scholarly journals Energy Near-Optimal Control Strategies for Industrial and Traction Drives with a.c. Motors

2017 ◽  
Vol 2017 ◽  
pp. 1-22 ◽  
Author(s):  
Ján Vittek ◽  
Peter Butko ◽  
Branislav Ftorek ◽  
Pavol Makyš ◽  
Lukáš Gorel
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Energy Savings ◽  
Position Control ◽  
Control Strategies ◽  
Time Profile ◽  
Optimal Controls ◽  
Zero Dynamic ◽  
Loop Dynamics ◽  
Traction Drives

The main contribution of this paper is a new rest-to-rest position control system for use with electric drives employing a.c. motors that is near-optimal with respect to combined electrical and frictional energy waste minimization. The friction has constant, linear, and quadratic components with respect to the rotor speed. The closeness to optimality is assessed by simulation, comparing the energy loss of the new control system with that predicted by computed optimal controls. The application of the near-optimal control system is rendered straightforward by using a symmetrical trapezoidal speed-time profile. This is provided by an energy saving reference position generator whose output is faithfully followed by means of a feedback control law based on forced dynamics control yielding prescribed closed loop dynamics, together with a matched zero dynamic lag precompensator. For load torque consisting of constant, linear, and quadratic components also maneuver time is optimized if it can be chosen arbitrary. Two case studies, one applied to position control of rotational drive and second one applied to train movement, confirm the possibilities of achieving energy savings.

Energy consumption optimization for AC drives position control

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Branislav Ftorek ◽  
Milan Saga ◽  
Pavol Orsansky ◽  
Jan Vittek ◽  
Peter Butko
Keyword(s):  
Control System ◽  
Energy Saving ◽  
Energy Savings ◽  
Position Control ◽  
Control Strategies ◽  
Content Type ◽  
Ac Drives ◽  
Energy Demands ◽  
Wide Range ◽  
Energy Consumption Optimization

Purpose The main purpose of this paper is to evaluate the two energy saving position control strategies for AC drives valid for a wide range of boundary conditions including an analysis of their energy expenses. Design/methodology/approach For energy demands analysis, the optimal energy control based on mechanical and electrical losses minimization is compared with the near-optimal one based on symmetrical trapezoidal speed profile. Both control strategies respect prescribed maneuver time and define acceleration profile for preplanned rest-to-rest maneuver. Findings Presented simulations confirm lower total energy expenditures of energy optimal control if compared with near-optimal one, but the differences are only small due to the fact that two energy saving strategies are compared. Research limitations/implications Developed overall control system consisting of energy saving profile generator, pre-compensator and position control system respecting principles of field-oriented control is capable to track precomputed state variables precisely. Practical implications Energy demands of both control strategies are verified and compared to simulations and preliminary experiments. The possibilities of energy savings were confirmed for both control strategies. Originality/value Experimental verification of designed control structure is sufficiently promising and confirmed assumed energy savings.

scholarly journals Vehicle Optimal Control Design to Meet the 1.5 °C Target: A Control Design Framework for Vehicle Subsystems

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3170
Author(s):  
Hu ◽  
Chen ◽  
Ding ◽  
Gu
Keyword(s):  
Optimal Control ◽  
Energy Savings ◽  
Control Strategies ◽  
Control Design ◽  
Paris Agreement ◽  
Design Framework ◽  
Control Effect ◽  
Linear Quadratic ◽  
Co2 Intensity ◽  
Light Duty Vehicle

Current studies have achieved energy savings of vehicle subsystems through various control strategies, but these control strategies lack a benchmark to measure whether these energy savings are sufficient. This work proposes a control design framework that uses the 1.5 °C target in the Paris Agreement as a benchmark to measure the adequacy of energy savings of vehicle subsystems. This control design framework involves two points. One is the conversion of the 1.5 °C target into a constraint on the energy consumption of a vehicle subsystem. The other is the optimal control design of the vehicle subsystem under this constraint. To describe the specific application of this control design framework, we conduct a case study concerning the control design of active suspension in a battery electric light-duty vehicle. By comparison with a widely used linear quadratic regulator (LQR) method, we find that this control design framework can both ensure the performance comparable to the LQR method and help to meet the 1.5 °C target in the Paris Climate Agreement. In addition, a sensitivity analysis shows that the control effect is hardly changed by battery electric vehicle market share and electricity CO2 intensity. This work might provide insight on ways that the automotive industry could contribute to the Paris Agreement.

