ADAPTIVE CONTROL OF ECONOMETRIC MODELS WITH UNKNOWN PARAMETERS

Author(s):  
Y. Ito
2020 ◽  
Vol 53 (2) ◽  
pp. 13876-13881
Author(s):  
Mohammad Pourmahmood Aghababa ◽  
Mehrdad Saif ◽  
Bahram Shafai

2012 ◽  
Vol 229-231 ◽  
pp. 2209-2212
Author(s):  
Bao Bin Liu ◽  
Wei Zhou

Logic-based switching adaptive control scheme is proposed for the model of DC-DC buck converter in presence of uncertain parameters and power supply disturbance. All uncertain parameters and the disturbance are estimated together through constructing Lyapunov function. And a switching mechanism is used to ensure global asymptotic stability of the closed-loop system. The results of simulation show that even if there are multiple unknown parameters in the small-signal model, the control system of DC-DC buck converter can estimate unknown parameters quickly and accurately.


2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Baojie Zhang ◽  
Hongxing Li

Universal projective synchronization (UPS) of two chaotic systems is defined. Based on the Lyapunov stability theory, an adaptive control method is derived such that UPS of two different hyperchaotic systems with unknown parameters is realized, which is up to a scaling function matrix and three kinds of reference systems, respectively. Numerical simulations are used to verify the effectiveness of the scheme.


Author(s):  
Mohan Santhakumar ◽  
Jinwhan Kim

This paper proposes a new tracking controller for autonomous underwater vehicle-manipulator systems (UVMSs) using the concept of model reference adaptive control. It also addresses the detailed modeling and simulation of the dynamic coupling between an autonomous underwater vehicle and manipulator system based on Newton–Euler formulation scheme. The proposed adaptation control algorithm is used to estimate the unknown parameters online and compensate for the rest of the system dynamics. Specifically, the influence of the unknown manipulator mass on the control performance is indirectly captured by means of the adaptive control scheme. The effectiveness and robustness of the proposed control scheme are demonstrated using numerical simulations.


2017 ◽  
Vol 6 (4) ◽  
pp. 1-16 ◽  
Author(s):  
A. Almatroud Othman ◽  
M.S.M. Noorani ◽  
M. Mossa Al-sawalha

Function projective dual synchronization between two pairs of hyperchaotic systems with fully unknown parameters for drive and response systems is investigated. On the basis of the Lyapunov stability theory, a suitable and effective adaptive control law and parameters update rule for unknown parameters are designed, such that function projective dual synchronization between the hyperchaotic Chen system and the hyperchaotic Lü system with unknown parameters is achieved. Theoretical analysis and numerical simulations are presented to demonstrate the validity and feasibility of the proposed method.


Author(s):  
J Wang ◽  
M F Hsieh

This paper describes a vehicle stability control (VSC) system using a vehicle yaw-inertia- and mass-independent adaptive control law. As a primary vehicle active control system, VSC can significantly improve vehicle driving safety for passenger cars and enhance trajectory tracking accuracy for other applications such as autonomous, surveillance, and mobile robot vehicles. For the designs of vehicle dynamic control systems, vehicle yaw inertia and mass are two of the most important parameters. However, in practical applications, vehicle yaw inertia and mass often change with vehicle payload and load distribution. In this paper, an adaptive control law is proposed to treat the vehicle yaw inertia and mass as unknown parameters and automatically address their variations. For the proposed adaptive control law, asymptotic stability of the yaw rate tracking error was proved by a Lyapunov-like analysis for certain vehicle architectures under some reasonable assumptions. The performance of the yaw-inertia- and mass-independent adaptive VSC system was evaluated under several driving conditions (i.e. double lane changing on a slippery surface and braking on a split- μ surface tests) through simulation studies using a high-fidelity full-vehicle model provided by CarSim®.


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