Model-free control of Lorenz chaos using an approximate optimal control strategy

2012 ◽  
Vol 17 (12) ◽  
pp. 4891-4900 ◽  
Author(s):  
Shuai Li ◽  
Yangming Li ◽  
Bu Liu ◽  
Timmy Murray
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Optimal Control Strategy ◽  
Model Free ◽  
Model Free Control

scholarly journals Model-Free Reinforcement Learning for Branching Markov Decision Processes

2021 ◽  
pp. 651-673
Author(s):  
Ernst Moritz Hahn ◽  
Mateo Perez ◽  
Sven Schewe ◽  
Fabio Somenzi ◽  
Ashutosh Trivedi ◽  
...  
Keyword(s):  
Optimal Control ◽  
Reinforcement Learning ◽  
Markov Decision Processes ◽  
Control Strategy ◽  
Natural Extension ◽  
Decision Processes ◽  
Optimal Control Strategy ◽  
Model Free ◽  
Learning Techniques ◽  
Markov Decision

AbstractWe study reinforcement learning for the optimal control of Branching Markov Decision Processes (BMDPs), a natural extension of (multitype) Branching Markov Chains (BMCs). The state of a (discrete-time) BMCs is a collection of entities of various types that, while spawning other entities, generate a payoff. In comparison with BMCs, where the evolution of a each entity of the same type follows the same probabilistic pattern, BMDPs allow an external controller to pick from a range of options. This permits us to study the best/worst behaviour of the system. We generalise model-free reinforcement learning techniques to compute an optimal control strategy of an unknown BMDP in the limit. We present results of an implementation that demonstrate the practicality of the approach.

Application of Optimal Control Strategy to Converter Gas Recovery System

2012 ◽  
Vol 38 (6) ◽  
pp. 1017 ◽  
Author(s):  
Jia-Yan ZHANG ◽  
Zhong-Hai MA ◽  
Xiao-Bin QIAN ◽  
Shao-Ming LI ◽  
Jia-Hong LANG
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Optimal Control Strategy ◽  
Gas Recovery ◽  
Recovery System ◽  
Converter Gas

Optimal control strategy for cancer remission using combinatorial therapy: A mathematical model-based approach

2021 ◽  
Vol 145 ◽  
pp. 110789
Author(s):  
Parthasakha Das ◽  
Samhita Das ◽  
Pritha Das ◽  
Fathalla A. Rihan ◽  
Muhammet Uzuntarla ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Optimal Control ◽  
Control Strategy ◽  
Optimal Control Strategy ◽  
Combinatorial Therapy ◽  
Model Based ◽  
Cancer Remission

scholarly journals Development of an Optimal Start Control Strategy for a Variable Refrigerant Flow (VRF) System

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 271
Author(s):  
Yusung Lee ◽  
Woohyun Kim
Keyword(s):  
Optimal Control ◽  
Control Strategy ◽  
Predictive Performance ◽  
Building Energy ◽  
Data Driven ◽  
Energy Usage ◽  
Optimal Control Strategy ◽  
Save Energy ◽  
Time Required ◽  
Optimal Control Methods

In this study, an optimal control strategy for the variable refrigerant flow (VRF) system is developed using a data-driven model and on-site data to save the building energy. Three data-based models are developed to improve the on-site applicability. The presented models are used to determine the length of time required to bring each zone from its current temperature to the set point. The existing data are used to evaluate and validated the predictive performance of three data-based models. Experiments are conducted using three outdoor units and eight indoor units on site. The experimental test is performed to validate the performance of proposed optimal control by comparing between conventional and optimal control methods. Then, the ability to save energy wasted for maintaining temperature after temperature reaches the set points is evaluated through the comparison of energy usage. Given these results, 30.5% of energy is saved on average for each outdoor unit and the proposed optimal control strategy makes the zones comfortable.

scholarly journals Greedy control of cascading failures in interdependent networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Malgorzata Turalska ◽  
Ananthram Swami
Keyword(s):  
Optimal Control ◽  
Complex Systems ◽  
Control Strategy ◽  
Cascading Failures ◽  
Optimal Control Strategy ◽  
Supercritical Regime ◽  
Interdependent Networks ◽  
Malicious Activity ◽  
Cross System ◽  
Made In

AbstractComplex systems are challenging to control because the system responds to the controller in a nonlinear fashion, often incorporating feedback mechanisms. Interdependence of systems poses additional difficulties, as cross-system connections enable malicious activity to spread between layers, increasing systemic risk. In this paper we explore the conditions for an optimal control of cascading failures in a system of interdependent networks. Specifically, we study the Bak–Tang–Wiesenfeld sandpile model incorporating a control mechanism, which affects the frequency of cascades occurring in individual layers. This modification allows us to explore sandpile-like dynamics near the critical state, with supercritical region corresponding to infrequent large cascades and subcritical zone being characterized by frequent small avalanches. Topological coupling between networks introduces dependence of control settings adopted in respective layers, causing the control strategy of a given layer to be influenced by choices made in other connected networks. We find that the optimal control strategy for a layer operating in a supercritical regime is to be coupled to a layer operating in a subcritical zone, since such condition corresponds to reduced probability of inflicted avalanches. However this condition describes a parasitic relation, in which only one layer benefits. Second optimal configuration is a mutualistic one, where both layers adopt the same control strategy. Our results provide valuable insights into dynamics of cascading failures and and its control in interdependent complex systems.

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