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Analysis & Design Of An Adaptive Autopilot: Theory & Experiments. 指導老師：曾慶耀 教授 學 生 ：呂政倫 學 號 ： 10267041. Outline. Introduction Model Autopilot Analysis Results Conclusions. Introduction.
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Analysis & Design Of An Adaptive Autopilot: Theory & Experiments 指導老師：曾慶耀 教授 學 生：呂政倫 學號：10267041
Outline • Introduction • Model • Autopilot Analysis • Results • Conclusions
Introduction PID controller was applied to course keeping. But PID exhibit performance with environmental disturbances and with large parametric variations. Adaptive autopilot composed of rather simple controllers to correct disturbances to the set course.
A controller is designed based on the Model Reference Adaptive System control theory. All the three controllers are implemented on a model boat under varying load conditions and experiments are conducted . The effectiveness of three controllers are then compared with each other.
Model The simplest mathematical model is the first order model of Nomoto which describes the dynamics between the rudder deflection (δ) and the boat’s yaw angle (ψ).
Autopilot Analysis Three kinds of controllers: • Conventional PD controller (with constant gains) • Gain Scheduling Controller • Adaptive Contoller • Constant gain feedback controller Constant gain feedback controller is a simple PD controller
PD gains can be computed beforehand for the “best” possible response for the Nomoto model. • Gain Scheduling Find measurable variables that correlate well with changes in the process dynamics. These variables can then be used to change the controller parameters.
The main advantage of gain scheduling is that the controller parameters can be change very quickly. • Design of Gain-Scheduling Controller For different values of speeds and loading conditions, different combinations of K and T are proposed.
ADAPTIVE CONTROL The construction of an adaptive controller contains the following steps: 1. Characterize the desired behavior of the closed-loop system. 2. Determine a control law with adjustable parameters. 3. Find a mechanism for adjusting the parameters. 4. Implement the control law.
MODEL REFERENCE ADAPTIVE SYSTEMS (MRAS) MRAS is to create a closed loop controller with parameters that can be updated to change the response of the system.
MIT RULE The MIT rule is the original approach to model reference adaptive control. A closed system in which the controller has one adjustable parameter θ.
After determining the reference model output ψm(t) for the boat • The PD-type control law which will be employed for this processes
After making the above approximations, we obtain the following differential equations for updating the PD controller gains.
Results Practically implementing the Gain Scheduling technique, MRAS and MIT rule and Constant Gain control on the boat that was designed and fabricated. The test and compare the effectivenessof algorithms, both graphically and numerically. • Estimation of Boat Parameters Tests several different speeds and the recorded data in all the experimental runs is analyzed for estimating the parameters K and T.
Experimental Results and Discussion A direct graphical comparison of performances of all the three algorithms are shown in Figs. 5 – 7 for a sample heading angle of .
Conclusions Three controller were successfully implemented to verify the effectiveness and to validate each which load is applied and the implemented technique (algorithm) to reach that angle. The desired angle of MRAS mode is reached faster compared to the other two algorithms. Future work will consider integration of more sensors such as for wind speed and complex dynamic steering models including nonlinear ones.
