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

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. 

[1]  Jih-Gau Juang,et al.  A hybrid intelligent controller for a twin rotor MIMO system and its hardware implementation. , 2011, ISA transactions.

[2]  Haytham M. Fayek,et al.  A controller based on Optimal Type-2 Fuzzy Logic: systematic design, optimization and real-time implementation. , 2014, ISA transactions.

[3]  I. Burhan Türksen,et al.  Modeling Uncertainty with Fuzzy Logic - With Recent Theory and Applications , 2009, Studies in Fuzziness and Soft Computing.

[4]  Hicham Chaoui,et al.  Computationally Efficient Adaptive Type-2 Fuzzy Control of Flexible-Joint Manipulators , 2013, Robotics.

[5]  Hani Hagras,et al.  A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots , 2004, IEEE Transactions on Fuzzy Systems.

[6]  Vicenç Puig,et al.  A fault-tolerant control scheme for non-linear discrete-time systems: Application to the twin-rotor system , 2010 .

[8]  Akbar Rahideh,et al.  Mathematical dynamic modelling of a twin-rotor multiple input-multiple output system , 2007 .

[9]  Tufan Kumbasar,et al.  An Open Source Matlab/Simulink Toolbox for Interval Type-2 Fuzzy Logic Systems , 2015, 2015 IEEE Symposium Series on Computational Intelligence.

[10]  Hardik Kannad Control of Twin Rotor MIMO System (TRMS) Using PID Controller , 2015 .

[11]  Tufan Kumbasar,et al.  Robust Stability Analysis and Systematic Design of Single-Input Interval Type-2 Fuzzy Logic Controllers , 2016, IEEE Transactions on Fuzzy Systems.

[12]  I. Eksin,et al.  Type-2 fuzzy model based controller design for neutralization processes. , 2012, ISA transactions.

[13]  Peng Wen,et al.  Decoupling control of a twin rotor mimo system using robust deadbeat control technique , 2008 .

[14]  Nohé R. Cázarez-Castro,et al.  Designing Type-1 and Type-2 Fuzzy Logic Controllers via Fuzzy Lyapunov Synthesis for nonsmooth mechanical systems , 2012, Eng. Appl. Artif. Intell..

[15]  Petr Chalupa,et al.  Modelling of Twin Rotor MIMO System , 2015 .

[16]  Akbar Rahideh,et al.  Dynamic modelling of a TRMS using analytical and empirical approaches , 2008 .

[17]  Ricardo Cajo,et al.  Evaluation of Algorithms for Linear and Nonlinear PID Control for Twin Rotor MIMO System , 2015, 2015 Asia-Pacific Conference on Computer Aided System Engineering.

[18]  Liang-Rui Chen,et al.  Improved Twin Rotor MIMO System Tracking and Transient Response Using Fuzzy Control Technology , 2011 .

[19]  Oscar Castillo,et al.  Evolutionary Optimization of Type-2 Fuzzy Logic Systems Applied to Linear Plants , 2009, Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control.

[20]  M. Furkan Dodurka,et al.  The simplest interval type-2 fuzzy PID controller: Structural analysis , 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).