系统与控制
Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems, where Linear Time-Invariant (LTI) systems are the fundamental building block. To analyze feedback loops with unstable LTI…
Deep Model Predictive Control (Deep MPC) is an evolving field that integrates model predictive control and deep learning. This manuscript is focused on a particular approach, which employs deep neural network in the loop with MPC. This…
The introduction of 5G New Radio networks with massive MIMO technology has complicated electromagnetic field exposure assessments for radiation protection. Massive MIMO transmission enables beamforming, beam steering, and spatial…
The large penetration of distributed generations impacts both the secondary low-voltage (LV) and the primary medium-voltage (MV) segments of the distribution network. Optimizing power flow calculations for the integrated MV/LV networks is…
As the world shifts towards utilizing natural resources for electricity generation, there is need to enhance forecasting systems to guarantee a stable electricity provision and to incorporate the generated power into the network systems.…
The paper addresses the problem of estimating robustly the external load torque in rotary actuator systems, when only the generated motor drive torque and angular displacement are the available input and output. We compare, theoretically…
Cyber-physical systems of systems (CPSoS) are highly complex, dynamic environments in which technical, cybernetic and organisational subsystems interact closely with one another. Dynamic, continuously adaptable resilience is required to…
Semantic communication can improve transmission efficiency by focusing on task-relevant information. However, under packet-based communication protocols, any error typically results in the loss of an entire packet, making semantic…
Low-frequency oscillations remain a major challenge in bulk power systems with high renewable penetration, long lines, and large loads. Existing damping strategies based on power modulation of high voltage DC (HVDC) or energy storage, are…
Autonomous Underwater Vehicles (AUVs) are indispensable for marine exploration; yet, their control is hindered by nonlinear hydrodynamics, time-varying disturbances, and localization uncertainty. Traditional controllers provide only limited…
Performance ratio (PR) is a established measure of efficiency of photovoltaic (PV) systems. While previous research demonstrated the effects of meteorological and technical variables on PR, a gap persists in the literature on which…
A hemispherical multilayer wide-band (7-13 GHz) band-pass frequency selective surface (FSS) is reported. A new design technique based on a Goldberg discretization and unit cell scaling technique is introduced to accommodate the curved…
We present a load frequency control strategy deploying a decentralized robust global integral terminal sliding mode control (GITSMC) method to maintain stable frequency and tie-line power in multi-area interconnected microgrids with…
This paper presents a physics-informed machine learning approach for synthesizing optimal feedback control policy for infinite-horizon optimal control problems by solving the Hamilton-Jacobi-Bellman (HJB) partial differential equation(PDE).…
The increasing penetration of renewable energy leads to a continuous reduction in system inertia, for which conventional synchronization criteria based solely on frequency consistency can no longer accurately capture the coupled dynamics of…
The interest in vertical farming arises from its ability to ensure consistent, high-quality, and pest-free vegetable production while supporting synergies with energy systems and urban development. While previous studies have assessed…
This paper presents a real-time capable algorithm for the learning of Gaussian Processes (GP) for submodels. It extends an existing recursive Gaussian Process (RGP) algorithm which requires a measurable output. In many applications,…
Long time-duration low-thrust nonlinear optimal spacecraft trajectory global search is a computationally and time expensive problem characterized by clustering patterns in locally optimal solutions. During preliminary mission design,…
In this work, we focus on the design of optimal controllers that must comply with an information structure. State-of-the-art approaches do so based on the H2 or Hinfty norm to minimize the expected or worst-case cost in the presence of…
We propose a novel recursive utility for controlling stochastic processes under risk and uncertainty. Our formulation uses a robustified Orlicz risk that can evaluate risk and uncertainty simultaneously. We focus on a control problem of a…