scholarly journals Modeling and Control of the Public Opinion: An Agree-Disagree Opinion Model

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Sara Bidah ◽  
Omar Zakary ◽  
Mostafa Rachik
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
Initial Conditions ◽  
Control Strategies ◽  
Rank Correlation ◽  
Latin Hypercube Sampling ◽  
Optimal Controls ◽  
Modeling And Control ◽  
Partial Rank Correlation ◽  
Objective Functional

In this paper, we aim to investigate optimal control to a new mathematical model that describes agree-disagree opinions during polls, which we presented and analyzed in Bidah et al., 2020. We first present the model and recall its different compartments. We formulate the optimal control problem by supplementing our model with a objective functional. Optimal control strategies are proposed to reduce the number of disagreeing people and the cost of interventions. We prove the existence of solutions to the control problem, we employ Pontryagin’s maximum principle to find the necessary conditions for the existence of the optimal controls, and Runge–Kutta forward-backward sweep numerical approximation method is used to solve the optimal control system, and we perform numerical simulations using various initial conditions and parameters to investigate several scenarios. Finally, a global sensitivity analysis is carried out based on the partial rank correlation coefficient method and the Latin hypercube sampling to study the influence of various parameters on the objective functional and to identify the most influential parameters.

scholarly journals Optimal control strategies of eradicating invisible glioblastoma cells after conventional surgery

2015 ◽  
Vol 12 (106) ◽  
pp. 20141392 ◽  
Author(s):  
Aurelio A. de los Reyes V ◽  
Eunok Jung ◽  
Yangjin Kim
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Cell Fate ◽  
Control Strategies ◽  
Metabolic Stress ◽  
Point Of View ◽  
Drug Infusion ◽  
Conventional Surgery ◽  
Cell Growth And Migration ◽  
Signalling Molecules

Glioblastoma, the most aggressive type of brain cancer, has median survival time of 1 year after diagnosis. It is characterized by alternating modes of rapid proliferation and aggressive invasion in response to metabolic stress in the microenvironment. A particular microRNA, miR-451, and its downstream signalling molecules, AMPK complex, are known to be key determinants in switching cell fate. These components form a core control system determining a balance between cell growth and migration which is regulated by fluctuating glucose levels in the microenvironment. An important factor from the treatment point of view is that low levels of glucose affect metabolism and activate cell migration through the miR-451-AMPK control system, creating ‘invisible’ migratory cells and making them inaccessible by conventional surgery. In this work, we apply optimal control theory to deal with the problem of maintaining upregulated miR-451 levels that prevent cell infiltration to surrounding brain tissue and thus induce localization of these cancer cells at the surgical site. The model also considers the effect of a drug that blocks inhibitive pathways of miR-451 from AMPK complex. Glucose infusion control and drug infusion control are chosen to represent dose rates of glucose and drug intravenous administrations, respectively. The characteristics of optimal control lead us to investigate the structure of optimal intravenous infusion regimen under various circumstances and predict best clinical outcomes with minimum expense possible.

scholarly journals Transmission Dynamics of Hepatitis C with Control Strategies

2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Adnan Khan ◽  
Sultan Sial ◽  
Mudassar Imran
Keyword(s):  
Optimal Control ◽  
Hepatitis C ◽  
Deterministic Model ◽  
Control Strategies ◽  
Endemic Equilibrium ◽  
Transmission Dynamics ◽  
Critical Parameters ◽  
Optimal Controls ◽  
Infected Population ◽  
The Impact

