{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/78626"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/78626","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Online Message Delay Prediction for Model Predictive Control over Controller Area Network","abstract":"Today's Cyber-Physical Systems (CPS) are typically distributed over several computing nodes communicating by way of shared buses such as Controller Area Network (CAN). Their control performance gets degraded due to variable delays (jitters) incurred by messages on the shared CAN bus due to contention and network overhead. This work presents a novel online delay prediction approach that predicts the message delay at runtime based on real-time traffic information on CAN. It leverages the proposed method to improve control quality, by compensating for the message delay using the Model Predictive Control (MPC) algorithm in designing the controller. By simulating an automotive Cruise Control system and a DC Motor plant in a CAN environment, it goes on to demonstrate that the delay prediction is accurate, and that the MPC design which takes the message delay into consideration, performs considerably better. It also implements the proposed method on an 8-bit 16MHz ATmega328P microcontroller and measures the execution time overhead. The results clearly indicate that the method is computationally feasible for online usage.","abstract_html":"Today's Cyber-Physical Systems (CPS) are typically distributed over several computing nodes communicating by way of shared buses such as Controller Area Network (CAN). Their control performance gets degraded due to variable delays (jitters) incurred by messages on the shared CAN bus due to contention and network overhead. This work presents a novel online delay prediction approach that predicts the message delay at runtime based on real-time traffic information on CAN. It leverages the proposed method to improve control quality, by compensating for the message delay using the Model Predictive Control (MPC) algorithm in designing the controller. By simulating an automotive Cruise Control system and a DC Motor plant in a CAN environment, it goes on to demonstrate that the delay prediction is accurate, and that the MPC design which takes the message delay into consideration, performs considerably better. It also implements the proposed method on an 8-bit 16MHz ATmega328P microcontroller and measures the execution time overhead. The results clearly indicate that the method is computationally feasible for online usage.","abstract_has_math":false,"creators":["Bangalore Narendranath Rao, Amith Kaushal"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Computer Engineering","degree_department":"Electrical and Computer Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Zeng, Haibo"],"committee_members":["Guo, Feng","Tokekar, Pratap"],"year":2017,"date_issued":"2017-07-28","date_published":"2017-07-28","updated_at":"2026-07-22T22:19:51Z","subjects":["Model Predictive Control (MPC)","Controller Area Network (CAN)","Online delay prediction","delay"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:12378"],"render_values":[{"text":"vt_gsexam:12378","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/78626","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Zeng, Haibo"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Guo, Feng","Tokekar, Pratap"]},{"key":"dc:contributor.department","label":"Department","values":["Electrical and Computer Engineering"]},{"key":"dc:creator","label":"Author","values":["Bangalore Narendranath Rao, Amith Kaushal"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-08-03T12:59:18Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-08-03T12:59:18Z"]},{"key":"dc:date.issued","label":"Date","values":["2017-07-28"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Model Predictive Control (MPC)","Controller Area Network (CAN)","Online delay prediction","delay"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:12378"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/78626"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Today's Cyber-Physical Systems (CPS) are typically distributed over several computing nodes communicating by way of shared buses such as Controller Area Network (CAN). Their control performance gets degraded due to variable delays (jitters) incurred by messages on the shared CAN bus due to contention and network overhead. This work presents a novel online delay prediction approach that predicts the message delay at runtime based on real-time traffic information on CAN. It leverages the proposed method to improve control quality, by compensating for the message delay using the Model Predictive Control (MPC) algorithm in designing the controller. By simulating an automotive Cruise Control system and a DC Motor plant in a CAN environment, it goes on to demonstrate that the delay prediction is accurate, and that the MPC design which takes the message delay into consideration, performs considerably better. It also implements the proposed method on an 8-bit 16MHz ATmega328P microcontroller and measures the execution time overhead. The results clearly indicate that the method is computationally feasible for online usage."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["In today’s world, most complicated systems such as automobiles employ a decentralized modular architecture with several nodes communicating with each other over a shared medium. The Controller Area Network (CAN) is the most widely accepted standard as far as automobiles are concerned. The performance of such systems gets degraded due to the variable delays (jitters) incurred by messages on the CAN. These delays can be caused by messages of higher importance delaying bus access to the messages of lower importance, or due to other network related issues. This work presents a novel approach that predicts the message delays in real-time based on the traffic information on CAN. This approach leverages the proposed method to improve the control quality by compensating for the message delay using an advanced controller algorithm called Model Predictive Control (MPC). By simulating an automotive Cruise Control system and a DC motor plant in a CAN environment, this work goes on to demonstrate that the delay prediction is accurate, and that the MPC design which takes the message delay into consideration, performs considerably better. It also implements the proposed approach on a low end microcontroller (8bit, 16MHz ATmega328P) and measures the time taken for predicting the delay for each message (execution overhead). The obtained results clearly indicate that the method is computationally feasible for use in a real-time scenario."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Online Message Delay Prediction for Model Predictive Control over Controller Area Network"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Zeng, Haibo"],"dc:contributor.committeemember":["Guo, Feng","Tokekar, Pratap"],"dc:contributor.department":["Electrical and Computer Engineering"],"dc:creator":["Bangalore Narendranath Rao, Amith Kaushal"],"dc:date.accessioned":["2017-08-03T12:59:18Z"],"dc:date.available":["2017-08-03T12:59:18Z"],"dc:date.issued":["2017-07-28"],"dc:description.abstract":["Today's Cyber-Physical Systems (CPS) are typically distributed over several computing nodes communicating by way of shared buses such as Controller Area Network (CAN). Their control performance gets degraded due to variable delays (jitters) incurred by messages on the shared CAN bus due to contention and network overhead. This work presents a novel online delay prediction approach that predicts the message delay at runtime based on real-time traffic information on CAN. It leverages the proposed method to improve control quality, by compensating for the message delay using the Model Predictive Control (MPC) algorithm in designing the controller. By simulating an automotive Cruise Control system and a DC Motor plant in a CAN environment, it goes on to demonstrate that the delay prediction is accurate, and that the MPC design which takes the message delay into consideration, performs considerably better. It also implements the proposed method on an 8-bit 16MHz ATmega328P microcontroller and measures the execution time overhead. 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This approach leverages the proposed method to improve the control quality by compensating for the message delay using an advanced controller algorithm called Model Predictive Control (MPC). By simulating an automotive Cruise Control system and a DC motor plant in a CAN environment, this work goes on to demonstrate that the delay prediction is accurate, and that the MPC design which takes the message delay into consideration, performs considerably better. It also implements the proposed approach on a low end microcontroller (8bit, 16MHz ATmega328P) and measures the time taken for predicting the delay for each message (execution overhead). The obtained results clearly indicate that the method is computationally feasible for use in a real-time scenario."],"dc:description.degree":["Master of Science"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:12378"],"dc:identifier.uri":["http://hdl.handle.net/10919/78626"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Model Predictive Control (MPC)","Controller Area Network (CAN)","Online delay prediction","delay"],"dc:title":["Online Message Delay Prediction for Model Predictive Control over Controller Area Network"],"dc:type":["Thesis"],"thesis:degree_discipline":["Computer Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:51Z"}