Application of Supervisory Model Predictive Controller in Polymer Extrusion Process

2020 ◽  
Author(s):  
M.Y. Elmahdawy ◽  
M. Abdelgeliel ◽  
Alaa eldin Khalil
Keyword(s):  
Extrusion Process ◽  
Polymer Extrusion ◽  
Model Predictive Controller ◽  
Predictive Controller

Enlarging the region of stability in robust model predictive controller based on dual-mode control

2021 ◽  
pp. 014233122110123
Author(s):  
Fatemeh Khani ◽  
Mohammad Haeri
Keyword(s):  
Stability Region ◽  
Linear Matrix ◽  
Input State ◽  
Dual Mode ◽  
Model Predictive Controller ◽  
Mode Control ◽  
Robust Model ◽  
Output Constraints ◽  
Predictive Controller ◽  
The Stability

Industrial processes are inherently nonlinear with input, state, and output constraints. A proper control system should handle these challenging control problems over a large operating region. The robust model predictive controller (RMPC) could be an linear matrix inequality (LMI)-based method that estimates stability region of the closed-loop system as an ellipsoid. This presentation, however, restricts confident application of the controller on systems with large operating regions. In this paper, a dual-mode control strategy is employed to enlarge the stability region in first place and then, trajectory reversing method (TRM) is employed to approximate the stability region more accurately. Finally, the effectiveness of the proposed scheme is illustrated on a continuous stirred tank reactor (CSTR) process.

scholarly journals A Perception-Aware Flatness-Based Model Predictive Controller for Fast Vision-Based Multirotor Flight

2020 ◽  
Vol 53 (2) ◽  
pp. 9412-9419
Author(s):  
Melissa Greeff ◽  
Timothy D. Barfoot ◽  
Angela P. Schoellig
Keyword(s):  
Model Predictive Controller ◽  
Predictive Controller

scholarly journals Research on Model Predictive Control for Automobile Active Tilt Based on Active Suspension

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 671
Author(s):  
Jialing Yao ◽  
Meng Wang ◽  
Zhihong Li ◽  
Yunyi Jia
Keyword(s):  
Load Transfer ◽  
Ride Comfort ◽  
Active Suspension ◽  
Path Tracking ◽  
Roll Angle ◽  
Lateral Acceleration ◽  
Vehicle Speed ◽  
Model Predictive Controller ◽  
Advantages And Disadvantages ◽  
Predictive Controller

To improve the handling stability of automobiles and reduce the odds of rollover, active or semi-active suspension systems are usually used to control the roll of a vehicle. However, these kinds of control systems often take a zero-roll-angle as the control target and have a limited effect on improving the performance of the vehicle when turning. Tilt control, which actively controls the vehicle to tilt inward during a curve, greatly benefits the comprehensive performance of a vehicle when it is cornering. After analyzing the advantages and disadvantages of the tilt control strategies for narrow commuter vehicles by combining the structure and dynamic characteristics of automobiles, a direct tilt control (DTC) strategy was determined to be more suitable for automobiles. A model predictive controller for the DTC strategy was designed based on an active suspension. This allowed the reverse tilt to cause the moment generated by gravity to offset that generated by the centrifugal force, thereby significantly improving the handling stability, ride comfort, vehicle speed, and rollover prevention. The model predictive controller simultaneously tracked the desired tilt angle and yaw rate, achieving path tracking while improving the anti-rollover capability of the vehicle. Simulations of step-steering input and double-lane change maneuvers were performed. The results showed that, compared with traditional zero-roll-angle control, the proposed tilt control greatly reduced the occupant’s perceived lateral acceleration and the lateral load transfer ratio when the vehicle turned and exhibited a good path-tracking performance.

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