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control of Anaerobic Digestion Reactor with Recirculation Using an Input-Output Linearizing control Strategy

Control of Anaerobic Digestion Reactor with Recirculation Us...

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10th IFAC symposium on control of Power and Energy systems (CPES)

作者： Tawai, Atthasit Panjapornpon, Chanin Sriariyanun, Malinee Cheenkachorn, Kraipat King Mongkuts Univ Technol North Bangkok Sirindhorn Int Thai German Grad Sch Engn Dept Mech & Proc Engn Bangkok 10800 Thailand Kasetsart Univ Dept Chem Engn Fac Engn Bangkok 10900 Thailand King Mongkuts Univ Technol North Bangkok Dept Chem Engn Fac Engn Bangkok 10800 Thailand

This work deals with the development and application of a model-based control system for an anaerobic digestion process which can recover energy using methane combustion. Due to the spatially distributed dynamics of some variables of the upflow anaerobic sludge blanket (UASB) reactor, a type of anaerobic digestion process, the traditional control systems may have insufficient performance to handle the complexity. An input-output (I/O) linearizing control scheme for a UASB reactor is developed for a two-step (acidogenesis-methanogenesis) kinetic model described by a coupled PDE-ODE system. The organic substrate (characterized by COD) is manipulated through the feed flow to achieve the desired trajectories. A simulation for closed-loop responses of the proposed control system is conducted and control performances are determined for servo and regulatory problems. The results show that the developed method provides very good responses to achieve the desired set points and handle the control problems without offset. (C) 2018, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Anaerobic digestion process Waste treatment I/O linearizing control Coupled PDE-ODE system UASB reactor

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Vehicle simulation environment enabling model-based systems engineering of chassis control systems

Vehicle simulation environment enabling model-based systems ...

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18th International Stuttgart symposium on Automotive and Engine Technology, 2018

作者： Braunholz, Christopher Krantz, Werner Wiedemann, Jochen Scharfenbaum, Ingo Schaaf, Uli Ohletz, Armin IVK/FKFS Stuttgart Germany AUDI AG Ingolstadt Germany

ISBN: (纸本)9783658211936

Modern vehicle and mobility concepts result in an increasing vehicle variety and complexity. Subsystems and -components have to be developed in close connection to assess interaction effects. For this work, only the vehicle chassis and its design and development process is to be considered. A modern vehicle chassis contains numerous active control systems, whose purpose include improvements of the vehicle safety, driving dynamics and driving comfort. These systems rely on valid vehicle state information, road condition information, battery degradation states and many more. Further, these systems depend on each other’s system states to avoid unwanted interference. Considering this, the vehicle sensor technology, the on-board power supply, as well as all chassis control systems to be developed together. Since a state-of-the-art vehicle chassis contains multiple control systems each being parameterised by hundreds of parameters, both complexity and interaction effects exceed the potential of independent, conventional development strategies. © Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2018.

关键词： Active safety systems

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RoboX: An End-to-End Solution to Accelerate Autonomous control in Robotics 18

<i>RoboX</i>: An End-to-End Solution to Accelerate Autonomou...

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45th ACM/IEEE Annual International symposium on Computer Architecture (ISCA)

作者： Sacks, Jacob Mahajan, Divya Lawson, Richard C. Esmaeilzadeh, Hadi Georgia Inst Technol Alternat Comp Technol ACT Lab Atlanta GA 30332 USA Univ Calif San Diego Alternat Comp Technol ACT Lab La Jolla CA 92093 USA

