Further developments in the new approach to boundary condition iteration in optimal control

2010 ◽  
Vol 79 (6) ◽  
pp. 968-976 ◽  
Author(s):  
Rein Luus
Keyword(s):  
Boundary Condition ◽  
Optimal Control ◽  
New Approach

scholarly journals Optimal control of a viscous generalized θ-type dispersive equation with weak dissipation

2020 ◽  
Vol 18 (1) ◽  
pp. 1302-1316
Author(s):  
Guobing Fan ◽  
Zhifeng Yang
Keyword(s):  
Boundary Condition ◽  
Optimal Control ◽  
Weak Solution ◽  
Existence And Uniqueness ◽  
Optimal Solution ◽  
Dispersive Equation ◽  
Weak Dissipation ◽  
Formula Type

Abstract In this paper, we investigate the problem for optimal control of a viscous generalized \theta -type dispersive equation (VG \theta -type DE) with weak dissipation. First, we prove the existence and uniqueness of weak solution to the equation. Then, we present the optimal control of a VG \theta -type DE with weak dissipation under boundary condition and prove the existence of optimal solution to the problem.

scholarly journals Method of evolving junctions: A new approach to optimal control with constraints

Automatica ◽  
2017 ◽  
Vol 78 ◽  
pp. 72-78 ◽  
Author(s):  
Wuchen Li ◽  
Jun Lu ◽  
Haomin Zhou ◽  
Shui-Nee Chow
Keyword(s):  
Optimal Control ◽  
New Approach

scholarly journals USING DYNAMIC NEURAL NETWORKS TO GENERATE CHAOS: AN INVERSE OPTIMAL CONTROL APPROACH

2001 ◽  
Vol 11 (03) ◽  
pp. 857-863 ◽  
Author(s):  
EDGAR N. SANCHEZ ◽  
JOSE P. PEREZ ◽  
GUANRONG CHEN
Keyword(s):  
Neural Networks ◽  
Optimal Control ◽  
Chaotic Attractors ◽  
Control Law ◽  
Inverse Optimal Control ◽  
Dynamic Neural Network ◽  
Dynamic Neural Networks ◽  
New Approach ◽  
Control Approach ◽  
Optimal Control Approach

This Letter suggests a new approach to generating chaos via dynamic neural networks. This approach is based on a recently introduced methodology of inverse optimal control for nonlinear systems. Both Chen's chaotic system and Chua's circuit are used as examples for demonstration. The control law is derived to force a dynamic neural network to reproduce the intended chaotic attractors. Computer simulations are included for illustration and verification.

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