Nonlinear model-based feedforward control of distillation columns

1995 ◽  
Vol 18 (3) ◽  
pp. 178-182 ◽  
Author(s):  
Johannes Broll ◽  
Armin Rix ◽  
Horst Gelbe
Author(s):  
Marcello Canova ◽  
Joseph Porembski ◽  
Kris Sevel ◽  
Yann Guezennec ◽  
Steve Yurkovich

The coupling of an internal combustion engine with a starter/alternator is one of the most easily realizable hybrid electric vehicle configurations to achieve significant fuel economy savings in urban driving. A successful implementation of the starter alternator technology includes controlling the electric motor to start and stop the engine quickly and smoothly, without compromising the vehicle noise, vibration and harshness (NVH) signature. The issue becomes more critical in the case of Diesel hybrids, as the peak compression torque is much larger than in automotive spark ignition engines. This paper presents a model-based approach in control design for engine start/stop operations with a belted starter/alternator. Starting from previous modeling and experimental results, a nonlinear model of a belted starter/alternator coupled with a Diesel engine is developed for control algorithm development. With the introduction of a feed-forward control action proportional to the instantaneous engine torque, the starter/alternator controller is capable of consistently reducing the large torque fluctuations during the engine start. With this feedforward control action, the engine start control problem can be translated into a simpler disturbance rejection problem, given a prescribed speed trajectory. This facilitates a linearization of the complex nonlinear model to produce a control-oriented model on which feedback control can be designed. Using the control-oriented model thus developed, different linear control designs have been developed and compared. Further, a robustness study is conducted to evaluate the effect of noise and uncertainties common to such systems. The final results are tested on the original nonlinear truth model, demonstrating the capability of starting and stopping the engine with very limited torque and speed fluctuations.


2004 ◽  
Vol 37 (12) ◽  
pp. 627-631
Author(s):  
Takamasa Yumoto ◽  
Tetsuya Ohtani ◽  
Hiromitsu Ohmori

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 388
Author(s):  
Waheed Ur Rehman ◽  
Xinhua Wang ◽  
Yiqi Cheng ◽  
Yingchun Chen ◽  
Hasan Shahzad ◽  
...  

Research in the field of tribo-mechatronics has been gaining popularity in recent decades. The objective of the current research is to improve static/dynamics characteristics of hydrostatic bearings. Hydrostatic bearings always work in harsh environmental conditions that effect their performance, and which may even result in their failure. The current research proposes a mathematical model-based system for hydrostatic bearings that helps to improve its static/dynamic characteristics under varying conditions of performance-influencing variables such as temperature, spindle speed, external load, and clearance gap. To achieve these objectives, the capillary restrictors are replaced with servo valves, and a mathematical model is developed along with robust control design systems. The control system consists of feedforward and feedback control techniques that have not been applied before for hydrostatic bearings in the published literature. The feedforward control tries to remove a disturbance before it enters the system while feedback control achieves the objective of disturbance rejection and improves steady-state characteristics. The feedforward control is a trajectory-based controller and the feedback controller is a sliding mode controller with a PID sliding surface. The particle swarm optimization algorithm is used to tune the 6-dimensional vector of the tuning parameters with multi-objective performance criteria. Numerical investigations have been carried out to check the performance of the proposed system under varying conditions of viscosity, clearance gap, external load and the spindle speed. The comparison of our results with the published literature shows the effectiveness of the proposed system.


Energy ◽  
2022 ◽  
pp. 123115
Author(s):  
Fang Liu ◽  
Qiu Mo ◽  
Yongwen Yang ◽  
Pai Li ◽  
Shuai Wang ◽  
...  

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