A survey on online learning and optimization for spark advance control of SI engines
Published 2018 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A survey on online learning and optimization for spark advance control of SI engines
Authors
Keywords
online learning, stochastic optimization, iterative solution, combustion control, spark ignition engine
Journal
Science China-Information Sciences
Volume 61, Issue 7, Pages -
Publisher
Springer Nature
Online
2018-06-16
DOI
10.1007/s11432-017-9377-7
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Spark advance self-optimization with knock probability threshold for lean-burn operation mode of SI engine
- (2017) Xun Shen et al. ENERGY
- An On-Board Calibration Scheme for Map-Based Combustion Phase Control of Spark-Ignition Engines
- (2017) Jinwu Gao et al. IEEE-ASME TRANSACTIONS ON MECHATRONICS
- Controlling spark timing for consecutive cycles to reduce the cyclic variations of SI engines
- (2015) Alirıza Kaleli et al. APPLIED THERMAL ENGINEERING
- Extremum seeking of dynamical systems via gradient descent and stochastic approximation methods
- (2015) Sei Zhen Khong et al. AUTOMATICA
- Statistics of Parameter Estimates: A Concrete Example
- (2015) Oscar Aguilar et al. SIAM REVIEW
- Online optimization of spark advance in alternative fueled engines using extremum seeking control
- (2014) Alireza Mohammadi et al. CONTROL ENGINEERING PRACTICE
- Spark Ignition Feedback Control by Means of Combustion Phase Indicators on Steady and Transient Operation
- (2014) Pipitone Emiliano JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME
- Automatic Combustion Phase Calibration With Extremum Seeking Approach
- (2014) Enrico Corti et al. JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME
- Unified frameworks for sampled-data extremum seeking control: Global optimisation and multi-unit systems
- (2013) Sei Zhen Khong et al. AUTOMATICA
- On-Board Calibration of Spark Timing by Extremum Seeking for Flex-Fuel Engines
- (2013) Erik Hellstrom et al. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
- Likelihood-Based Control of Engine Knock
- (2013) James C. Peyton Jones et al. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
- Estimating Parameters in Physical Models through Bayesian Inversion: A Complete Example
- (2013) Moritz Allmaras et al. SIAM REVIEW
- A Framework for Extremum Seeking Control of Systems With Parameter Uncertainties
- (2012) Dragan Nesic et al. IEEE TRANSACTIONS ON AUTOMATIC CONTROL
- A learning algorithm concept for updating look-up tables for automotive applications
- (2012) C. Guardiola et al. MATHEMATICAL AND COMPUTER MODELLING
- EKF-based adaptation of look-up tables with an air mass-flow sensor application
- (2011) Erik Höckerdal et al. CONTROL ENGINEERING PRACTICE
- Spark Advance Real-Time Optimization Based on Combustion Analysis
- (2011) Enrico Corti et al. JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME
- A new extremum seeking technique and its application to maximize RF heating on FTU
- (2009) D. Carnevale et al. FUSION ENGINEERING AND DESIGN
- Extremum Seeking With Stochastic Perturbations
- (2009) C. Manzie et al. IEEE TRANSACTIONS ON AUTOMATIC CONTROL
- Identification and adaptation of linear look-up table parameters using an efficient recursive least-squares technique
- (2009) James C. Peyton Jones et al. ISA TRANSACTIONS
- On the choice of dither in extremum seeking systems: A case study
- (2008) Ying Tan et al. AUTOMATICA
- A Comparison Between Combustion Phase Indicators for Optimal Spark Timing
- (2008) Emiliano Pipitone JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME
- Self-optimising control of an SI-engine using a torque sensor
- (2007) Stefan Larsson et al. CONTROL ENGINEERING PRACTICE
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started