ISBN: (纸本)9781538659847

Novel algorithmic advances have paved the way for robotics to transform the dynamics of many social and enterprise applications. To achieve true autonomy, robots need to continuously process and interact with their environment through computationally-intensive motion planning and control algorithms under a low power budget. Specialized architectures offer a potent choice to provide low-power, high-performance accelerators for these algorithms. Instead of taking a traditional route which profiles and maps hot code regions to accelerators, this paper delves into the algorithmic characteristics of the application domain. We observe that many motion planning and control algorithms are formulated as a constrained optimization problems solved online through Model Predictive control (MPC). While models and objective functions differ between robotic systems and tasks, the structure of the optimization problem and solver remain fixed. Using this theoretical insight, we create RoboX, an end-to-end solution which exposes a high-level domain-specific language to roboticists. This interface allows roboticists to express the physics of the robot and its task in a form close to its concise mathematical expressions. The RoboX backend then automatically maps this high-level specification to a novel programmable architecture, which harbors a programmable memory access engine and compute-enabled interconnects. Hops in the interconnect are augmented with simple functional units that either operate on in-fight data or are bypassed according a micro-program. Evaluations with six different robotic systems and tasks show that RoboX provides a 29.4x (73 x) speedup and 22.1 x (79.4 x) performance-per-watt improvement over an ARM Cortex A57 (Intel Xeon E3). Compared to GPUs, RoboX attains 7.8 x, 65.5 x, and 71.8x higher Performance-per Watt to Tegra X2, GTX 650 Ti, and Tesla K40 with a power envelope of only 3.4 Watts at 45 mn.

关键词： Accelerators domain-specific languages DSL in-network computing model predictive control MPC robotics

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An automated instrumental variable method for rigid industrial robot identification

An automated instrumental variable method for rigid industri...

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18th IFAC symposium on System Identification (SYSID)

作者： Brunot, M. Janot, A. Carrillo, F. Off Natl Etud & Rech Aerosp 2 Ave Edouard Belin F-31055 Toulouse France LGP ENI Tarbes 47 Ave AzereixBP 1629 F-65016 Tarbes France

Industrial robots must be operated in closed-loop since they are electro-mechanical systems with double integrator behaviour. Their mechanical model, called the Inverse Dynamic Identification Model (IDIM), is based on Newton's laws and has the advantage of being linear with respect to the parameters. The Instrumental Variable (IDIM-IV) method provides a robust solution to the closed-loop estimation problem. This method relies on a tailor-made prefiltering process in order to estimate accurate parameters. An alternative and automatic way of constructing the observation matrix has been recently introduced. If this methodology provides appropriate estimated parameters, it can fail to estimate the variances of those parameters. In this paper, an identification of the additive noise characteristics is included in the process to obtain correct and lower variances of the IDIM parameters. The evaluation of the new estimation algorithm on a one degree-of-freedom rigid robot shows that it improves statistical efficiency, while minimizing the a priori knowledge required from the practitioner. (C) 2018, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Robots identification System identification Instrumental Variable methods Closed-loop identification Robot dynamics

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Prediction of Selected Parameters of Energy Storage System using Recurrent Neural Networks

Prediction of Selected Parameters of Energy Storage System u...

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10th International-Federation-of-Automatic-control (IFAC) symposium on Fault Detection, Supervision and Safety for Technical processes (SAFEprocess)

作者： Mozaryn, Jakub Chmielewski, Adrian Warsaw Univ Technol Inst Automat Control & Robot A Boboli 8 St PL-02525 Warsaw Poland Warsaw Univ Technol Inst Vehicles Narbutta 84 St PL-02524 Warsaw Poland

This article presents a methodology of the prediction of chosen parameters of an energy storage system in subsequent recharging cycles. Because of a nonlinear description of process dynamics, a coupling of the terminal voltage and temperatures of a battery, the Recurrent Artificial Neural Network structure (R-ANN) is used. A training and testing data were gathered at the laboratory stand with the Valve-Regulated Lead-Acid Absorbent Glass Mat battery (VRLA AGM). As a result, we present an experimental evaluation of the proposed methodology. (C) 2018, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Energy storage Neural network models Prediction methods Expert systems

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control strategy for electromechanical active roll stabilization

Control strategy for electromechanical active roll stabiliza...

