Evaluation of Algorithms for Linear and Nonlinear PID Control for Twin Rotor MIMO System

This paper analizes a linear and a nonlinear PID control algorithms for a twin rotor MIMO system (TRMS), which is characterized by its nonlinearity, two degrees of freedom and cross coupling. This work aims to stabilize a TRMS in order to achieve a particular position and to follow a trajectory in the shortest time. Mathematical modelling of helicopter system is simulated using MATLAB/Simulink, the two degrees of freedom are controlled both horizontally and vertically through the proposed controllers. Here is also proposed a novel set of nonlinear-segmented observers for each degree of freedom in order to measure the states required by the nonlinear controller. Followed by a comparative performance analysis of both algorithms in a real TRMS.

[1]  P. S. Manoharan,et al.  PID control scheme for twin rotor MIMO system using a real valued genetic algorithm with a predetermined search range , 2013, 2013 International Conference on Power, Energy and Control (ICPEC).

[2]  Bhanu Pratap,et al.  State observer based robust feedback linearization controller for twin rotor MIMO system , 2012, 2012 IEEE International Conference on Control Applications.

[3]  Jih-Gau Juang,et al.  PID Control Using Presearched Genetic Algorithms for a MIMO System , 2008, IEEE Trans. Syst. Man Cybern. Part C.

[4]  Hui Li,et al.  PID control based on wavelet neural network identification and tuning and its application to fin stabilizer , 2005, IEEE International Conference Mechatronics and Automation, 2005.

[5]  N. Ahmed,et al.  Controller design using fuzzy logic for a twin rotor MIMO system , 2003, 7th International Multi Topic Conference, 2003. INMIC 2003..

[6]  J. G. Ziegler,et al.  Optimum Settings for Automatic Controllers , 1942, Journal of Fluids Engineering.

[7]  Benjamin C. Kuo,et al.  AUTOMATIC CONTROL SYSTEMS , 1962, Universum:Technical sciences.

[8]  Bhanu Pratap,et al.  Optimal control of twin rotor MIMO system using output feedback , 2012, 2012 2nd International Conference on Power, Control and Embedded Systems.

[9]  Indrani Kar,et al.  T-S fuzzy model based controller and observer design for a Twin Rotor MIMO System , 2013, 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[10]  Aidan O'Dwyer,et al.  Handbook of PI and PID controller tuning rules , 2003 .

[11]  Marcin Wozniak.  Fitness function for evolutionary computation applied in dynamic object simulation and positioning , 2014, 2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS).

[12]  مريم,et al.  Nonlinear System Identification Based on a Novel Adaptive Fuzzy Wavelet Neural Network , 2013 .

[13]  P. S. Manoharan,et al.  Non-linear modeling and PID control of twin rotor MIMO system , 2012, 2012 IEEE International Conference on Advanced Communication Control and Computing Technologies (ICACCCT).

[14]  Bhanu Pratap,et al.  Sliding mode state observer for 2-DOF twin rotor MIMO system , 2010, 2010 International Conference on Power, Control and Embedded Systems.

[15]  M.H. Shaheed,et al.  Hybrid Fuzzy-PID-based Control of a Twin Rotor MIMO System , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.