Active force control with iterative learning control algorithm for a vehicle suspension

The research focuses on the application of an active force control (AFC) strategy with iterative learning control (ILC) algorithms to compensate for the various introduced road profiles or 'disturbances' in a quarter car suspension system as an improvement to ride comfort performance. ILC...

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Main Author: Rosmazi, Rosli
Format: Thesis
Language:English
Published: 2013
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/9041/1/ROSMAZI%20BIN%20ROSLI.PDF
http://umpir.ump.edu.my/id/eprint/9041/
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Institution: Universiti Malaysia Pahang
Language: English
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spelling my.ump.umpir.90412021-08-19T04:17:20Z http://umpir.ump.edu.my/id/eprint/9041/ Active force control with iterative learning control algorithm for a vehicle suspension Rosmazi, Rosli TL Motor vehicles. Aeronautics. Astronautics The research focuses on the application of an active force control (AFC) strategy with iterative learning control (ILC) algorithms to compensate for the various introduced road profiles or 'disturbances' in a quarter car suspension system as an improvement to ride comfort performance. ILC algorithm is implemented into AFC-based control scheme to reduce its complexity and hence faster response, by replacing the use of artificial intelligence (Al) method as proposed by previous researcher. The new control scheme named active force control with iterative learning control algorithm (AFCIL) is complemented by the classic proportionalintegral-derivative (PID) control incorporated and designed as the outermost control loop. The PID controller was first designed and tested prior to developing the AFC which was directly cascaded with the YIDdoop. A number of ILC algorithms were explicitly employed to compute the estimated mass in the AFC loop that is necessary to trigger the control action. The AFC with ILC (AFCIL) suspension system was experimented both through simulation and practical experimentation considering various ILC learning parameters, differenti operating conditions and a number of external disturbances to test and verify the system robustness. The simulation was conducted using MATLAB/Simulink software package whilstthe experimental study utilized the existing experimental rig with a hardware-in-the-loop simulation (HILS) configuration with the proposed ILC algorithms incorporated as the new research contribution. The results obtained, via various control schemes in, the form of PID, AFCIL and passive systems were rigorously, compared and analyzed.to ascertain the system performance in terms of its, ability, to improve riding comfort characteristics. The results imply that the proposed AFC-based scheme produces the best response with an approximately 50% improvement I in comparison to the 'PID and passive counterparts. 2013-10 Thesis NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/9041/1/ROSMAZI%20BIN%20ROSLI.PDF Rosmazi, Rosli (2013) Active force control with iterative learning control algorithm for a vehicle suspension. Masters thesis, Universiti Teknologi Malaysia.
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TL Motor vehicles. Aeronautics. Astronautics
spellingShingle TL Motor vehicles. Aeronautics. Astronautics
Rosmazi, Rosli
Active force control with iterative learning control algorithm for a vehicle suspension
description The research focuses on the application of an active force control (AFC) strategy with iterative learning control (ILC) algorithms to compensate for the various introduced road profiles or 'disturbances' in a quarter car suspension system as an improvement to ride comfort performance. ILC algorithm is implemented into AFC-based control scheme to reduce its complexity and hence faster response, by replacing the use of artificial intelligence (Al) method as proposed by previous researcher. The new control scheme named active force control with iterative learning control algorithm (AFCIL) is complemented by the classic proportionalintegral-derivative (PID) control incorporated and designed as the outermost control loop. The PID controller was first designed and tested prior to developing the AFC which was directly cascaded with the YIDdoop. A number of ILC algorithms were explicitly employed to compute the estimated mass in the AFC loop that is necessary to trigger the control action. The AFC with ILC (AFCIL) suspension system was experimented both through simulation and practical experimentation considering various ILC learning parameters, differenti operating conditions and a number of external disturbances to test and verify the system robustness. The simulation was conducted using MATLAB/Simulink software package whilstthe experimental study utilized the existing experimental rig with a hardware-in-the-loop simulation (HILS) configuration with the proposed ILC algorithms incorporated as the new research contribution. The results obtained, via various control schemes in, the form of PID, AFCIL and passive systems were rigorously, compared and analyzed.to ascertain the system performance in terms of its, ability, to improve riding comfort characteristics. The results imply that the proposed AFC-based scheme produces the best response with an approximately 50% improvement I in comparison to the 'PID and passive counterparts.
format Thesis
author Rosmazi, Rosli
author_facet Rosmazi, Rosli
author_sort Rosmazi, Rosli
title Active force control with iterative learning control algorithm for a vehicle suspension
title_short Active force control with iterative learning control algorithm for a vehicle suspension
title_full Active force control with iterative learning control algorithm for a vehicle suspension
title_fullStr Active force control with iterative learning control algorithm for a vehicle suspension
title_full_unstemmed Active force control with iterative learning control algorithm for a vehicle suspension
title_sort active force control with iterative learning control algorithm for a vehicle suspension
publishDate 2013
url http://umpir.ump.edu.my/id/eprint/9041/1/ROSMAZI%20BIN%20ROSLI.PDF
http://umpir.ump.edu.my/id/eprint/9041/
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