In this paper, we consider nonconvex optimization problems with nonlinear equality constraints. We assume that the objective function and the functional constraints are locally smooth. To solve this problem, we introd...
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Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems. However, we show that the current SRG analysis suffers from some pitfalls that limit its applicabi...
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A method for diagnosing unsteady modes of electrohydraulic complex electromechanical systems based on monitoring of energy processes as part of the variable-frequency electric drive of the pump has been developed. It ...
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We present a local minimax lower bound on the excess cost of designing a linear-quadratic controller from offline data. The bound is valid for any offline exploration policy that consists of a stabilizing controller a...
We present a local minimax lower bound on the excess cost of designing a linear-quadratic controller from offline data. The bound is valid for any offline exploration policy that consists of a stabilizing controller and an energy bounded exploratory input. The derivation leverages a relaxation of the minimax estimation problem to Bayesian estimation, and an application of van Trees inequality. We show that the bound aligns with system-theoretic intuition. In particular, we demonstrate that the lower bound increases when the optimal control objective value increases. We also show that the lower bound increases when the system is poorly excitable, as characterized by the spectrum of the controllability gramian of the system mapping the noise to the state and the $\mathcal{H}_{\infty}$ norm of the system mapping the input to the state. We further show that for some classes of systems, the lower bound may be exponential in the state dimension, demonstrating exponential sample complexity for learning the linear-quadratic regulator.
This paper proposes and develops a physics-inspired neural network (PiNN) for learning the parameters of commercially implemented adaptive cruise control (ACC) systems in automotive industry. To emulate the core funct...
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The development of modern IT technologies and resources, offer in many economic-industrial applications, efficient solutions for planning and managing of specific activities. New research directions in the field of ma...
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The development of modern IT technologies and resources, offer in many economic-industrial applications, efficient solutions for planning and managing of specific activities. New research directions in the field of management and optimization of supply-customer (SC) systems are defined and evaluated. The paper proposes a management model based on a causal graph structure, which expresses the connection and interdependence between the two entities involved in the specific activities of the field, the suppliers of goods and services and the consumers of these goods and products. Information related to production and storage capacity, up-to-date requirements for customer needs, delivery planning, production and consumption dynamics are considered. The transport between the actors involved in the system is an important component with weight in the costs of supply-sale activities. The optimal solution for the supply-customer transport system is proposed based on different strategies of game theory.
This work presents a methodology to analyze the hybridization use of fuel cells, batteries, and combustion engines to supply the power needed for flight in all the phases. The analysis is performed on a case study ana...
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Typical autonomous driving systems are a combination of machine learning algorithms (often involving neural networks) and classical feedback controllers. Whilst significant progress has been made in recent years on th...
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Operational loads have both static and dynamic characteristics. Dynamic loads occur during the operation of the considered mechanism, both during acceleration and deceleration periods, as well as during steady motion ...
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This work is concerned with interconnected networks with non-identical subsystems. We investigate the output consensus of the network where the dynamics are subject to external disturbance and/or reference input. For ...
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