The Lyapunov exponent is calculated through a numerical method on the time series obtained experimentally by having the fuzzy controller in closed loop with the plant dynamics.
Results show that with the path control method based on the fuzzy controller optimized by the genetic algorithm ensures that the vehicle sails along the expected path.
The experiments results verify that the performance of our membership functions formation method is better and the fuzzy controller designed by our method has higher control quality.
The simulation results are also included to show the effectiveness of the fuzzy controller by the flexible spacial model design approach.
The objective of this work is to design stable adaptive fuzzy controllers which can provide high degree of automation, guarantee asymptotic stability and also achieve satisfactory transient performance by simultaneous adaptations of both the fuzzy controller structure and its free parameters.
The results obtained are compared with the ones obtained with the fuzzy controller optimized by a MOPSO algorithm.
In its current state, the fuzzy controller is only driven by the indoor temperature forecasted by the NNARX module; no variations in indoor heat gains or occupants' clothing and behavior were considered for driving the controller.
Next, the parameters of the fuzzy controller are optimized by genetic algorithm.
