The existing uncertainties during the operation of processes could strongly affect performance forecasting systems, control strategies and fault detection systems when they are not considered in design. Because that, study uncertainty quantification has gained more attention among researchers past decades. From this field study, prediction intervals arise as one techniques most used literature to represent effect over future process behavior. Thus, have focused on developing based use fuzzy...

This paper presents a two-level hierarchical energy management system (EMS) for microgrid operation that is based on robust model predictive control (MPC) strategy. EMS focuses minimizing the cost of drawn from main grid and increasing self-consumption local renewable resources, brings benefits to users as well distribution network operator (DNO). The higher level comprises MPC controller which optimizes usage defines power reference tracked by lower-level real-time controller. proposed...

Implementing control schemes for modular multilevel converters (M2Cs) involves both a cyber and physical level, leading to cyber-physical system (CPS). At the communication network enables data exchange between sensors, platforms, monitoring systems. Meanwhile, at semiconductor devices that comprise M2C are switched <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> / xmlns:xlink="http://www.w3.org/1999/xlink">off</small> by system. In...

This paper presents a methodology based on generic evolutionary algorithms to solve dynamic pickup and delivery problem formulated under hybrid predictive control approach. The solution scheme is designed support the dispatcher of dial-a-ride service, where quick efficient real-time solutions are needed. considers different configurations particle swarm optimization genetic within proposed ad-hoc in real time nonlinear mixed-integer related with These consist techniques handle operational...

This article presents a novel scheme based on distributed model-based predictive control for the secondary level of hybrid ac/dc microgrids (MGs). Prediction models droop and power-transfer equations are proposed to characterize generators in both ac dc sub-MGs, whereas power balance constraints used predict behavior interlinking converters. The operational (such as powers action limits) included all formulations. Experimental results validate following cases: 1) load changes, working within...

This paper presents a hybrid adaptive predictive control approach that includes future information in real-time routing decisions the context of dynamic pickup and delivery problem (DPDP). We recognize this research when is dynamic, an additional stochastic effect has to be considered within analytical expression objective function for vehicle scheduling routing, which extra cost associated with potential rerouting arising from unknown requests future. The major contributions are: first,...

The optimisation of predicted control policies in model predictive (MPC) enables the use information on uncertainty that, though not available at current time, will be so a future point prediction horizon. Optimisation over feedback laws is however prohibitively computationally expensive. so-called affine-in-the-disturbance strategies provide compromise and this article considers disturbance compensation context stochastic MPC. Unlike earlier approaches, here applied entire horizon...

A Robust MPC strategy for Heating, Ventilation and Air Conditioning Systems (HVAC) is proposed in this work. The typical control objective of minimizing energy consumption while maintaining user comfort considered naturally suited HVAC systems with the aforementioned goal because it a that considers process constraints optimization performance index, explicitly handles uncertainty. In system, uncertainty comes from ambient temperature internal loads predictions, which are main factors...

A recent paper, which considered multiplicative uncertainty, introduced polytopic dynamics into the prediction structure and optimized these so as to maximize volume of an invariant ellipsoid. This work was extended case mixed additive uncertainty with conditions that are claimed only be sufficient. Additionally, when system known over a horizon, N, derived control law used terminal overall robust MPC strategy deployed affine-in-the-disturbances policy. The aim this paper is reformulate such...

The stability of stochastic model-predictive control (MPC) subject to additive disturbances is often demonstrated in the literature by constructing Lyapunov-like inequalities that ensure closed-loop performance bounds and boundedness state, but tight ultimate for state nonconservative are typically not determined. In this article, we use an input-to-state property find conditions imply convergence with probability 1 a disturbed nonlinear system minimal robust positively invariant set. We...

As CO2 emission regulations increase, fleet owners increasingly consider the adoption of Electric Vehicle (EV) fleets in their business. The conventional Routing Problem (VRP) aims to find a set routes reduce operational costs. However, route planning EVs poses different challenges than that Internal Combustion Engine Vehicles (ICEV). (E-VRP) must take into consideration EV limitations such as short driving range, high charging time, poor infrastructure, and battery degradation. In this...

This paper presents a new robust distributed approach for the energy management of rural multi-microgrids communities in Chile. These are often geographically isolated and have poor connection to main electricity grid. Operating them as individual microgrids allows community connect grid or behave stand-alone system (islanded). Connecting coordinating operation can improve system's robustness demand uncertainty, well reducing dependency on However, this coordination be challenging because...

Recently introduced parameterized tube model predictive control (PTMPC) supersedes the robust (RMPC) using affine in past disturbances policy, and is, certain cases, equivalent to RMPC utilizing dynamic programming. PTMPC online implementation reduces a standard convex optimization for which numbers of decision variables equality inequality constraints grow quadratically with respect prediction horizon N. This paper considers reduction computational complexity linear growth by allowing part...

This paper presents a new methodology for Prediction Interval (PI) construction based on modified Takagi-Sugeno fuzzy system trained with joint Supervision loss function. Given desired coverage level, this model is capable of providing predictions the expected value along interval bounds. tested by simulation experiments using dataset containing real temperature data from rural community in southern Chile. The proposed was compared state-of-the-art Fuzzy Numbers model. It shown that Joint...

The modular multilevel converter (MMC) is a prominent solution for medium- to high-voltage and high-power conversion applications. Recently, distributed control strategies have been proposed make this in terms of software hardware. In architecture, high-level tasks are performed by central controller (CC), whereas low-level achieved local controllers (LCs) placed on the MMC submodules. CC LCs use cyber-physical system (CPS) share all necessary information execute their respective schemes....

The performance enhancement of an inverter-based grid-connected system necessitates a fast and accurate dynamic response in terms estimating three-phase grid voltage attributes. synchronous reference frame phase-locked loop and/or the frequency-locking (i.e., frequency-locked loop) approaches are widely used practical applications. However, due to phase/frequency feedback loops, aforementioned parameter estimation schemes may experience instability provide slow response. This work presents...