Robust adaptive state-feedback tracking for nonlinear systems

1998 ◽  
Vol 43 (1) ◽  
pp. 84-89 ◽  
Author(s):  
R. Marino ◽  
P. Tomei
Keyword(s):  
Nonlinear Systems ◽  
State Feedback ◽  
Robust Adaptive ◽  
Feedback Tracking

scholarly journals Approximation-Based Quantized State Feedback Tracking of Uncertain Input-Saturated MIMO Nonlinear Systems with Application to 2-DOF Helicopter

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1062
Author(s):  
Byung Mo Kim ◽  
Sung Jin Yoo
Keyword(s):  
Nonlinear Systems ◽  
State Feedback ◽  
Tracking Error ◽  
Multiple Input Multiple Output ◽  
Input Saturation ◽  
Lyapunov Theory ◽  
Experimental Results ◽  
State Variables ◽  
Mimo Nonlinear Systems ◽  
Feedback Tracking

This paper addresses an approximation-based quantized state feedback tracking problem of multiple-input multiple-output (MIMO) nonlinear systems with quantized input saturation. A uniform quantizer is adopted to quantize state variables and control inputs of MIMO nonlinear systems. The primary features in the current development are that (i) an adaptive neural network tracker using quantized states is developed for MIMO nonlinear systems and (ii) a compensation mechanism of quantized input saturation is designed by constructing an auxiliary system. An adaptive neural tracker design with the compensation of quantized input saturation is developed by deriving an augmented error surface using quantized states. It is shown that closed-loop stability analysis and tracking error convergence are conducted based on Lyapunov theory. Finally, we give simulation and experimental results of the 2-degrees-of-freedom (2-DOF) helicopter system for verifying to the validity of the proposed methodology where the tracking performance of pitch and yaw angles is measured with the mean squared errors of 0.1044 and 0.0435 for simulation results, and those of 0.0656 and 0.0523 for experimental results.

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