Adaptive Control of Hydraulic Drive System: Real Time Steady-State Estimation Using Kalman Filter
Publicerad
Författare
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
This thesis investigates how an adaptive controller can be developed for a hydraulic
drive system. The currently used controller consists of a feed-forward component
and a PI component. The feed-forward component consists of tables describing
the steady-states of the vehicle, where the desired value is acquired through linear
interpolation between the table points. The problem being that the system behaviour
changes with time, leading the table values to become inaccurate and as a
consequence the controller cannot control the system to satisfaction.
The goal of this thesis is to solve this adaptivity problem and develop a controller
that can handle the changes to the system over time. This is achieved by implementing
a Kalman filter-based algorithm that updates the steady-state values of
the feed-forward part of the controller to correct values, based on continuous measurements
from the system. Relevant tables values are chosen as Kalman states
which are updated based on measurements from the system and then reinserted
into the tables. Two further development concepts are investigated. In the first the
Kalman filter is updated with a batch of measurements and in the second a 3rd
order polynomial is used to find interpolated values instead of linear interpolation.
The conclusion is that the above mentioned algorithm results in an efficient system
controller that maintains a comfortable driving experience. It is shown in this
thesis that updated table values provide better control performance and that this
contributes to the adaptivity of the controller.
Beskrivning
Ämne/nyckelord
Machine learning, Reinforcement learning, System control, Model-free Control, Model-Based Control, Adaptive Control, Kalman Filter, Extended Kalman Filter