We study the computation of the global generalized Nash equilibrium (GNE) for a class of non-convex multi-player games, where players' actions are subject to both local and coupling constraints. Due to the non-con...
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ISBN:
(数字)9798350354409
ISBN:
(纸本)9798350354416
We study the computation of the global generalized Nash equilibrium (GNE) for a class of non-convex multi-player games, where players' actions are subject to both local and coupling constraints. Due to the non-convex payoff functions, we employ canonical duality to reformulate the setting as a complementary problem. Under given conditions, we reveal the relation between the stationary point and the global GNE. According to the convex-concave properties within the complementary function, we propose a continuous-time mirror descent to compute GNE by generating functions in the Bregman divergence and the damping-based design. Then, we devise several Lyapunov functions to prove that the trajectory along the dynamics is bounded and convergent.
Concerns over the energy and environmental crisis are driving the strategic integration of distributed generators (DGs) in power systems, hastening the shift to sustainable energy. Microgrids (MGs) emerged as self-rel...
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ISBN:
(数字)9798350318265
ISBN:
(纸本)9798350318272
Concerns over the energy and environmental crisis are driving the strategic integration of distributed generators (DGs) in power systems, hastening the shift to sustainable energy. Microgrids (MGs) emerged as self-reliant, localized power solutions for DGs integration, enhancing grid performance and reliability by allowing grid-connected and islanded modes of operation. Moreover, the dc nature of many DGs and household devices, together with the progress in power electronics, have shifted research from conventional ac MGs towards dc and hybrid ac/dc MGs, which increase the complexity and the number of control scenarios. Therefore, the MG control environment require advanced data-driven algorithms to overcome the stochasticity and non-linear characteristics of MGs systems. In this context, artificial intelligence (AI) techniques demonstrate high potential for enhancing the control and operation in the dynamic MG environment. This paper reviews the most recent research effort regarding the application of AI-based technology in the hierarchical control structure for ac, dc and hybrid ac/dc MG architectures.
This study aims to compare the effectiveness of different Pharmacokinetic-Pharmacodynamic (PK-PD) models for administering Propofol and Remifentanil, two critical agents in anesthesia. Initially, different PK models w...
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ISBN:
(数字)9783907144107
ISBN:
(纸本)9798331540920
This study aims to compare the effectiveness of different Pharmacokinetic-Pharmacodynamic (PK-PD) models for administering Propofol and Remifentanil, two critical agents in anesthesia. Initially, different PK models were introduced: one for Propofol based on the Schnider model and another for Remifentanil using the Minto model. Alternatively, both drugs were modeled using the Eleveld models. The PK-PD models were integrated into a closed-loop control system using model predictive control (MPC) with disturbances to control the Bispectral index (BIS) and the Richmond Agitation Sedation Scale (RASS). The methodology involved simulating the anesthetic agents in the open-source patient simulator (2 inputs, 2 outputs) with 12 patient datasets in a controlled environment to simulate the patient response variability, allowing for a detailed analysis of the model's performance in maintaining optimal drug concentrations. The primary focus was on the system's ability to adapt to surgical disturbances, a key challenge in anesthesia management, and whether a different modeling of drugs can have an impact on their effects. The results indicated significant differences in the performance of the two models configurations. The Eleveld model for Propofol showed less usage of drugs to maintain the desired BIS value. Concluding that this comparative analysis offers a valuable reference for selecting appropriate modeling approaches in the development of advanced control strategies in anesthesia.
The increased demand for active control of engines has made the study of high-frequency response actuators increasingly important, and actuators based on magnetostrictive materials are promising for a wide range of ap...
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In this paper, we develop a distributionally robust model predictive control framework for the control of wind farms with the goal of power tracking and mechanical stress reduction of the individual wind turbines. We ...
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Inthis paper many improvements in dealing with energy quality issues that could arise in electrical drive systems using asynchronous machines are presented. A series active power filter is used in electrical drive sys...
Inthis paper many improvements in dealing with energy quality issues that could arise in electrical drive systems using asynchronous machines are presented. A series active power filter is used in electrical drive systems with induction motors to reduce harmonic current and voltage. We also propose a variety of active power filters with hysteresis current value control. Lastly, some experimental results for an electrical drive system utilizing an induction motor and a PWM converter are provided. These findings are followed by a discussion of the system's energy quality issues.
It is demonstrated that the electrohydraulic complex is a complex system of interconnected electromechanical and hydraulic equipment with low controllability of parameters in non-stationary modes. The estimation of co...
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In this paper, we investigate the problem of distributed load balancing under network capacity constraints, where the participating agents cooperate with the aim of jointly minimizing both the workload disparity among...
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In this paper, we investigate the problem of distributed load balancing under network capacity constraints, where the participating agents cooperate with the aim of jointly minimizing both the workload disparity among them as well as the overall workload transfer. Classical approaches for asymptotic convergence to the global optimum in a distributed fashion typically assume timely exchange of information between neighboring agents of a given multi-agent system. This assumption is not necessarily valid in practical settings due to non-commensurate (heterogeneous) communication and processing delays that might affect transmissions at different times. More specifically, we consider what effect multiple heterogeneous time-varying delays, among the agents can have on the distributed load balancing problem. We show that the distributed load balancing problem under bounded heterogeneous time-varying delays is globally asymptotically stable, but the rate of convergence is affected. Bounds on the convergence rate are provided with respect to an upper bound on the delays. Simulation examples are provided to show the validity and performance of our theoretical results.
This paper proposes a hybrid method using Genetic Algorithm and Transfer Learning in Deep Neural Networks for gesture classification using surface EMG (sEMG) signals. The goal is to develop efficient Convolutional Neu...
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ISBN:
(数字)9798350394276
ISBN:
(纸本)9798350394283
This paper proposes a hybrid method using Genetic Algorithm and Transfer Learning in Deep Neural Networks for gesture classification using surface EMG (sEMG) signals. The goal is to develop efficient Convolutional Neural Networks (CNN) that can be implemented in real-time situations to recognize gestures with a small number of EMG sensors. By “efficient” we mean good classification accuracy, short data acquisition time, and short CNN training time. The dataset to verify the performance of the proposed algorithm is created in our laboratory. We compare the performance of CNNs trained (a) from scratch, (b) using transfer learning, and (c) using transfer learning with GA-optimized parameters. The performance of the proposed hybrid method shows a good performance.
This paper investigates the stereographic projection of points along the Nyquist plots of single input single output (SISO) linear time invariant (LTI) systems subject to probabilistic uncertainty. At each frequency, ...
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ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
This paper investigates the stereographic projection of points along the Nyquist plots of single input single output (SISO) linear time invariant (LTI) systems subject to probabilistic uncertainty. At each frequency, there corresponds a complex-valued random variable with given probability distribution in the complex plane. The chordal distance between the stereographic projections of this complex value and the corresponding value for a nominal model, as per the well-known ν-Gap metric of Vinnicombe, is also a random quantity. The main result provides the cumulative density function (CDF) of the chordal distance at a given frequency. Such a stochastic distance framework opens up a fresh and a fertile research direction on probabilistic robust control theory.
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