Adaptive Fuzzy Type-2 in Control of 2-DOF Helicopter

Abstract

In the present article, type-2 fuzzy controllers (T2FLC) are designed to control position of yaw and pitch angles of the Twin Rotor Multi-input Multi-output System (TRMS) characterized with nonlinear dynamics and uncertainties. Type-2 fuzzy control method is preferred to capture uncertainties and input and output external disturbances. In the presented approach, two independent type-2 fuzzy controllers are designed. Performance of each control scheme is examined under a number of simulations, furthermore some performance indexes to highlight the advantages of the controllers. The results of tracking and disturbance/load rejection tests are compared with the results obtained from conventional fuzzy controller and PID controller. It is the fact that presented diagrams and tabulated results showed that present control approach provided significant advantages over the compared controllers. 

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

“…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.…”

“…A Bounded Input Bounded Output (BIBO) is one of the approaches to realize the stability of IT2FLC [17]. Assume G1 and G2 are representing T2FLC and the controlled plant model respectively, see Figure 8.…”

“…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).…”

Rapidly-implementable optimizely-sizable fuzzy controller architectures: A performance analysis for semiconductor packaging two axes table

“…A typical type-2 fuzzy membership function is consist of two type-1 fuzzy membership functions as shown in Fig.2. [18].…”

Real Time Implementation of Type-2 Fuzzy Backstepping Sliding Mode Controller for Twin Rotor MIMO System (TRMS)

“…The major disadvantage of sliding mode is the chattering phenomenon, which can damage the actuators by too frequent stress and impair the operation and performance of the system, in order to reduce these oscillations several solutions have been made, for example: use artificial intelligence tools, including fuzzy logic type 1 and type 2, in [2] authors presented the real time implementation of non linear observerbased on type-1 fuzzy sliding mode controller for TRMS system, the proposed control in this paper can be attenuating the chattering phenomena of the sliding mode control. In [12,13] the type 2 fuzzy logic and adaptive type 2 fuzzy logic controllers are proposed to stabilize the TRMS Helicopter system, using two independent type-2 fuzzy controllers for the yaw and pitch angles of the TRMS, the performance of each control scheme is examined under a number of simulations. In this work, the real time implementation of T2FBSMC approaches for a TRMS system is proposed.…”