Ferroelectric materials are characterized by their ability to exhibit spontaneous electric polarization, which can be reversed by an external electric field. This property has made them indispensable in applications s...
Ferroelectric materials are characterized by their ability to exhibit spontaneous electric polarization, which can be reversed by an external electric field. This property has made them indispensable in applications such as non-volatile memories, capacitors, and sensors.
The importance of Model Predictive control(MPC)has significant applications in the agricultural industry,more specifically for greenhouse’s control ***,the complexity of the greenhouse and its limited prior knowledge...
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The importance of Model Predictive control(MPC)has significant applications in the agricultural industry,more specifically for greenhouse’s control ***,the complexity of the greenhouse and its limited prior knowledge prevent an exact mathematical description of the *** methods provide a promising solution to this issue through their capacity to identify the system’s comportment using the fit between model output and observed *** this paper,we introduce an application of Constrained Model Predictive control(CMPC)for a greenhouse temperature and relative *** this purpose,two Multi Input Single Output(MISO)systems,using Numerical Subspace State Space System Identification(N4SID)algorithm,are firstly suggested to identify the temperature and the relative humidity comportment to heating and ventilation *** this sense,linear state space models were adopted in order to evaluate the robustness of the control *** the system is identified,the MPC technique is applied for the temperature and the humidity *** results show that the regulation of the temperature and the relative humidity under constraints was guaranteed,both parameters respect the ranges 15℃≤T_(int)≤30℃and 50%≤H_(int)≤70%*** the other hand,the control signals uf and uh applied to the fan and the heater,respect the hard constraints notion,the control signals for the fan and the heater did not exceed 0≤uf≤4.3 Volts and 0≤uh≤5 Volts,respectively,which proves the effectiveness of the MPC and the tracking ***,we show that with the proposed technique,using a new optimization toolbox,the computational complexity has been significantly *** greenhouse in question is devoted to Schefflera Arboricola cultivation.
The presence of long-range interactions is crucial in distinguishing between abstract complex networks and wave *** photonics,because electromagnetic interactions between optical elements generally decay rapidly with ...
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The presence of long-range interactions is crucial in distinguishing between abstract complex networks and wave *** photonics,because electromagnetic interactions between optical elements generally decay rapidly with spatial distance,most wave phenomena are modeled with neighboring interactions,which account for only a small part of conceptually possible ***,we explore the impact of substantial long-range interactions in topological *** demonstrate that a crystalline structure,characterized by long-range interactions in the absence of neighboring ones,can be interpreted as an overlapped *** overlap model facilitates the realization of higher values of topological invariants while maintaining bandgap width in photonic topological *** breaking of topology-bandgap tradeoff enables topologically protected multichannel signal processing with broad *** practically accessible system parameters,the result paves the way to the extension of topological physics to network science.
This paper considers the value iteration algorithms of stochastic zero-sum linear quadratic games with unkown ***-policy and off-policy learning algorithms are developed to solve the stochastic zero-sum games,where th...
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This paper considers the value iteration algorithms of stochastic zero-sum linear quadratic games with unkown ***-policy and off-policy learning algorithms are developed to solve the stochastic zero-sum games,where the system dynamics is not *** analyzing the value function iterations,the convergence of the model-based algorithm is *** equivalence of several types of value iteration algorithms is *** effectiveness of model-free algorithms is demonstrated by a numerical example.
With photovoltaic(PV)sources becoming more prevalent in the energy generation mix,transitioning grid-connected PV systems from grid-following(GFL)mode to gridforming(GFM)mode becomes essential for offering self-synchr...
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With photovoltaic(PV)sources becoming more prevalent in the energy generation mix,transitioning grid-connected PV systems from grid-following(GFL)mode to gridforming(GFM)mode becomes essential for offering self-synchronization and active support *** numerous GFM methods have been proposed,the potential of DC voltage control malfunction during the provision of the primary and inertia support in a GFM PV system remains insufficiently *** fill the gap,some main GFM methods have been integrated into PV systems featuring detailed DC source *** conduct a comparative analysis of their performance in active support and DC voltage *** GFM methods such as virtual synchronous machine(VSM)face a significant risk of DC voltage failure in situations like alterations in solar radiation,leading to PV system tripping and jeopardizing local system *** the case of DC GFM methods such as matching control(MC),the active support falls short due to the absence of an accurate and dispatchable droop *** address the issue,a matching synchronous machine(MSM)control method is developed to provide dispatchable active support and enhance the DC voltage dynamics by integrating the MC and VSM control *** active support capability of the PV systems with the proposed method is quantified analytically and verified by numerical simulations and field tests.
This paper proposes a data-driven learning-based approach to predictive control for switched nonlinear systems subject to state and control constraints and external stochastic disturbances. A switched Koopman modeling...
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This paper proposes a data-driven learning-based approach to predictive control for switched nonlinear systems subject to state and control constraints and external stochastic disturbances. A switched Koopman modeling framework is developed, where a multi-mode neural network for state lifting is trained simultaneously with Koopman operators and state reconstruction matrices for all *** framework facilitates the construction of the switched linear Koopman model in a transformed space and effectively captures the dynamics of the original nonlinear system. A switched predictive control strategy is then designed to regulate the switched Koopman model with constrained states and control inputs against both the stochastic disturbances and the uncertainties introduced by the lifting neural network. The proposed control scheme ensures mean-square stability and guarantees boundedness during the online phase. Furthermore, boundedness analysis is performed to determine the bounded set of the original system state across all admissible switching sequences. The effectiveness of the proposed methodology is demonstrated through a case study of a gene regulatory network.
This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking pe...
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This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.
In this paper,the authors consider the inverse problem for the Moore-Gibson-Thompson equation with a memory term and variable diffusivity,which introduce a sort of delay in the dynamics,producing nonlocal effects in *...
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In this paper,the authors consider the inverse problem for the Moore-Gibson-Thompson equation with a memory term and variable diffusivity,which introduce a sort of delay in the dynamics,producing nonlocal effects in *** H¨older stability of simultaneously determining the spatially varying viscosity coefficient and the source term is obtained by means of the key pointwise Carleman estimate for the Moore-Gibson-Thompson *** the sake of generality in mathematical tools,the analysis of this paper is discussed within the framework of Riemannian geometry.
Market participants can only bid with lagged information disclosure under the existing market mechanism,which can lead to information asymmetry and irrational market behavior,thus influencing market *** promote ration...
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Market participants can only bid with lagged information disclosure under the existing market mechanism,which can lead to information asymmetry and irrational market behavior,thus influencing market *** promote rational bidding behavior of market participants and improve market efficiency,a novel electricity market mechanism based on cloudedge collaboration is proposed in this *** market information,called residual demand curve,is published to market participants in real-time on the cloud side,while participants on the edge side are allowed to adjust their bids according to the information disclosure prior to closure *** proposed mechanism can encourage rational bids in an incentive-compatible way through the process of dynamic equilibrium while protecting participants’*** paper further formulates the mathematical model of market equilibrium to simulate the process of each market participant’s strategic bidding behavior towards equilibrium.A case study based on the IEEE 30-bus system shows the proposed market mechanism can effectively guide bidding behavior of market participants,while condensing exchanged information and protecting privacy of participants.
Diabetes mellitus is one of the most common diseases affecting patients of different ages. Diabetes can be controlled if diagnosed as early as possible. One of the serious complications of diabetes affecting the retin...
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