Eigenstructure Assignment for Linear Quadratic Regulator

1996 ◽  
Vol 29 (1) ◽  
pp. 1098-1103
Author(s):  
Y. Ochi ◽  
K. Kanai
Keyword(s):  
Linear Quadratic Regulator ◽  
Eigenstructure Assignment ◽  
Linear Quadratic

Robust eigenstructure assignment using the genetic algorithm and constrained state feedback

1997 ◽  
Vol 211 (1) ◽  
pp. 53-61 ◽  
Author(s):  
T Clarke ◽  
R Davies
Keyword(s):  
Genetic Algorithm ◽  
State Feedback ◽  
Linear Quadratic Regulator ◽  
Eigenstructure Assignment ◽  
Dynamic Feedback ◽  
Linear Quadratic ◽  
Stability Margins ◽  
Lateral Dynamics ◽  
Genetic Algorithm Approach ◽  
Handling Quality

This paper describes a robust eigenstructure assignment methodology for a constrained state feedback problem. The method, which is based upon the linear quadratic regulator and involves the minimization, via the genetic algorithm, of a multiobjective cost function, is applied to L1011 Tristar aircraft lateral dynamics. The design example generates a fixed-gain state feedback solution which shows independent phase margins of 51· in each channel, while exhibiting an eigenstructure close to that desired, lying well within specified handling quality requirements. If two states are made unavailable for feedback, the robustness properties are seriously eroded. When a dynamic feedback compensator is then used, there is a substantial recovery of the robustness. It is concluded that the genetic algorithm approach described here is easy to use and generates good multivariable stability margins.

A Genetic Algorithm Convergence and Models for Eigenstructure Assignment via Linear Quadratic Regulator (LQR)

2008 ◽  
Vol 6 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Joao Viana Fonseca ◽  
Ivanildo Silva Abreu ◽  
Patricia Helena Moraes Rego ◽  
Marlon de Paulo Melo Wolff ◽  
Orlando Fonseca Silva
Keyword(s):  
Genetic Algorithm ◽  
Linear Quadratic Regulator ◽  
Eigenstructure Assignment ◽  
Linear Quadratic ◽  
Algorithm Convergence

A Study on Linear Quadratic Regulator with the Desired Low-Pass Property

2013 ◽  
Vol 133 (12) ◽  
pp. 2167-2175 ◽  
Author(s):  
Katsuhiko Fuwa ◽  
Satoshi Murayama ◽  
Tatsuo Narikiyo
Keyword(s):  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Low Pass

scholarly journals Neural Network Based Contact Force Control Algorithm for Walking Robots

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 287
Author(s):  
Byeongjin Kim ◽  
Soohyun Kim
Keyword(s):  
Neural Network ◽  
Contact Force ◽  
Force Control ◽  
Control Algorithm ◽  
Position Control ◽  
Linear Quadratic Regulator ◽  
Walking Robots ◽  
Test Model ◽  
Linear Quadratic ◽  
Contact Force Control

Walking algorithms using push-off improve moving efficiency and disturbance rejection performance. However, the algorithm based on classical contact force control requires an exact model or a Force/Torque sensor. This paper proposes a novel contact force control algorithm based on neural networks. The proposed model is adapted to a linear quadratic regulator for position control and balance. The results demonstrate that this neural network-based model can accurately generate force and effectively reduce errors without requiring a sensor. The effectiveness of the algorithm is assessed with the realistic test model. Compared to the Jacobian-based calculation, our algorithm significantly improves the accuracy of the force control. One step simulation was used to analyze the robustness of the algorithm. In summary, this walking control algorithm generates a push-off force with precision and enables it to reject disturbance rapidly.

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