Type-2 fuzzy logic control of a 2-DOF helicopter (TRMS system)

Abstract

Abstract:The helicopter dynamic includes nonlinearities, parametric uncertainties and is subject to unknown external disturbances. Such complicated dynamics involve designing sophisticated control algorithms that can deal with these difficulties. In this paper, a type 2 fuzzy logic PID controller is proposed for TRMS (twin rotor mimo system) control problem. Using triangular membership functions and based on a human operator experience, two controllers are designed to control the position of the yaw and the pitch angles of the TRMS. Simulation results are given to illustrate the effectiveness of the proposed control scheme.

Intelligent Tracking Control Using Pso-Based Interval Type-2 Fuzzy Logic for a Mimo Maneuvering System

“…The PD-Like IT2FLC controlled system has been simulated for 100 seconds with zero initial conditions for both; pitch and yaw angles. In this simulation, the reference signals of Sinusoidal wave and Saw tooth with amplitude of 0.2 rad and frequency of 0.02Hz and step input of 0.2 rad are applied to both angles [16]. To investigate the robustness of both controllers with respect to the measurement noise and parametric variations, a signal noise with is added to the measured variables.…”

“…To investigate the robustness of both controllers with respect to the measurement noise and parametric variations, a signal noise with is added to the measured variables. The measured signals from sensors are in general subject to noise in spite of the output of systems are measured using adequate sensors [16,17]. In the following simulations, a uniformly distributed random signal with amplitude of (0.01) is added to the measured pitch and yaw signals, see Figure 9.…”

“…This vehicle is acted by nonlinear aerodynamics forces and gravity, and complexity increases because of flexible surfaces structures which make a realistic analysis difficult [16]. To study the control of this aerodynamics model, the TRMS, a Lab.…”

“…Simulation results also show the effectiveness of the proposed controller in terms of the simplicity of the controller and improving time domain characteristics. The proposed controller uses two input membership function which reduces the rules into 4 as compared with the designed ones in references (9,13,16,17) which uses Type-1and Typ-2 FLC. Both controllers are BIBO stable for all reference trajectories applied without and with the application of noise, see equations (24 and 25).…”

Adaptive Tracking Control for Twin Rotor Multiple-Input Multiple-Output Based on Iss Stabilization

“…With uncertain parameters and external disturbance, the closed loop driven by PID controller keeps the undesirable responses including large overshoot, oscillations and large setting time. The references [5], [6] concerned the control for TRMS using fuzzy logic controller and PID controller. By using the fuzzy controller, the performance of system is better, so to capture the uncertainties there are so many times to try and try the fuzzy laws, the membership functions.…”