Real Time Implementation of non Linear Observer-Based Fuzzy Sliding Mode Controller for a twin rotor multi-input multi-output system (TRMS)

Abstract Control of the helicopter includes nonlinearities, coupling and external perturbations. This paper presents a control strategy for TRMS (twin rotor mimo system), based on the coupling of the fuzzy logic control with the so-called sliding mode control to make its beam track accurately a reference signal, or reach desired positions in 2 DOF (degree of freedom). Only yaw and pitch angles are considered available for measurement. A non linear observer is used to estimate the unmeasured states. The proposed control scheme can be attenuating the chattering effect of the sliding mode control. Exponential stability is guaranteed by using the Lyapunov method. To show the effectiveness of the proposed observer-based robust controller is illustrated by simulation and experimental results. The real time implementation has been effectuated to the real TRMS system using MATLAB real-time tool box and Advantech PCI1711 card.

[1]  Akbar Rahideh,et al.  Constrained output feedback model predictive control for nonlinear systems , 2012 .

[2]  Wei Li,et al.  Sliding mode voltage control strategy for capturing maximum wind energy based on fuzzy logic control , 2015 .

[3]  Bhanu Pratap,et al.  Real-Time Implementation of Neuro Adaptive Observer-Based Robust Backstepping Controller for Twin Rotor Control System , 2014 .

[4]  Hasan Komurcugil,et al.  Time-varying sliding-coefficient-based decoupled terminal sliding-mode control for a class of fourth-order systems. , 2014, ISA transactions.

[5]  Ming-Yang Cheng,et al.  Implementation of a sliding-mode-based position sensorless drive for high-speed micro permanent-magnet synchronous motors. , 2014, ISA transactions.

[6]  Chin-Wang Tao,et al.  Design of a parallel distributed fuzzy LQR controller for the twin rotor multi-input multi-output system , 2010, Fuzzy Sets Syst..

[7]  Arun D. Mahindrakar,et al.  Terminal Sliding Mode Control of a Twin Rotor Multiple-Input Multiple-Output System , 2011 .

[8]  Thair Sh. Mahmoud,et al.  ANFIS Controller with Fuzzy Subtractive Clustering Method to Reduce Coupling Effects in Twin Rotor MIMO System (TRMS) with Less Memory and Time Usage , 2009, 2009 International Conference on Advanced Computer Control.

[9]  B M Patre,et al.  Composite fuzzy sliding mode control of nonlinear singularly perturbed systems. , 2014, ISA transactions.

[10]  Peng Wang,et al.  Predictive Sliding Mode Control Using Feedback Linearization for Hypersonic Vehicle , 2015 .

[11]  Y. J. Huang,et al.  PID-based fuzzy sliding mode control for twin rotor multi-input multi-output systems , 2013, IEEE 2013 Tencon - Spring.

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

[13]  Rong-Jong Wai,et al.  Fuzzy Sliding-Mode Control Using Adaptive Tuning Technique , 2007, IEEE Transactions on Industrial Electronics.

[14]  Chitralekha Mahanta,et al.  Adaptive second-order sliding mode controller for a twin rotor multi-input-multi-output system , 2012 .

[15]  Yonggui Kao,et al.  A sliding mode approach to robust stabilisation of Markovian jump linear time-delay systems with generally incomplete transition rates , 2015 .

[16]  V. Utkin Variable structure systems with sliding modes , 1977 .

[17]  T. Madani,et al.  Control of a Quadrotor Mini-Helicopter via Full State Backstepping Technique , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[18]  Chin-Wang Tao,et al.  A Novel Fuzzy-Sliding and Fuzzy-Integral-Sliding Controller for the Twin-Rotor Multi-Input–Multi-Output System , 2010, IEEE Transactions on Fuzzy Systems.

[19]  Ahmad B. Rad,et al.  Indirect adaptive fuzzy sliding mode control: Part I: fuzzy switching , 2001, Fuzzy Sets Syst..

[20]  S. J. Mija,et al.  Robust H∞ control algorithm for Twin Rotor MIMO System , 2014, 2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies.

[21]  Hongxing Li,et al.  Finite-time control for nonlinear spacecraft attitude based on terminal sliding mode technique. , 2014, ISA transactions.

[22]  K. Dhanalakshmi,et al.  Fuzzy based sliding surface for shape memory alloy wire actuated classical super-articulated control system , 2015, Appl. Soft Comput..

[23]  John Y. Hung,et al.  Variable structure control: a survey , 1993, IEEE Trans. Ind. Electron..

[24]  S. Spurgeon Choice of discontinuous control component for robust sliding mode performance , 1991 .

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

[26]  Ferat Sahin,et al.  Optimal control of a twin rotor MIMO system using LQR with integral action , 2014, 2014 World Automation Congress (WAC).

[27]  Siti Fauziah Toha,et al.  Dynamic Nonlinear Inverse-Model Based Control of a Twin Rotor System Using Adaptive Neuro-fuzzy Inference System , 2009, 2009 Third UKSim European Symposium on Computer Modeling and Simulation.

[28]  Chin-Wang Tao,et al.  Fuzzy sliding-mode control for ball and beam system with fuzzy ant colony optimization , 2012, Expert Syst. Appl..

[29]  Keng Peng Tee,et al.  Adaptive Neural Network Control for Helicopters in Vertical Flight , 2008, IEEE Transactions on Control Systems Technology.

[30]  Shubhi Purwar,et al.  Composite Nonlinear Feedback controller for Twin Rotor MIMO System , 2014, International Conference on Recent Advances and Innovations in Engineering (ICRAIE-2014).

[31]  Chieh-Li Chen,et al.  Optimal design of fuzzy sliding-mode control: A comparative study , 1998, Fuzzy Sets Syst..