Modeling and control of PEMFC air supply system based on T-S fuzzy theory and predictive control

Energy ◽  
2019 ◽  
Vol 188 ◽  
pp. 116078 ◽  
Author(s):  
Duo Yang ◽  
Rui Pan ◽  
Yujie Wang ◽  
Zonghai Chen
Keyword(s):  
Predictive Control ◽  
Fuzzy Theory ◽  
Supply System ◽  
Modeling And Control ◽  
Air Supply ◽  
And Control

Modeling and control of an air supply system for a heavy duty PEMFC engine

2016 ◽  
Vol 41 (36) ◽  
pp. 16230-16239 ◽  
Author(s):  
Zhixiang Liu ◽  
Lun Li ◽  
Yi Ding ◽  
Huiwen Deng ◽  
Weirong Chen
Keyword(s):  
Supply System ◽  
Heavy Duty ◽  
Modeling And Control ◽  
Air Supply ◽  
And Control

The Modeling and Control of Leaching Rate in Nickel Stir Leaching Process of Sulfuric Acid

2012 ◽  
Vol 485 ◽  
pp. 165-168
Author(s):  
Qiang Li ◽  
Cheng Zhi Yang ◽  
Wen Bo Zhang ◽  
Yang Yu
Keyword(s):  
Computer Simulation ◽  
Sulfuric Acid ◽  
Predictive Control ◽  
Pid Control ◽  
Rate Control ◽  
Leaching Rate ◽  
Modeling And Control ◽  
Leaching Process ◽  
And Control ◽  
Nickel Leaching

Leaching rate is one of the key parameters in the nickel stir leaching process of sulfuric acid and it is hard to online measure directly due to a lot of uncertain facts. In this paper, the prediction model of nickel leaching rate is established by least squares identification method. A controller combining predictive control(PFC) and PID control is designed to control nickel leaching rate in stir leaching process of sulfuric acid and better results of leaching rate control is proved by computer simulation.

Modeling and control through leadership of a refined flocking system

2014 ◽  
Vol 25 (02) ◽  
pp. 255-282 ◽  
Author(s):  
Alfio Borzì ◽  
Suttida Wongkaew
Keyword(s):  
Predictive Control ◽  
Control Strategy ◽  
Social Systems ◽  
Open Loop ◽  
Modeling And Control ◽  
Control Scheme ◽  
Nonlinear Conjugate Gradient ◽  
Optimality Systems ◽  
And Control ◽  
Conjugate Gradient Solver

A new refined flocking model that includes self-propelling, friction, attraction and repulsion, and alignment features is presented. This model takes into account various behavioral phenomena observed in biological and social systems. In addition, the presence of a leader is included in the system in order to develop a control strategy for the flocking model to accomplish desired objectives. Specifically, a model predictive control scheme is proposed that requires the solution of a sequence of open-loop optimality systems. An accurate Runge–Kutta scheme to discretize the optimality systems and a nonlinear conjugate gradient solver are implemented and discussed. Numerical experiments are performed that investigate the properties of the refined flocking model and demonstrate the ability of the control strategy to drive the flocking system to attain a desired target configuration and to follow a given trajectory.

scholarly journals Modeling and Control of Crane Overload Protection During Marine Lifting Operation Based on Model Predictive Control

2017 ◽  
Author(s):  
Zhengru Ren ◽  
Roger Skjetne ◽  
Zhen Gao
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Pid Controller ◽  
Degrees Of Freedom ◽  
Multiple Shooting ◽  
Control Input ◽  
Lumped Mass ◽  
Modeling And Control ◽  
Overload Protection ◽  
And Control

This paper deals with a nonlinear model predictive control (NMPC) scheme for a winch servo motor to overcome the sudden peak tension in the lifting wire caused by a lumped-mass payload at the beginning of a lifting off or a lowering operation. The crane-wire-payload system is modeled in 3 degrees of freedom with the Newton-Euler approach. Direct multiple shooting and real-time iteration (RTI) scheme are employed to provide feedback control input to the winch servo. Simulations are implemented with MATLAB and CaSADi toolkit. By well tuning the weighting matrices, the NMPC controller can reduce the snatch loads in the lifting wire and the winch loads simultaneously. A comparative study with a PID controller is conducted to verify its performance.

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