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18th International Stuttgart symposium on Automotive and Engine Technology, 2018

作者： Illg, Igor Freuer, Andreas Eisenbarth, Markus Nareyko, Georgi Koch, Thorsten Porsche AG Germany

ISBN: (纸本)9783658211936

As a part of the chassis, electromechanical active roll stabilization systems increase the spread between driving dynamics and driving comfort. There are several distinct advantages compared to the passive versions: improved driving comfort, increased lateraltire force and adjusted self-steering behavior. Functional upgrading results from the interaction of mechatronic components: actuators, sensors and information processing. Using system control as a functional key component with in information processing plays a decisive role in this process. Numerous conflicting goals represent a challenge regarding system development. On the one hand due to the high demand on the dynamics of the set forces in the chassis;on the other hand, because of the typical automotive requirements such as limited power resources, a high operating temperature and the sensitive acoustics. The following paper provides an insight into the system function of the electro mechanical active roll stabilization employed in different D-segment vehicles of the Porsche AG. Special focus is placed on the description of a modular-hierarchical structured control strategy as it has already proven its value despite the above-mentioned conflicting goals. The control structure primarily consists of three core elements: the sensor data fusion of external disturbance variables including an internal preview, the modal transformation of the disturbance excitation into axle specific variables as well as a model based subordinate actuator control. © Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2018.

关键词： Sensor data fusion

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A Novel control Framework of Haptic Take-Over System for Automated Vehicles

A Novel Control Framework of Haptic Take-Over System for Aut...

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2018 IEEE Intelligent Vehicles symposium, IV 2018

作者： Lv, Chen Wang, Huaji Cao, Dongpu Zhao, Yifan Sullman, Mark Auger, Daniel J. Brighton, James Matthias, Rebecca Skrypchuk, Lee Mouzakitis, Alexandros School of Mechanical and Aerospace Engineering School of Electrical and Electronic Engineering Nanyang Technological Univ Singapore639798 Singapore AVL Powertrain UK Ltd CoventryCV4 7EZ United Kingdom School of Aerospace Transport and Manufacturing Cranfield Univ. BedfordMK43 0AL United Kingdom Mechanical and Mechatronics Engineering Univ. of Waterloo ONN2L 3G1 Canada Middle East Technical University Turkey Jaguar Land Rover CoventryCV3 4LF United Kingdom

ISBN: (纸本)9781538644522

Autonomous driving presents an exciting new development in vehicle technology. It poses a new challenge in driver-automation collaboration particularly during handover transitions between human and machine. In order to deal with this problem, this paper proposes a novel control framework for the haptic take-over system. The high-level framework of the haptic take-over control system, which takes driver cognitive workload, neuromuscular dynamics and optimal trajectory planning into consideration, is developed. Under the proposed framework, the determination approach of the optimal input sequence is introduced. The model of the allowed driver take-over authority, which is associated with driver's cognitive workload, as well as muscle readiness during take- over, is investigated and developed. The haptic feedback torque controller is then designed so as to minimize the deviation between the allowed control authority and driver's current degree of participation. A handover process, along with the proposed take-over control method, is also simulated. The simulation results validate the feasibility and effectiveness of the proposed approach. © 2018 IEEE.

关键词： Intelligent vehicle highway systems

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18th International Stuttgart symposium on Automotive and Engine Technology, 2018

18th International Stuttgart Symposium on Automotive and Eng...

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18th International Stuttgart symposium on Automotive and Engine Technology, 2018

ISBN: (纸本)9783658211936

The proceedings contain 115 papers. The special focus in this conference is on Automotive and Engine Technology. The topics include: Analysis of rollover behavior of SUVs in the early phase of chassis development;next generation 3D vehicle dynamics test system – Software and control concept;driving dynamics in the Formula Student;High-level phlegmatization of an ICE for the use in a series hybrid powertrain;combustion engine concepts with extended expansion in hybrid powertrains;adaptive energy management strategy for a heavy-duty truck with a P2-hybrid topology;modeling of a map based turbocharger in a three dimensional engine environment;impact of compressor induced acoustic excitations on the accuracy of the air flow measuring signal;CFD simulation of scroll compressors with axial and radial clearances and thermal deformation;towards a standardized reference architecture for vehicle-to-backend platforms: Motivation and benefits;Safe computing with central ECUs;from the environmental model to the intelligent engine stop start system;challenges of a safe value-added production logistics of the future;flexible production systems as an answer to a volatile environment;basic principles of agile assembly in the automotive industry;homogeneous lean burn engine combustion system development – Concept study;AUDI h-tron – A key-technology to meeting the requirements for sustainable drive concepts;The new Porsche GT engine family: The perfect link between motorsports and road car engines;development of an innovative combustion process: Spark-assisted compression ignition;Measures to fulfill "Real Driving Emission (RDE)" with Diesel passenger cars;additive manufactured open cell structures: Promising substrates for automotive catalysts.

