scholarly journals A Multi-Layered Control Approach for Self-Adaptation in Automotive Embedded Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Marc Zeller ◽  
Christian Prehofer
Keyword(s):  
Embedded Systems ◽  
Lower Layer ◽  
Central Control ◽  
Self Healing ◽  
Control Approach ◽  
Control Loops ◽  
Automotive Systems ◽  
Vehicle Networks ◽  
Self Adaptation ◽  
Layer Control

We present an approach for self-adaptation in automotive embedded systems using a hierarchical, multi-layered control approach. We model automotive systems as a set of constraints and define a hierarchy of control loops based on different criteria. Adaptations are performed at first locally on a lower layer of the architecture. If this fails due to the restricted scope of the control cycle, the next higher layer is in charge of finding a suitable adaptation. We compare different options regarding responsibility split in multi-layered control in a self-healing scenario with a setup adopted from automotive in-vehicle networks. We show that a multi-layer control approach has clear performance benefits over a central control, even though all layers work on the same set of constraints. Furthermore, we show that a responsibility split with respect to network topology is preferable over a functional split.

scholarly journals DC-link sensorless control strategy for grid-connected PV systems

2021 ◽  
Author(s):  
Mostafa Ahmed ◽  
Mohamed Abdelrahem ◽  
Ahmed Farhan ◽  
Ibrahim Harbi ◽  
Ralph Kennel
Keyword(s):  
Sensorless Control ◽  
Current Loop ◽  
Sensor Failure ◽  
Atmospheric Conditions ◽  
Step Size ◽  
Pv System ◽  
Control Approach ◽  
Control Loops ◽  
Pv Systems ◽  
The Cost

AbstractSensorless strategies become very popular in modern control techniques because they increase the system reliability. Besides, they can be used as back-up control in case of sensor failure. In this paper, a DC-link sensorless control approach is developed, which is suited for grid-connected PV systems. The studied system is a two-stage PV scheme, where the DC–DC stage (boost converter) is controlled using an adaptive step-size perturb and observe (P&O) method. Further, the inverter control is accomplished by voltage oriented control (VOC). Generally, the VOC is implemented with two cascaded control loops, namely an outer voltage loop and an inner current loop. However, in this work, the outer loop is avoided and the reference current is generated using a losses model for the system. The losses model accounts for the most significant losses in the PV system. Moreover, particle swarm optimization (PSO) is utilized to compensate for the unmodeled losses. The PSO is executed offline for the purpose of calculation burden reduction. The proposed approach simplifies the cascaded VOC strategy and eliminates the DC-link voltage sensor, which in turn decreases the cost of the system. Finally, the proposed technique is compared with the conventional one at different atmospheric conditions and validated using MATLAB simulation results.

Dynamic Analysis and Stability Improvement Concerning the Integration of Wind Farms Kurdistan Electric Network Case Study

2011 ◽  
pp. 198-219 ◽  
Author(s):  
Mohammad Saleh ◽  
Hassan Bevrani
Keyword(s):  
Wind Power ◽  
Dynamic Models ◽  
Wind Farms ◽  
Integrated System ◽  
Electric Network ◽  
Control Approach ◽  
Control Loops ◽  
And Performance ◽  
The Stability

This chapter presents an overview of key issues and technical challenges in a regional electric network, following the integration of a considerable amount of wind power. A brief survey on wind power system, the present status of wind energy worldwide, common dynamic models, and control loops for wind turbines are given. In this chapter, the Kurdistan electric network in the Northwest part of Iran is introduced as a case study system, and an analytical approach is conducted to evaluate the potential of wind power installation, overall capacity estimation, and economic issues, based on the practical data. Then, the impact of high penetration wind power on the system dynamic and performance for various wind turbine technologies is presented. The stability of integrated system is analyzed, and the need for revising of conventional controls and performance standards is emphasized. Finally, a STATCOM-based control approach is addressed to improve the system stability.

scholarly journals Hierarchical predictive control of Wastewater Treatment Plants

2018 ◽  
Vol 210 ◽  
pp. 02002
Author(s):  
Ioan Nascu
Keyword(s):  
Wastewater Treatment ◽  
Predictive Control ◽  
Wastewater Treatment Plants ◽  
Lower Layer ◽  
Hierarchical Control ◽  
Treatment Plant ◽  
Quality Parameters ◽  
Control Approach ◽  
Tuning Parameters ◽  
Aeration System

This paper investigates the performance of a new predictive control approach used to improve the energy efficiency and effluent quality of a conventional Wastewater Treatment Plant (WWTP). A two-layer hierarchical control structure is proposed: process control as a lower layer and a higher layer of optimization. The Activated Sludge Process (ASP) optimization using the proposed approach provides an improved aeration system efficiency to reduce energy costs while maintaining the quality parameters of the effluent. The control strategy is evaluated by performing simulations and analyzing the results. The regulatory performances have been tested and the effects of several tuning parameters are investigated.

