Non-linear modeling and PID control of twin rotor MIMO system

Author(s):  
A.P.S. Ramalakshmi ◽  
P.S. Manoharan
Author(s):  
Winston Netto ◽  
Rohan Lakhani ◽  
S. Meenatchi Sundaram

The Twin Rotor MIMO System is a higher order non-linear plant and is inherently unstable due to cross coupling between tail and main rotor. In this paper only the control of main rotor is considered which is non-linear and stable by using adaptive schemes. The control problem is to achieve perfect tracking for input reference signals while maintaining robustness and stability. Four adaptive schemes were implemented, two using Model Reference Adaptive Control under which MIT rule and Modified MIT rule are used. The other two using Adaptive Interaction, namely, Adaptive PID and Approximate Adaptive PID. It is observed that adaptive schemes fulfill all the three system performance requirements at the same time. Modified MIT rule was found to give superior performance in comparison to other controllers. Also Approximate Adaptive PID was able to stabilize the main rotor and cancel the effect of cross coupling between tail rotor and main rotor when operating simultaneously without the need for designing decouplers for the system. Thus the main rotor can be made independent from the state of the tail rotor by using Approximate Adaptive PID.


2013 ◽  
Vol 393 ◽  
pp. 688-693 ◽  
Author(s):  
Hanif Ramli ◽  
Wahyu Kuntjoro ◽  
M.S. Meon ◽  
K.M Asraf K. Ishak

This paper reports a current study on modeling and simulation of adaptive Active Force Control (AFC) based scheme embedded with an artificial neural network (ANN) and/or fuzzy logic (FL) in response manipulations of the twin rotor multi-input multi-output (MIMO) system (TRMS). TRMS is well known for its non-linear behaviour and common classical control scheme such as Proportional-Integral-Derivative (PID) would not be adequate to compensate disturbances. The disturbances in this case were as the results of non-linear external and internal parametric changes, namely angular momentum and couple reactions between the two axes of TRMS. The adaptive control algorithm was proposed in both pitch and yaw to generate an optimum control gain for both responses, simulated viz. MATLAB/SIMULINK software Package. The ANN and FL were integrated into the scheme and act as optimum control algorithm in catalyzing the performance of the TRMS. The results from hybrid conditions of PID-AFC, PID-AFC-ANN and PID-AFC-FL respectively were observed and analyzed. From performance evaluation, PID-AFC-FL scheme has demonstrated a potentially robust and effective manipulating capability in trajectory tracking.


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