Linear Quadratic-Model Algorithmic Control method: a controller design method combining the Linear Quadratic method and the Model Algorithmic Control algorithm

1989 ◽  
Vol 28 (2) ◽  
pp. 178-186 ◽  
Author(s):  
Chun Min Cheng
Keyword(s):  
Control Algorithm ◽  
Control Method ◽  
Controller Design ◽  
Design Method ◽  
Quadratic Model ◽  
Linear Quadratic ◽  
Linear Quadratic Model ◽  
Model Algorithmic Control

Preview Control for Vehicle Lateral Guidance in Highway Automation

1993 ◽  
Vol 115 (4) ◽  
pp. 679-686 ◽  
Author(s):  
Huei Peng ◽  
Masayoshi Tomizuka
Keyword(s):  
Frequency Domain ◽  
Control Algorithm ◽  
Controller Design ◽  
Feedforward Control ◽  
Design Method ◽  
Tracking Error ◽  
Ride Quality ◽  
Linear Quadratic ◽  
Preview Control ◽  
Control Approach

The continuous time deterministic optimal preview control algorithm is applied to the lateral guidance of a vehicle for an automated highway. In the lateral guidance problem, the front wheel steering angle of the vehicle is controlled so that the vehicle follows the center for a lane with small tracking error and maintains good ride quality simultaneously. A preview control algorithm is obtained by minimizing a quadratic performance index which includes terms representing the passenger ride quality as well as the lateral tracking error, each of these terms is multiplied by a frequency dependent weight. This design method is known as a frequency shaped linear quadratic (FSLQ) optimal control approach. It permits incorporating frequency domain design specifications such as high frequency robustness and ride quality in the optimal controller design. It is shown that the optimal preview control law consists of a feedback control term and two feedforward control terms. The feedback term is exactly the same as that of traditional LQ control algorithm. The feedforward preview control action significantly improves the tracking performance and ride quality. Frequency-domain analyses, as well as numerical simulation results, show the improvements achieved by using the preview control algorithm in both the frequency and time domains.

scholarly journals Simulating Radiotherapy Effect in High-Grade Glioma by Using Diffusive Modeling and Brain Atlases

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Alexandros Roniotis ◽  
Kostas Marias ◽  
Vangelis Sakkalis ◽  
Georgios C. Manikis ◽  
Michalis Zervakis
Keyword(s):  
High Grade Glioma ◽  
Quadratic Model ◽  
Normal Brain ◽  
Linear Quadratic ◽  
Linear Quadratic Model ◽  
Diffusive Model ◽  
Glioma Model ◽  
Modern Application ◽  
Diffusion Tensors ◽  
Brain Atlases

Applying diffusive models for simulating the spatiotemporal change of concentration of tumour cells is a modern application of predictive oncology. Diffusive models are used for modelling glioblastoma, the most aggressive type of glioma. This paper presents the results of applying a linear quadratic model for simulating the effects of radiotherapy on an advanced diffusive glioma model. This diffusive model takes into consideration the heterogeneous velocity of glioma in gray and white matter and the anisotropic migration of tumor cells, which is facilitated along white fibers. This work uses normal brain atlases for extracting the proportions of white and gray matter and the diffusion tensors used for anisotropy. The paper also presents the results of applying this glioma model on real clinical datasets.

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