We present a rigorous mathematical analysis of a deterministic model, for the transmission dynamics of hepatitis C, using a standard incidence function. The infected population is divided into three distinct compartments featuring two distinct infection stages (acute and chronic) along with an isolation compartment. It is shown that for basic reproduction number R0≤1, the disease-free equilibrium is locally and globally asymptotically stable. The model also has an endemic equilibrium for R0>1. Uncertainty and sensitivity analyses are carried out to identify and study the impact of critical parameters on R0. In addition, we have presented the numerical simulations to investigate the influence of different important parameters on R0. Since we have a locally stable endemic equilibrium, optimal control is applied to the deterministic model to reduce the total infected population. Two different optimal control strategies (vaccination and isolation) are designed to control the disease and reduce the infected population. Pontryagin’s Maximum Principle is used to characterize the optimal controls in terms of an optimality system which is solved numerically. Numerical results for the optimal controls are compared against the constant controls and their effectiveness is discussed.

scholarly journals Optimal control problem for a tuberculosis model with multiple infectious compartments and time delays

2021 ◽  
Vol 11 (1) ◽  
pp. 75-91
Author(s):  
Mohamed Elhia ◽  
Omar Balatif ◽  
Lahoucine Boujallal ◽  
Mostafa Rachik
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Time Delays ◽  
Control Strategies ◽  
Multiple Time ◽  
Optimal Controls ◽  
Loss To Follow Up ◽  
Tuberculosis Model

In this paper, we formulate an optimal control problem based on a tuberculosis model with multiple infectious compartments and time delays. In order to have a more realistic model that allows highlighting the role of detection, loss to follow-up and treatment in TB transmission, we propose an extension of the classical SEIR model by dividing infectious patients in the compartment (I) into three categories: undiagnosed infected (I), diagnosed patients who are under treatment (T) and diagnosed patients who are lost to follow-up (L). We incorporate in our model delays representing the incubation period and the time needed for treatment. We also introduce three control variables in our delayed system which represent prevention, detection and the efforts that prevent the failure of treatment. The purpose of our control strategies is to minimize the number of infected individuals and the cost of intervention. The existence of the optimal controls is investigated, and a characterization of the three controls is given using the Pontryagin's maximum principle with delays. To solve numerically the optimality system with delays, we present an adapted iterative method based on the iterative Forward-Backward Sweep Method (FBSM). Numerical simulations performed using Matlab are also provided. They indicate that the prevention control is the most effective one. To the best of our knowledge, it is the first work to apply optimal control theory to a TB model which considers infectious patients diagnosis, loss to follow-up phenomenon and multiple time delays.

scholarly journals Towards practical dynamic induction control of wind farms: analysis of optimally controlled wind-farm boundary layers and sinusoidal induction control of first-row turbines

2018 ◽  
Author(s):  
Wim Munters ◽  
Johan Meyers
Keyword(s):  
Optimal Control ◽  
Wind Farm ◽  
Control Strategies ◽  
Computational Cost ◽  
Wind Farms ◽  
Practical Implementation ◽  
Control Mechanisms ◽  
Optimal Controls ◽  
Eddy Simulation ◽  
Wake Interactions

Abstract. Wake interactions between wind turbines in wind farms lead to reduced energy extraction in downstream rows. In recent work, optimization and large-eddy simulation were combined with optimal dynamic induction control of wind farms to study the mitigation of these effects, showing potential power gains of up to 20 % (Munters & Meyers 2017 Phil Trans R Soc A 375, 20160100, doi:10.1098/rsta.2016.0100). However, the computational cost associated with these optimal control simulations impedes practical implementation of this approach. Furthermore, the resulting control signals optimally react to the specific instantaneous turbulent flow realizations in the simulations, so that they cannot be simply used in general. The current work focuses on the detailed analysis of the optimization results of Munters & Meyers, with the aim to identify simplified control strategies that mimic the optimal control results and can be used in practice. The analysis shows that wind-farm controls are optimized in a parabolic manner with little upstream propagation of information. Moreover, turbines can be classified into first-row, intermediate-row, and last-row turbines based on their optimal control dynamics. At the moment, the control mechanisms for intermediate-row turbines remain unclear, but for first-row turbines we find that the optimal controls increase wake mixing by periodic shedding of vortex rings. This behavior can be mimicked with a simple sinusoidal thrust control strategy for first-row turbines, resulting in robust power gains for turbines in the entrance region of the farm.

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