fill mass made of man-made fine soils that undergo cementation) in a stope (underground mining excavations), a retaining structure or
Output Feedback Control of Uncertain Hydraulic Servo Systems
This paper proposes a new control design method for high-order servo systems with hydraulic actuator dynamics, where the backstepping scheme is avoided and only the system output is required for the control implementation.
Robust Optimal Control of Wave Energy Converters Based on Adaptive Dynamic Programming
This paper presents a robust adaptive optimal control strategy for wave energy converters (WECs) based on the concept of adaptive dynamic programming (ADP), where a critic neural network (NN) is used to approximate the time-dependent optimal cost value.
An Integrated Optimal Design for Guaranteed Cost Control of Motor Driving System With Uncertainty
A novel combined performance index including the plant design objective and the control performance is developed as the integrated design cost function for the motor driving system.
Nonlinear Constrained Optimal Control of Wave Energy Converters With Adaptive Dynamic Programming
In this paper, we address the energy maximization problem of wave energy converters (WEC) subject to nonlinearities and constraints, and present an efficient online control strategy based on the
Modeling Self-Adaptive Software Systems by Fuzzy Rules and Petri Nets
I-PN is proposed to model a self-adaptive software system that can autonomously modify its behavior at runtime in response to changes in the system and its environment and is described in two different languages: component behaviors in Petri nets while logic control in fuzzy rules.