Loading...
Search for:
farjadnasab--milad
0.032 seconds
Optimal Control of Unknown Interconnected Systems via Distributed Learning
, M.Sc. Thesis Sharif University of Technology ; Babazadeh, Maryam (Supervisor)
Abstract
This thesis addresses the problem of optimal distributed control of unknown interconnected systems. In order to deal with this problem, a data-driven learning framework for finding the optimal centralized and the suboptimal distributed controllers has been developed via convex optimization.First of all, the linear quadratic regulation (LQR) problem is formulated into a nonconvex optimization problem. Using Lagrangian duality theories, a semidefinite program is then developed that requires information about the system dynamics. It is shown that the optimal solution to this problem is independent of the initial conditions and represents the Q-function, an important concept in reinforcement...
Model-free LQR design by Q-function learning
, Article Automatica ; Volume 137 , 2022 ; 00051098 (ISSN) ; Babazadeh, M ; Sharif University of Technology
Elsevier Ltd
2022
Abstract
Reinforcement learning methods such as Q-learning have shown promising results in the model-free design of linear quadratic regulator (LQR) controllers for linear time-invariant (LTI) systems. However, challenges such as sample-efficiency, sensitivity to hyper-parameters, and compatibility with classical control paradigms limit the integration of such algorithms in critical control applications. This paper aims to take some steps towards bridging the well-known classical control requirements and learning algorithms by using optimization frameworks and properties of conic constraints. Accordingly, a new off-policy model-free approach is proposed for learning the Q-function and designing the...
Does the short-term boost of renewable energies guarantee their stable long-term growth? Assessment of the dynamics of feed-in tariff policy
, Article Renewable Energy ; Volume 159 , October , 2020 , Pages 1252-1268 ; Hamed Shakouri, G ; Mashayekhi, A. N ; Kazemi, A ; Sharif University of Technology
Elsevier Ltd
2020
Abstract
Feed-in tariff (FiT) is one of the most efficient ways that many governments throughout the world use to stimulate investment in renewable energies (REs) technology. For governments, financial management of the policy could be challenging as it needs a considerable amount of budget to support RE producers during the long remuneration period. In this paper, it has been illuminated that the early growth of REs capacity could be a temporary boost. And the socio-economic structure of the system will backlash the policy if some social mechanisms are not considered. Social tolerance for paying REs tax and potential investors’ trust emanated from budget-related mechanisms -which have rarely been...