Robustness of adaptive discrete-time LQG control for first-order systems

2010 ◽  
Vol 58 (1) ◽  
pp. 89-97
Author(s):  
A. Królikowski ◽  
D. Horla
Keyword(s):  
Control System ◽  
Discrete Time ◽  
Point Of View ◽  
Constrained Control ◽  
Certainty Equivalence ◽  
First Order ◽  
Lqg Control ◽  
Self Tuning ◽  
And Performance ◽  
Performance Robustness

Robustness of adaptive discrete-time LQG control for first-order systemsThe discrete-time adaptive LQG control of first-order systems is considered from robustness point of view. Both stability and performance robustness are analyzed for different control system structures. A case of amplitude-constrained control is presented, and application of certainty equivalence for self-tuning implementation is also discussed.

scholarly journals Discrete-time sliding mode observer for the state estimation of a manoeuvring target

2019 ◽  
Vol 233 (7) ◽  
pp. 847-854
Author(s):  
K Harikumar ◽  
Titas Bera ◽  
Rajarshi Bardhan ◽  
Suresh Sundaram
Keyword(s):  
Boundary Layer ◽  
Discrete Time ◽  
Sliding Mode ◽  
Estimation Error ◽  
Sliding Mode Observer ◽  
Unknown Parameters ◽  
First Order ◽  
Error Dynamics ◽  
And Performance ◽  
The Stability

This article addresses the problem of estimating the position, velocity, and acceleration of a manoeuvring target from noisy position measurements. A discrete-time sliding mode observer is designed to handle unmeasured disturbance input and measurement noise. A first-order linear dynamics is considered for target acceleration. The acceleration input command and the pole of the first-order acceleration dynamics are considered to be unknown parameters with known upper bounds. A finite non-zero boundary layer is employed to reduce the chattering phenomenon typically associated with sliding mode observers. Analysis of estimation error dynamics is presented for the case where the discrete-time sliding mode observer is operating outside the boundary layer and also within the boundary layer. An algorithm is developed for obtaining the observer gain vector that guarantees the stability of the error dynamics. Numerical simulations and experimental results are presented to validate the stability and performance of the proposed observer.

Extension of the Dual-rate Control System Independent of the Discrete-time Output Response

2019 ◽  
Vol 139 (8) ◽  
pp. 889-890
Author(s):  
Takao Sato ◽  
Natsuki Kawaguchi ◽  
Nozomu Araki ◽  
Yasuo Konishi
Keyword(s):  
Control System ◽  
Discrete Time ◽  
Rate Control ◽  
Output Response

An Analytical Transient Tire Model

2001 ◽  
Vol 29 (2) ◽  
pp. 108-132 ◽  
Author(s):  
A. Ghazi Zadeh ◽  
A. Fahim
Keyword(s):  
Transient Behavior ◽  
Stability Control ◽  
Vehicle Stability ◽  
Tire Model ◽  
Steering Angle ◽  
First Order ◽  
Vehicle Stability Control ◽  
Proposed Model ◽  
Depth Study ◽  
And Performance

Abstract The dynamics of a vehicle's tires is a major contributor to the vehicle stability, control, and performance. A better understanding of the handling performance and lateral stability of the vehicle can be achieved by an in-depth study of the transient behavior of the tire. In this article, the transient response of the tire to a steering angle input is examined and an analytical second order tire model is proposed. This model provides a means for a better understanding of the transient behavior of the tire. The proposed model is also applied to a vehicle model and its performance is compared with a first order tire model.

Determinants of Control System Design in Divisionalized Firms

2004 ◽  
Vol 79 (3) ◽  
pp. 545-570 ◽  
Author(s):  
Margaret A. Abernethy ◽  
Jan Bouwens ◽  
Laurence van Lent
Keyword(s):  
Control System ◽  
System Design ◽  
Performance Measures ◽  
Simultaneous Equation ◽  
Equation Model ◽  
Control System Design ◽  
Information Asymmetries ◽  
Endogenous Variables ◽  
And Performance ◽  
Using Data

We investigate two determinants of two choices in the control system of divisionalized firms, namely decentralization and use of performance measures. The two determinants are those identified in the literature as important to control system design: (1) information asymmetries between corporate and divisional managers and (2) division interdependencies. We treat decentralization and performance measurement choices as endogenous variables and examine the interrelation among these choices using a simultaneous equation model. Using data from 78 divisions, our results indicate that decentralization is positively related to the level of information asymmetries and negatively to intrafirm interdependencies, while the use of performance measures is affected by the level of interdependencies among divisions within the firm, but not by information asymmetries. We find some evidence that decentralization choice and use of performance measures are complementary.

scholarly journals Self-Tuning Two Degree-of-Freedom Proportional–Integral Control System Based on Reinforcement Learning for a Multiple-Input Multiple-Output Industrial Process That Suffers from Spatial Input Coupling

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 487
Author(s):  
Fumitake Fujii ◽  
Akinori Kaneishi ◽  
Takafumi Nii ◽  
Ryu’ichiro Maenishi ◽  
Soma Tanaka
Keyword(s):  
Control System ◽  
Reinforcement Learning ◽  
Pid Control ◽  
Multiple Input Multiple Output ◽  
Industrial Process ◽  
Pi Controller ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Self Tuning ◽  
Two Degree Of Freedom

Proportional–integral–derivative (PID) control remains the primary choice for industrial process control problems. However, owing to the increased complexity and precision requirement of current industrial processes, a conventional PID controller may provide only unsatisfactory performance, or the determination of PID gains may become quite difficult. To address these issues, studies have suggested the use of reinforcement learning in combination with PID control laws. The present study aims to extend this idea to the control of a multiple-input multiple-output (MIMO) process that suffers from both physical coupling between inputs and a long input/output lag. We specifically target a thin film production process as an example of such a MIMO process and propose a self-tuning two-degree-of-freedom PI controller for the film thickness control problem. Theoretically, the self-tuning functionality of the proposed control system is based on the actor-critic reinforcement learning algorithm. We also propose a method to compensate for the input coupling. Numerical simulations are conducted under several likely scenarios to demonstrate the enhanced control performance relative to that of a conventional static gain PI controller.

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