Vehicle tracking using fractional order Kalman filter for non-linear system

2015 ◽  
Author(s):  
Harpreet Kaur ◽  
J. S. Sahambi
Keyword(s):  
Kalman Filter ◽  
Linear System ◽  
Fractional Order ◽  
Vehicle Tracking ◽  
Non Linear ◽  
Non Linear System

Modified Volterra LMS algorithm to fractional order for identification of Hammerstein non‐linear system

2017 ◽  
Vol 11 (8) ◽  
pp. 975-985 ◽  
Author(s):  
Naveed Ishtiaq Chaudhary ◽  
Muhammad Saeed Aslam ◽  
Muhammad Asif Zahoor Raja
Keyword(s):  
Linear System ◽  
Fractional Order ◽  
Lms Algorithm ◽  
Non Linear ◽  
Non Linear System

A novel LSSVM-L Hammerstein model structure for system identification and nonlinear model predictive control of CSTR servo and regulatory control

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Akshaykumar Naregalkar ◽  
Subbulekshmi Durairaj
Keyword(s):  
Linear System ◽  
Regulatory Control ◽  
Hammerstein Model ◽  
Support Vector ◽  
Model Structure ◽  
Linear Dynamics ◽  
Vector Machines ◽  
Non Linear ◽  
Laguerre Filters ◽  
Non Linear System

Abstract A continuous stirred tank reactor (CSTR) servo and the regulatory control problem are challenging because of their highly non-linear nature, frequent changes in operating points, and frequent disturbances. System identification is one of the important steps in the CSTR model-based control design. In earlier work, a non-linear system model comprises a linear subsystem followed by static nonlinearities and represented with Laguerre filters followed by the LSSVM (least squares support vector machines). This model structure solves linear dynamics first and then associated nonlinearities. Unlike earlier works, the proposed LSSVM-L (least squares support vector machines and Laguerre filters) Hammerstein model structure solves the nonlinearities associated with the non-linear system first and then linear dynamics. Thus, the proposed Hammerstein’s model structure deals with the nonlinearities before affecting the entire system, decreasing the model complexity and providing a simple model structure. This new Hammerstein model is stable, precise, and simple to implement and provides the CSTR model with a good model fit%. Simulation studies illustrate the benefit and effectiveness of the proposed LSSVM-L Hammerstein model and its efficacy as a non-linear model predictive controller for the servo and regulatory control problem.

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