Design Model Free Fuzzy Sliding Mode Control: Applied to Internal Combustion Engine.
Modeling and control of engine systems are vital due to wide range of their applications. As it is obvious stability is the minimum requirement in any control system, however the proof of stability is not trivial especially in the case of nonlinear systems. One of the most active research areas in...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2011
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| Online Access: | http://psasir.upm.edu.my/id/eprint/23313/ |
| _version_ | 1848844723177914368 |
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| author | Sulaiman, Nasri Piltan, Farzin Ferdosali, Paiman Talooki, Iraj Assadi |
| author_facet | Sulaiman, Nasri Piltan, Farzin Ferdosali, Paiman Talooki, Iraj Assadi |
| author_sort | Sulaiman, Nasri |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Modeling and control of engine systems are vital due to wide range of their applications. As it is
obvious stability is the minimum requirement in any control system, however the proof of stability
is not trivial especially in the case of nonlinear systems. One of the most active research areas in
field of internal combustion engine (IC engine) is control of the fuel ratio. The strategies for control
of engines are classified into two main groups: classical and non-classical methods, where the
classical methods used the conventional control theory and non-classical methods used the
artificial intelligence theory such as fuzzy logic, neural networks and/or neurofuzzy. One of the
best nonlinear robust controllers which can be used in uncertainty nonlinear systems is sliding
mode controller (SMC). Chattering phenomenon is the main challenge in this controller. Fuzzy
logic and neuro control have been applied successfully in many applications. Therefore stable
control of an internal combustion engine is challenging because it has uncertain dynamic
parameters. This research presents design a fuzzy sliding mode control with improved in sliding
mode algorithm which offers a model-free sliding mode methodology. The fuzzy sliding mode
controller is designed as a 49 rules Mamdani’s error-based fuzzy sliding-like equivalent part
instead of nonlinear dynamic equation of equivalent part. Various performance indices like the
minimum error, trajectory, disturbance rejection, and chattering control are used for comparison. |
| first_indexed | 2025-11-15T08:35:27Z |
| format | Article |
| id | upm-23313 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T08:35:27Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-233132014-10-03T02:03:49Z http://psasir.upm.edu.my/id/eprint/23313/ Design Model Free Fuzzy Sliding Mode Control: Applied to Internal Combustion Engine. Sulaiman, Nasri Piltan, Farzin Ferdosali, Paiman Talooki, Iraj Assadi Modeling and control of engine systems are vital due to wide range of their applications. As it is obvious stability is the minimum requirement in any control system, however the proof of stability is not trivial especially in the case of nonlinear systems. One of the most active research areas in field of internal combustion engine (IC engine) is control of the fuel ratio. The strategies for control of engines are classified into two main groups: classical and non-classical methods, where the classical methods used the conventional control theory and non-classical methods used the artificial intelligence theory such as fuzzy logic, neural networks and/or neurofuzzy. One of the best nonlinear robust controllers which can be used in uncertainty nonlinear systems is sliding mode controller (SMC). Chattering phenomenon is the main challenge in this controller. Fuzzy logic and neuro control have been applied successfully in many applications. Therefore stable control of an internal combustion engine is challenging because it has uncertain dynamic parameters. This research presents design a fuzzy sliding mode control with improved in sliding mode algorithm which offers a model-free sliding mode methodology. The fuzzy sliding mode controller is designed as a 49 rules Mamdani’s error-based fuzzy sliding-like equivalent part instead of nonlinear dynamic equation of equivalent part. Various performance indices like the minimum error, trajectory, disturbance rejection, and chattering control are used for comparison. 2011 Article PeerReviewed Sulaiman, Nasri and Piltan, Farzin and Ferdosali, Paiman and Talooki, Iraj Assadi (2011) Design Model Free Fuzzy Sliding Mode Control: Applied to Internal Combustion Engine. International Journal of Engineering, 5 (4). pp. 302-312. ISSN 1025-2495 English |
| spellingShingle | Sulaiman, Nasri Piltan, Farzin Ferdosali, Paiman Talooki, Iraj Assadi Design Model Free Fuzzy Sliding Mode Control: Applied to Internal Combustion Engine. |
| title | Design Model Free Fuzzy Sliding Mode Control: Applied to Internal Combustion Engine. |
| title_full | Design Model Free Fuzzy Sliding Mode Control: Applied to Internal Combustion Engine. |
| title_fullStr | Design Model Free Fuzzy Sliding Mode Control: Applied to Internal Combustion Engine. |
| title_full_unstemmed | Design Model Free Fuzzy Sliding Mode Control: Applied to Internal Combustion Engine. |
| title_short | Design Model Free Fuzzy Sliding Mode Control: Applied to Internal Combustion Engine. |
| title_sort | design model free fuzzy sliding mode control: applied to internal combustion engine. |
| url | http://psasir.upm.edu.my/id/eprint/23313/ |