We study the formation of short-term interest rates in the interbank lending market where banks are modeled as agents with bounded rationality. We propose a novel model which is based on bilateral contracts between ri...
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In this paper the control of a platoon with a nonlinear controller under event-triggered communication is investigated. The proposed nonlinear controller is a predecessor-following controller for a certain class of no...
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In this paper the control of a platoon with a nonlinear controller under event-triggered communication is investigated. The proposed nonlinear controller is a predecessor-following controller for a certain class of nonlinear functions. For the event-triggered communication scheme every agent decides based on its own state when it transmits its state information. Therefore, a trigger rule is designed that guarantees exponential convergence of the state error while it excludes Zeno behavior. The results are extended to allow heterogeneous trigger rules under certain conditions. Furthermore the case of heterogeneous controllers is analyzed and exponential convergence and exclusion of Zeno behavior is still guaranteed. The theoretical results of the paper are supported by numerical simulations.
This paper illustrates the application of point-parametric modeling for model predictive control applications in dynamic networks. The point-parametric modelling methodology is applicable to a variety of large scale c...
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This paper illustrates the application of point-parametric modeling for model predictive control applications in dynamic networks. The point-parametric modelling methodology is applicable to a variety of large scale complex systems such as drinking water distribution systems, power networks, transportation networks and telecommunication networks. Robust parameter estimation provided by point-parametric modelling technology is addressed. The models developed are suitable for model predictive controller design. A numerical example based on drinking water distribution system is used to illustrate the point-parametric modeling for water quality prediction.
This paper presents a co-simulation model using MATLAB® toolboxes to illustrate an interaction between the communication system and the energy grid, coherent with the concept of smart grid that employs IEC 61850 ...
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A growing number of cities worldwide have been installing public bike sharing systems, offering citizens a flexible and "green" alternative of mobility. In most bike sharing systems, customers rent and retur...
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ISBN:
(纸本)9781479978878
A growing number of cities worldwide have been installing public bike sharing systems, offering citizens a flexible and "green" alternative of mobility. In most bike sharing systems, customers rent and return bikes at different stations, without prior notification of the system operator. As a consequence, bike systems often become unbalanced, leaving some stations either empty or full. In such a case, customers either cannot pick up or return their bikes, resulting in a low service level. Typically, system operators employ staff to manually relocate bikes using trucks, leading to considerable operational cost. In this paper, we describe various methods to balance bike sharing systems by actively engaging customers in the balancing process. In particular, we show that by appropriately sending "control signals" to customers requesting them to slightly change their intended journeys, bike sharing systems can be balanced without using staffed trucks. Through extensive simulations based on historical data from London's Barclays Cycle Hire scheme, we show that simple control signals are sufficient to effectively balance the bike sharing system and offer service rates close to 100%.
Battery capacity prediction in aerospace systems is a computationally expensive problem. In this paper, we propose a novel field programmable gate array-based(FPGA) vector processor to reduce latency in this applicati...
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Battery capacity prediction in aerospace systems is a computationally expensive problem. In this paper, we propose a novel field programmable gate array-based(FPGA) vector processor to reduce latency in this application. This processor architecture is optimized for the kernel recursive least squares(KRLS) algorithm, and used to perform online regression. Pipelining is employed to increase performance and microcoding used to provide flexibility. The design was verified using NASA Prognostics Center of Excellence(PCo E) lithium-ion battery capacity data. Experimental results show that the proposed processor can achieve factors of 7, 2 and 5 improvement in execution time, power and latency over a standard microprocessor solution, while maintaining prediction accuracy. The vector processor is suitable not only for battery capacity prediction, but also for other online time series prediction problems.
In this paper, we consider chance-constrained Stochastic Model Predictive control problems for uncertain linear systems subject to additive disturbance. A popular method for solving the associated chance-constrained o...
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ISBN:
(纸本)9781479978878
In this paper, we consider chance-constrained Stochastic Model Predictive control problems for uncertain linear systems subject to additive disturbance. A popular method for solving the associated chance-constrained optimization problem is by means of randomization, in which the chance constraints are replaced by a finite number of sampled constraints, each corresponding to a disturbance realization. Earlier approaches in this direction lead to computationally expensive problems, whose solutions are typically very conservative both in terms of cost and violation probabilities. One way of overcoming this conservatism is to use piecewise affine (PWA) policies, which offer more flexibility than conventional open-loop and affine policies. Unfortunately, the straight-forward application of randomized methods towards PWA policies will lead to computationally demanding problems, that can only be solved for problems of small sizes. To address this issue, we propose an alternative method based on a combination of randomized and robust optimization. We show that the resulting approximation can greatly reduce conservatism of the solution while exhibiting favorable scaling properties with respect to the prediction horizon.
Building energy management is an active field of research since the potential in energy savings can be substantial. Nevertheless, the opportunities for large savings within individual buildings can be limited by the f...
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ISBN:
(纸本)9781479978878
Building energy management is an active field of research since the potential in energy savings can be substantial. Nevertheless, the opportunities for large savings within individual buildings can be limited by the flexibility of the installed climate control devices and the individual construction characteristics. The energy hub concept allows one to manage a collection of buildings in a cooperative manner, by providing opportunities for load shifting between buildings and the sharing of expensive but energy efficient equipment housed in the hub, such as heat pumps, boilers, batteries. Typically, control design for the buildings and the energy hub are done separately, underutilizing the potential flexibility provided by the interconnected system. To address these issues, we propose a unified framework for controlling the operation of the energy hub and the buildings it connects to. By modeling all exogenous disturbance parameters as stochastic processes, and by using state-space representation of the building dynamics, we formulate a multistage stochastic optimization problem to minimize the total energy consumption of the system in a cooperative manner. We solve the resulting infinite dimensional optimization problem using a decision rule approximation, and we benchmark its performance on a numerical study, comparing it with established solution techniques.
The present paper is the first of a series of two papers that concerns the modeling of a complex multipurpose biotechnological plant that consist in two interconnected subsystems, namely an anaerobic digestor and a ph...
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The present paper is the first of a series of two papers that concerns the modeling of a complex multipurpose biotechnological plant that consist in two interconnected subsystems, namely an anaerobic digestor and a photobioreactor. The paper is presenting a complex analytical model for the photobioreactor that embeds the effect of pH on the photosynthetic growth of microalgae. The static characteristics of the multivariable non-square system are discussed along with the solution for its reduction when control strategies are aimed. Simplified dynamic models for the design of control loops were obtained through Hankel analysis.
Canonical correlation analysis(CCA) could be utilized for analyzing a linear static process when the input-output relationship is explicitly existing. Based on the canonical variates obtained by the CCA method, a nove...
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