Flocking of Multi-Agent Systems Using a Unified Optimal Control Approach

2013 ◽  
Vol 135 (6) ◽  
Author(s):  
Jianan Wang ◽  
Ming Xin
Keyword(s):  
Optimal Control ◽  
Cost Function ◽  
Distributed Feedback ◽  
Control Law ◽  
Multi Agent Systems ◽  
Optimal Control Strategy ◽  
Control Approach ◽  
Control Framework ◽  
Multi Agent ◽  
Optimal Control Approach

In this paper, the multi-agent flocking problem is investigated in a unified optimal control framework. The flocking characteristics, such as velocity alignment, navigation, cohesion, and collision/obstacle avoidance, are accomplished by formulating them into respective cost function terms. The resultant nonquadratic cost function poses a challenging optimal control problem. A novel inverse optimal control strategy is adopted to derive an analytical optimal control law. The optimality and asymptotic stability are proved and the distributed feedback control law only requires local information to achieve the flocking behaviors. Various simulation scenarios are used to demonstrate the effectiveness of the optimal flocking algorithm.

scholarly journals Optimal Control Approach to Lambert’s Problem and Gibbs’ Method

2020 ◽  
Vol 10 (7) ◽  
pp. 2419
Author(s):  
Minjeong Kim ◽  
Sungsu Park
Keyword(s):  
Optimal Control ◽  
Pseudospectral Method ◽  
Orbital Energy ◽  
Control Approach ◽  
Control Framework ◽  
Lambert’S Problem ◽  
Computation Algorithm ◽  
Lambert's Problem ◽  
Energy Computation ◽  
Optimal Control Approach

This paper presents the optimal control approach to solve both Lambert’s problem and Gibbs’ method, which are commonly used for preliminary orbit determination. Lambert’s problem is reinterpreted with Hamilton’s principle and is converted to an optimal control problem. Various extended Lambert’s problems are formulated by modifying the weighting and constraint settings within the optimal control framework. Furthermore, Gibbs’ method is also converted to an extended Lambert’s problem with two position vectors and one orbit energy with the help of the proposed orbital energy computation algorithm. The proposed extended Lambert’s problem and Gibbs’ method are numerically solved with the Lobatto pseudospectral method, and their accuracies are verified by numerical simulations.

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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