Fig 1.
(a) Block diagrams of conventional MRAC system, (b) block diagrams of RSAC system.
Fig 2.
Simulink simulation model for the first scenario.
Fig 3.
The reference input, outputs of the reference model and the plant: (a) a view of full-time simulation, (b) a close view of initial responses, (c) a close view of final responses.
Fig 4.
(a) Model error, (b) adaptation gain from the first simulation scenario.
Fig 5.
(a) Step input disturbance, (b) system outputs, (c) control signal from the first simulation scenario and (d) logarithmic scaled MSE values for various values of error threshold ez.
Fig 6.
Simulink simulation model for the second scenario.
Fig 7.
Reference input, outputs of reference model and the plant: (a) a view of full-time simulation, (b) a close view of initial response for the plant perturbation, (c) a close view of final responses.
Fig 8.
(a) Control signal, (b) adaptation gain; (c) model error signal from the second simulation scenario.
Fig 9.
The short-time average square error calculated for the second simulation scenario.
Fig 10.
System outputs for continuous multi-sinusoidal reference input (a) at the beginning and (b) at the end of simulation, (c) adaptation gain, (d) short-time average square error.
Fig 11.
A comparison of outputs of RSAC and conventional MRAC with MIT rule: (a) a close view of responses of systems for the plant perturbation at 15000 sec, (b) a close view of final responses of systems.
Fig 12.
(a) A prototype of coaxial rotors control experimental test platform; (b) Close views of Arduino Mega 2560 card; (c) Close views of coaxial rotors and blades used in the experimental system.
Fig 13.
Matlab/Simulink design of the proposed adaptive control system.
Fig 14.
Electrical components of experimental system.
Fig 15.
Implementation of update rules of (a) control optimizer (Eq 7) and (b) adaptation optimizer (Eq 11) in Simulink.
Fig 16.
Sinusoidal reference input, output of reference model and output of coaxial rotors control; (a) a full view of experimental results; (b) a close view for initial response (Before adaptation); (c) a close view of final responses of the experimental system (After adaptation).
Fig 17.
(a) The control signal, (b) the adaptation gain and (c) the model error signal from the experimental system.