Self-tuning controller: minimum variance/
The self-tuning controller with minimum variance control law is studied with the input-output DARMA (Deterministic AutoRegressive Moving Average) models. Four models of plants are simulated through Turbo Pascal Program. Firstly, the simulation is dealing with parameters estimation by using RLS (Recu...
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Sekudai: UTM,
1993
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| _version_ | 1796662813100343296 |
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| author | 417661 Chai, Andrew Hek Loong |
| author_facet | 417661 Chai, Andrew Hek Loong |
| author_sort | 417661 Chai, Andrew Hek Loong |
| collection | OCEAN |
| description | The self-tuning controller with minimum variance control law is studied with the input-output DARMA (Deterministic AutoRegressive Moving Average) models. Four models of plants are simulated through Turbo Pascal Program. Firstly, the simulation is dealing with parameters estimation by using RLS (Recursive Least Square) algorithm. The convergence of each estimation is investigated through graphic plots. Four choices of output is studied and the control is done by employing the Minimum Variance Control Law. The performance is evaluated through graphical plot. Suggestions for better simulation are proposed. |
| first_indexed | 2024-03-04T16:52:51Z |
| format | |
| id | KOHA-OAI-TEST:88066 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| last_indexed | 2024-03-04T16:52:51Z |
| publishDate | 1993 |
| publisher | Sekudai: UTM, |
| record_format | dspace |
| spelling | KOHA-OAI-TEST:880662020-12-19T17:00:53ZSelf-tuning controller: minimum variance/ 417661 Chai, Andrew Hek Loong Sekudai: UTM,1993The self-tuning controller with minimum variance control law is studied with the input-output DARMA (Deterministic AutoRegressive Moving Average) models. Four models of plants are simulated through Turbo Pascal Program. Firstly, the simulation is dealing with parameters estimation by using RLS (Recursive Least Square) algorithm. The convergence of each estimation is investigated through graphic plots. Four choices of output is studied and the control is done by employing the Minimum Variance Control Law. The performance is evaluated through graphical plot. Suggestions for better simulation are proposed.Project paper (Bachelor of Mechanical Engineering) - Universiti Teknologi Malaysia, 1993The self-tuning controller with minimum variance control law is studied with the input-output DARMA (Deterministic AutoRegressive Moving Average) models. Four models of plants are simulated through Turbo Pascal Program. Firstly, the simulation is dealing with parameters estimation by using RLS (Recursive Least Square) algorithm. The convergence of each estimation is investigated through graphic plots. Four choices of output is studied and the control is done by employing the Minimum Variance Control Law. The performance is evaluated through graphical plot. Suggestions for better simulation are proposed.1420PRZSLAdaptive control systemsAutomatic control |
| spellingShingle | Adaptive control systems Automatic control 417661 Chai, Andrew Hek Loong Self-tuning controller: minimum variance/ |
| title | Self-tuning controller: minimum variance/ |
| title_full | Self-tuning controller: minimum variance/ |
| title_fullStr | Self-tuning controller: minimum variance/ |
| title_full_unstemmed | Self-tuning controller: minimum variance/ |
| title_short | Self-tuning controller: minimum variance/ |
| title_sort | self tuning controller minimum variance |
| topic | Adaptive control systems Automatic control |
| work_keys_str_mv | AT 417661chaiandrewhekloong selftuningcontrollerminimumvariance |