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Prediction of human driver behaviors based on an improved HMM approach

Prediction of human driver behaviors based on an improved HM...

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2018 IEEE Intelligent Vehicles symposium, IV 2018

作者： Deng, Qi Wang, Jiao Söffker, DIrk Dynamics and Control University of Duisburg-Essen Duisburg Germany

ISBN: (纸本)9781538644522

Research and development of predicting driving behaviors play an important role in the development of Advanced Driver Assistance systems (ADAS) for assisting drivers. In this contribution, an approach is developed based on Hidden Markov Model (HMM) for predicting human driving behaviors. Three different driving maneuvers including left/right lane change and lane keeping are modeled as hidden states for the HMM. Based on observations (training), the HMM approach is able to calculate the most possible driving behaviors using observed sequences. Furthermore, the observed sequences are also used for training of HMM in the modeling process. To improve the prediction performance of the model, a prefilter is proposed to quantize the collected signals into observed sequences with specific features. In this contribution the definition of a suitable prefilter will be discussed and finally optimized. The approach focuses on the definition of optimal prefilters. Here optimality is defined as the optimal segments describing a quantized prefilter mapping the vehicle's environment to quantized states. In combination with related HMM-based results in terms of accuracy, detection, and false alarm rates an optimal parameter set of the prefilter can be determined. Using experimental data from real human driving behaviors (taken from driving simulator) it can be concluded that the optimal definition of the prefilter can increase the detection rate and accuracy, and in the meanwhile decrease the false alarm rate. The effectiveness of driving behaviors prediction has been successfully proved by comparison with other methods in this contribution. © 2018 IEEE.

关键词： Hidden Markov models

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Improved Driving Behaviors Prediction Based on Fuzzy Logic-Hidden Markov Model (FL-HMM)

Improved Driving Behaviors Prediction Based on Fuzzy Logic-H...

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2018 IEEE Intelligent Vehicles symposium, IV 2018

作者： Deng, Qi Söffker, DIrk Dynamics and Control University of Duisburg-Essen Duisburg Germany

ISBN: (纸本)9781538644522

Research and development of human driving behaviors play an important role in the development of assistance systems. In this contribution, a driving behaviors prediction model is based on a newly developed approach combining different Hidden Markov Models (HMM) cooperatively combined by Fuzzy Logic (FL). Due to variations of individual human drivers decision behavior the task to classify related behaviors based on individually trained models is difficult. The FL approach will be used for additional distinction of driving scenes into very safe, safe, and dangerous driving scenarios. For each scenario corresponding HMMs will be trained. Three different driving behaviors including left/right lane change and lane keeping are modelled as hidden states for the HMM. Based on observations, the algorithm calculates the most possible driving behaviors through the observation sequences. Furthermore, the observed sequences are also used for training of HMM during modeling process. To improve the prediction performance of the model, a prefilter is proposed to quantize the collected signals into observed sequences with specific features. To optimize the model performance NSGA-II was used to define the optimal thresholds of FL and the optimal prefilters of HMMs. Using experimental data from real human driving behaviors (taken from driving simulator) it can be concluded that selecting optimal thresholds will increase the performance of driving behaviors prediction. The effectiveness of the suggested fuzzy-based HMM has been successfully proved based on experiments. © 2018 IEEE.

关键词： Hidden Markov models

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