scholarly journals Logarithmic norm based robust adaptive state‐feedback control of the linear time‐varying systems under system uncertainty and external disturbances

2020 ◽  
Vol 3 (2) ◽  
Author(s):  
Robert Vrabel
Keyword(s):  
Feedback Control ◽  
State Feedback ◽  
Linear Time ◽  
State Feedback Control ◽  
Time Varying ◽  
External Disturbances ◽  
System Uncertainty ◽  
Logarithmic Norm ◽  
Time Varying Systems ◽  
Robust Adaptive

Stabilization of linear time-varying systems using proportional-derivative state feedback

2017 ◽  
Vol 40 (7) ◽  
pp. 2100-2115 ◽  
Author(s):  
Taha HS Abdelaziz
Keyword(s):  
Degrees Of Freedom ◽  
State Feedback ◽  
Linear Time ◽  
State Feedback Control ◽  
Time Varying ◽  
Closed Loop Systems ◽  
Continuous Time Systems ◽  
Time Varying Systems ◽  
Small Gain ◽  
Time Systems

This paper presents the stabilization approach for linear time-varying continuous-time systems using proportional-derivative (PD) state feedback control. The solvability conditions for the problem are considered. The general analytical expressions for the PD controller gains are derived, which describe the available degrees of freedom offered by PD state feedback. The non-uniqueness of the controller gains is utilized to obtain closed-loop systems with small gain elements. Two numerical examples are introduced to demonstrate the effectiveness of the proposed approach.

NN approach to state-feedback control of high-order non-linear time-delay systems with time-varying control coefficient

2016 ◽  
Vol 40 (1) ◽  
pp. 163-170 ◽  
Author(s):  
Min Huifang ◽  
Duan Na
Keyword(s):  
Neural Network ◽  
Feedback Control ◽  
State Feedback ◽  
Linear Time ◽  
High Order ◽  
State Feedback Control ◽  
Delay Systems ◽  
Time Varying ◽  
Control Coefficient ◽  
Non Linear

This paper considers the adaptive state-feedback control problem for a class of high-order non-linear systems with unknown control coefficient and time delays. By applying the neural network approximation method and the Nussbaum function approach, the restrictions on non-linear functions and the conditions on the time-varying control coefficient are largely relaxed. In addition, an adaptive neural network state-feedback controller with only one adaptive parameter is successfully constructed by introducing proper Lyapunov–Krasovskii functionals and using the backstepping technique. The proposed scheme guarantees the closed-loop system to be semi-globally uniformly ultimately bounded. Finally, a simulation example demonstrates the effectiveness of the controller.

scholarly journals Switched H2-state-feedback control with application to a fighter aircraft

2019 ◽  
Vol 233 (14) ◽  
pp. 5428-5437
Author(s):  
Emre Kemer ◽  
Hasan Başak ◽  
Emmanuel Prempain
Keyword(s):  
Feedback Control ◽  
State Feedback ◽  
Linear Time ◽  
State Feedback Control ◽  
Time Varying ◽  
Fighter Aircraft ◽  
Control Laws ◽  
Use Of Time ◽  
External Signals ◽  
Parameter Dependent

This paper proposes two different [Formula: see text]-state-feedback controller synthesis algorithms for uncertain linear, time-varying, switched systems. The synthesis algorithms are based on a dwell-time approach, which makes use of time-varying parameter-dependent Lyapunov functions. The control laws consist of state-feedback controllers that are switched according to external signals. The proposed synthesis algorithms are then employed to design switched [Formula: see text]-state-feedback control laws for the longitudinal dynamics of the ADMIRE fighter benchmark model. The results obtained in simulation show the merits of the proposed approach.

scholarly journals Control of Linear Time-Varying Systems Using Forward Riccati Equation

1997 ◽  
Vol 119 (3) ◽  
pp. 536-540 ◽  
Author(s):  
Min-Shin Chen ◽  
Chung-yao Kao
Keyword(s):  
Boundary Condition ◽  
Riccati Equation ◽  
State Feedback ◽  
Linear Time ◽  
The State ◽  
State Feedback Control ◽  
Feedback Gain ◽  
Time Varying ◽  
Time Varying Systems ◽  
Future Information

This paper presents a new state feedback control design for linear time-varying systems. In conventional control designs such as the LQ optimal control, the state feedback gain is calculated off-line by solving a Differential Riccati Equation (DRE) backwards with the boundary condition set at some future time. The apparent disad-vantage of using a backward DRE is that future information of the system matrices is required to find the state feedback gain at every time instant. In this paper, an inversion state transformation is applied to the system so that the DRE associated with the transformed system becomes forward in the sense that its boundary condition is set at the initial time of operation (t = t0). As a result, the forward DRE can be calculated on-line without using future information of the system matrices.

The Swing Control of Cranes with Variable Rope Length Based on Linear Time Varying System Theory

2012 ◽  
Vol 461 ◽  
pp. 763-767
Author(s):  
Li Fu Wang ◽  
Zhi Kong ◽  
Xin Gang Wang ◽  
Zhao Xia Wu
Keyword(s):  
State Feedback ◽  
Closed Loop ◽  
Linear Time ◽  
Feedback Stabilization ◽  
Time Varying ◽  
Closed Loop System ◽  
Overhead Cranes ◽  
Time Varying Systems ◽  
Time Invariant ◽  
Time Invariant System

In this paper, following the state-feedback stabilization for time-varying systems proposed by Wolovich, a controller is designed for the overhead cranes with a linearized parameter-varying model. The resulting closed-loop system is equivalent, via a Lyapunov transformation, to a stable time-invariant system of assigned eigenvalues. The simulation results show the validity of this method.

State feedback control for uncertain switched systems with interval time-varying delay

2010 ◽  
Vol 13 (6) ◽  
pp. 1035-1042 ◽  
Author(s):  
Limin Wang ◽  
Cheng Shao ◽  
Xuanyu Liu
Keyword(s):  
Feedback Control ◽  
Switched Systems ◽  
State Feedback ◽  
State Feedback Control ◽  
Time Varying ◽  
Interval Time ◽  
Time Varying Delay ◽  
Varying Delay
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