Model Reference Adaptive Controller to regulate steam temperature in distillation process for essential oil extraction

2011 ◽  
Author(s):  
Nurhani Kasuan ◽  
Mohd Nasir Taib ◽  
Mohd Hezri Fazalul Rahiman
Keyword(s):  
Essential Oil ◽  
Adaptive Controller ◽  
Oil Extraction ◽  
Distillation Process ◽  
Steam Temperature ◽  
Model Reference ◽  
Model Reference Adaptive

Manufacturing Process for Extracting Essential Oils from White Pepper (Piper nigrum L.) by Hydrodistillation Technique

2019 ◽  
Vol 298 ◽  
pp. 89-93 ◽  
Author(s):  
Thien Hien Tran ◽  
Thi To Quyen Ngo ◽  
Thi Kim Ngan Tran ◽  
Tri Duc Lam ◽  
Tan Phat Dao ◽  
...  
Keyword(s):  
Essential Oil ◽  
Essential Oils ◽  
Manufacturing Process ◽  
Oil Extraction ◽  
Piper Nigrum ◽  
Optimal Conditions ◽  
Distillation Process ◽  
White Pepper ◽  
Oil Performance

Vietnam is the world's leading country in growing and producing pepper trees. In this study, we attempted the optimization of white pepper essential oil extraction. The obtained oil was then subject to determination of constituent composition via GC-MS method. The essential oil performance achieved 3.6% by hydro-distillation process with optimal conditions (25 grams of fresh pepper, size 18, 120 minutes extraction, 130°C). A total of 23 volatile constituents were identified from the white pepper essential oil, with the major components being 27.4% of Limonene, 3-Carene 22,928%, Sabinene 17,622%, β-pinene 10.068%, α-Pinene 5.426%.

Synthesis Design and Analysis of a Hybrid Controller for Robotic Arms

2016 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Pid Controller ◽  
Adaptive Controller ◽  
Convergence Speed ◽  
Model Reference ◽  
Robotic Arms ◽  
Hybrid Controller ◽  
Comparison Results ◽  
Convergence Performance ◽  
Model Reference Adaptive ◽  
Better Than

In this paper, a hybrid controller for robotic arms is proposed and designed by combining a proportional-integral-derivative controller (PID) and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. The convergence performance of the PID controller, the model reference adaptive controller and the PID+MRAC hybrid controller for 1-DOF and 2-DOF manipulators are compared. The comparison results show that the convergence speed and its performance for the MRAC and the PID+MRAC controllers are better than that of the PID controller, and the convergence performance for the hybrid control is better than that of the MRAC control.

The development of a model reference adaptive controller to control the knee joint of paraplegics

1991 ◽  
Vol 36 (6) ◽  
pp. 683-691 ◽  
Author(s):  
M.S. Hatwell ◽  
B.J. Oderkerk ◽  
C.A. Sacher ◽  
G.F. Inbar
Keyword(s):  
Knee Joint ◽  
Adaptive Controller ◽  
Model Reference ◽  
Model Reference Adaptive

Evaluation of P-Q Controllers for an Injection Moulding Machine

2000 ◽  
Author(s):  
Paul K. Guerrier ◽  
Kevin A. Edge
Keyword(s):  
Injection Moulding ◽  
Adaptive Controller ◽  
Pi Controller ◽  
Hardware In The Loop ◽  
Model Reference ◽  
Industry Standard ◽  
Moulding Machine ◽  
Single Controller ◽  
Pressure Controller ◽  
Model Reference Adaptive

Abstract There are a number of problems surrounding traditional velocity and pressure controllers used on injection moulding machines. Injection moulding machines are also very expensive and full scale testing is often not appropriate at the beginning of new controller evaluation. This paper presents results for a half scale ‘hardware-in-the-loop’ load emulation of the filling and packing phases of injection moulding, suitable for controller evaluation. The problems linked to the current industry standard velocity and pressure controller are discussed along with alternative strategies. Schemes including single controller fuzzy logic and neural network solutions are discussed and ruled out in favour of ones containing separate velocity and pressure controllers. Results for a model reference adaptive pressure controller are presented and compared with those obtained using a closed loop PI controller experimentally and in simulation. Experimentally the model reference adaptive controller outperforms the PI controller but does suffer from gain drift.

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