Application of Intelligent Adaptive Force Control for a Helicopter Seat Suspension System

The high level of transmitted noise and vibrations of a helicopter flight to the aircrew body can cause discomfort and perhaps affect their performance and physical condition. This paper presents an active seat suspension system with intelligent active force control (AFC) using an artificial neural network (ANN), iterative learning (IL) algorithm, and fuzzy logic (FL) to reduce vibration on the helicopter seat. Therefore, three control schemes are considered for this application namely AFCANN, AFCIL, and AFCFL. Computer simulations are performed using the MATLAB software to verify the proposed control schemes. The pilot head displacement, acceleration and also seat acceleration transmissibility are selected as target variables. The simulation results demonstrate that the usage of proposed control schemes leads to effective control of target variables especially active force control using fuzzy logic (AFCFL) which is showing superior performance and accuracy between other intelligent adaptive force control schemes. In future work, this controller will be assessed by experimental tests.

Keywords:

Pilot body vibration , Fuzzy logic , Iterative learning , Neural network , Active force controller