scholarly journals Voltage Ride through Control Strategy of Modular Multilevel Converter under Unbalanced Voltage Sag

2019 ◽  
Vol 9 (3) ◽  
pp. 551
Author(s):  
Seyed Hakimi ◽  
Amin Hajizadeh
Keyword(s):  
Control Strategy ◽  
Reactive Power ◽  
Current Control ◽  
Adaptive Robust Control ◽  
Voltage Sag ◽  
Modular Multilevel Converter ◽  
Multilevel Converter ◽  
Control Approach ◽  
Control Loops ◽  
Unbalanced Voltage

This paper develops modeling and describes a control strategy for a modular multilevel converter (MMC) for grid-connected renewable energy systems. The proposed model can be used to simulate MMC activity during normal and faulty situations. Firstly, a dynamic model of a grid-connected MMC (GC-MMC), based upon the symmetrical component of voltages and currents, was designed. Then an adaptive robust control approach was established in order to follow the reference currents of the converter and stabilize the submodule (SM) capacitor voltage. The positive and negative sequences of reference currents that were given from the demanded active and reactive power during grid voltage disturbance and a normal situation were then utilized in control loops. Finally, the numerical results for the performance of the MMC throughout voltage sag conditions and the effect of uncertainties on the filter parameters during changing power demands were evaluated. The results specified that the current control strategy is more potent under voltage sag situations and able to fulfill the stability requirements of the MMC.

A Bio-Inspired Framework for a Self-Healing Assembly System

2011 ◽  
Author(s):  
Lee J. Wells ◽  
Jaime A. Camelio ◽  
Giovannina Zapata
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
System Level ◽  
Self Healing ◽  
Monitoring And Control ◽  
Statistical Process ◽  
Control Approach ◽  
Process Monitoring And Control ◽  
Manufacturing Assembly ◽  
And Control

Statistical process monitoring and control has been popularized throughout the manufacturing industry as well as various other industries interested in improving product quality and reducing costs. Advances in this field have focused primarily on more efficient ways for diagnosing faults, reducing variation, developing robust design techniques, and increasing sensor capabilities. System level advances are largely dependent on the introduction of new techniques in the listed areas. A unique system level quality control approach is introduced in this paper as a means to integrate rapidly advancing computing technology and analysis methods in manufacturing systems. Inspired by biological systems, the developed framework utilizes immunological principles as a means of developing self-healing algorithms and techniques for manufacturing assembly systems. The principles and techniques attained through this bio-mimicking approach will be used for autonomous monitoring, detection, diagnosis, prognosis, and control of station and system level faults, contrary to traditional systems that largely rely on final product measurements and expert analysis to eliminate process faults.

scholarly journals Research on Multi-Objective Optimization and Control Algorithms for Automatic Train Operation

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3842 ◽  
Author(s):  
Kai-wei Liu ◽  
Xing-Cheng Wang ◽  
Zhi-hui Qu
Keyword(s):  
Predictive Control ◽  
Control Algorithm ◽  
Lower Layer ◽  
Target Speed ◽  
Speed Controller ◽  
Urban Rail ◽  
Train Operation ◽  
Automatic Train Operation ◽  
And Control ◽  
Layer Control

The automatic train operation (ATO) system of urban rail trains includes a two-layer control structure: upper-layer control and lower-layer control. The upper-layer control is to optimize the target speed curve of ATO, and the lower-layer control is the tracking by the urban rail train of the optimal target speed curve generated by the upper-layer control according to the tracking control strategy of ATO. For upper-layer control, the multi-objective model of urban rail train operation is firstly built with energy consumption, comfort, stopping accuracy, and punctuality as optimization indexes, and the entropy weight method is adopted to solve the weight coefficient of each index. Then, genetic algorithm (GA) is used to optimize the model to obtain an optimal target speed curve. In addition, an improved genetic algorithm (IGA) based on directional mutation and gene modification is proposed to improve the convergence speed and optimization effect of the algorithm. The stopping and speed constraints are added into the fitness function in the form of penalty function. For the lower-layer control, the predictive speed controller is designed according to the predictive control principle to track the target speed curve accurately. Since the inflection point area of the target speed curve is difficult to track, the softness factor in the predictive model needs to be adjusted online to improve the control accuracy of the speed. For this paper, we mainly improve the optimization and control algorithms in the upper and lower level controls of ATO. The results show that the speed controller based on predictive control algorithm has better control effect than that based on the PID control algorithm, which can meet the requirements of various performance indexes. Thus, the feasibility of predictive control algorithm in an ATO system is also verified.

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