Optimal control law in state-space formalism for eXtreme Adaptive Optics

2005 ◽  
Author(s):  
Brice Le Roux ◽  
Marcel Carbillet
Keyword(s):  
Optimal Control ◽  
State Space ◽  
Adaptive Optics ◽  
Control Law ◽  
Space Formalism

Kalman-filter-based optimal control law for star-oriented and layer-oriented multiconjugate adaptive optics

2004 ◽  
Author(s):  
Brice Le Roux ◽  
Roberto Ragazzoni ◽  
Carmelo Arcidiacono ◽  
Jean-Marc Conan ◽  
Caroline Kulcsar ◽  
...  
Keyword(s):  
Optimal Control ◽  
Kalman Filter ◽  
Adaptive Optics ◽  
Control Law

Optimal control law for multiconjugate adaptive optics

2003 ◽  
Author(s):  
Brice Le Roux ◽  
Jean-Marc Conan ◽  
Caroline Kulcsar ◽  
Henri-Francois Raynaud ◽  
Laurent M. Mugnier ◽  
...  
Keyword(s):  
Optimal Control ◽  
Adaptive Optics ◽  
Control Law

Optimal control law for classical and multiconjugate adaptive optics

2004 ◽  
Vol 21 (7) ◽  
pp. 1261 ◽  
Author(s):  
Brice Le Roux ◽  
Caroline Kulcsár ◽  
Laurent M. Mugnier ◽  
Thierry Fusco ◽  
Henri-François Raynaud ◽  
...  
Keyword(s):  
Optimal Control ◽  
Adaptive Optics ◽  
Control Law

Fuzzy Control of Structure for Semi-Active Friction Damper Using GA

2006 ◽  
Author(s):  
Hong-Nan Li ◽  
Dahai Zhao
Keyword(s):  
Optimal Control ◽  
State Space ◽  
Control Strategy ◽  
Fuzzy Model ◽  
The State ◽  
Effective Control ◽  
Control Law ◽  
Control Force ◽  
Friction Damper ◽  
Active Friction

The motion of friction dampers, either passive or semi-active, involves sticking and slipping phases. The idea for increasing the performance of semi-active friction damper is to maintain its motion in the slipping phase as much as possible, since energy is dissipated during the slipping phase rather than the sticking phase. The effectiveness of semi-active friction damper depends on the control strategy used. Because of nonlinear characteristic of the friction damper, the establishment of an effective control strategy is a challenging effort. In optimal control theory, the bang-bang is a class of classical control laws. However, when applied to real structure control, it will produce some problems. One of disadvantages is that differential equation has to be solved on-line during the control process, which will lead to time delay and instability to the control system. The other is that the undesirable spikes will emerge near the origin of the state space due to high speed switching of the control force. In this paper, a new strategy based on the T-S fuzzy model and modified bang-bang algorithm is proposed. First, the theory of the T-S fuzzy model is briefly introduced. Next, the modified bang-bang control law is reviewed. Then, the implementation procedure of the proposed control method is detailed for description, and the optimal control force in the consequent part of the T-S model is achieved by the genetic algorithm. Finally, on the establishment of the semi-active control law, the approach here is applied to the vibration control of a three story building with a semi-active friction damper. Numerical simulation results indicate that the proposed control strategy not only effectively reduce the chattering effect as the responses of the structure cross through the zero points in the state space but also is adaptive to varying excitations from weak and strong earthquakes.

scholarly journals Adaptive Optimal Robust Control for Uncertain Nonlinear Systems Using Neural Network Approximation in Policy Iteration

2021 ◽  
Vol 11 (5) ◽  
pp. 2312
Author(s):  
Dengguo Xu ◽  
Qinglin Wang ◽  
Yuan Li
Keyword(s):  
Neural Network ◽  
Optimal Control ◽  
Robust Control ◽  
Nonlinear Systems ◽  
Policy Iteration ◽  
Control Law ◽  
Globally Asymptotically Stable ◽  
Control Approach ◽  
Input Uncertainties ◽  
Theoretical Results

In this study, based on the policy iteration (PI) in reinforcement learning (RL), an optimal adaptive control approach is established to solve robust control problems of nonlinear systems with internal and input uncertainties. First, the robust control is converted into solving an optimal control containing a nominal or auxiliary system with a predefined performance index. It is demonstrated that the optimal control law enables the considered system globally asymptotically stable for all admissible uncertainties. Second, based on the Bellman optimality principle, the online PI algorithms are proposed to calculate robust controllers for the matched and the mismatched uncertain systems. The approximate structure of the robust control law is obtained by approximating the optimal cost function with neural network in PI algorithms. Finally, in order to illustrate the availability of the proposed algorithm and theoretical results, some numerical examples are provided.

Optimal control techniques for the adaptive optics system of the LBT

2008 ◽  
Author(s):  
G. Agapito ◽  
F. Quiros-Pacheco ◽  
P. Tesi ◽  
S. Esposito ◽  
M. Xompero
Keyword(s):  
Optimal Control ◽  
Adaptive Optics ◽  
Control Techniques ◽  
Adaptive Optics System
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