An Improved Optimal Adaptive Control Method for MIMO Sine Vibration Control of a Multichannel Coupled System

2018 ◽  
Author(s):  
Chao Li ◽  
Zhangwei Chen ◽  
Hongfei Zu ◽  
Yugang Zhao
Keyword(s):  
Adaptive Control ◽  
Control Algorithm ◽  
Control Method ◽  
Coupled System ◽  
Excellent Performance ◽  
Fast Convergence Rate ◽  
Accelerate Convergence ◽  
The Stability ◽  
Adaptive Control Algorithm ◽  
Response Vector

This paper proposes an improved optimal adaptive control algorithm to accelerate convergence for sine control of general multichannel coupled system, as well as enhance the stability. First of all, the convergence of traditional multi-input multi-output (MIMO) sine control method is analytically investigated in the presence of frequency response function (FRF) error. Then, the controller with the improved optimal adaptive control algorithm is developed, where a high-precision algorithm for amplitude and phase estimation is proposed to guarantee the accuracy of the response vector calculation. Numerical simulation results show that the proposed method possess excellent performance with fast convergence rate and strong robustness.

Dynamics and Controller Design of a Screw Wheel Drive Holonomic Rescue Robot

2012 ◽  
Author(s):  
Emin Faruk Kececi
Keyword(s):  
Adaptive Control ◽  
Control Algorithm ◽  
Controller Design ◽  
Mechanical Design ◽  
Future Research ◽  
Rescue Robot ◽  
Wheel Drive ◽  
The Stability ◽  
Adaptive Control Algorithm ◽  
Future Work

This paper reports a holonomic rescue robot where the robot is driven by screw wheels. The necessity of a such platform is explained and the mechanical design and the actual prototype are presented. In order to design an adaptive control algorithm to ensure the trajectory tracking, the dynamical model is constructed. The stability of the adaptive control algorithm is proven with Lyapunov stability analysis. The necessary electronics to implement the controller algorithm is explained and the conclusions and future work section reports the results of the study as well as the future research directions.

Lyapunov Based Adaptive Control Method for Hydraulic Servo Drive

2016 ◽  
Author(s):  
Hamid Roozbahani ◽  
Konstantin Frumkin ◽  
Heikki Handroos
Keyword(s):  
Adaptive Control ◽  
Control Algorithm ◽  
Environmental Changes ◽  
Control Method ◽  
Servo System ◽  
Adaptive Controller ◽  
Servo Drive ◽  
Hydraulic Servo ◽  
Hydraulic Servo System ◽  
Adaptive Control Algorithm

Adaptive control systems are one of the most significant research directions of modern control theory. It is well known that every mechanical appliance’s behavior noticeably depends on environmental changes, functioning-mode parameter changes and changes in technical characteristics of internal functional devices. An adaptive controller involved in control process allows reducing an influence of such changes. In spite of this such type of control methods is applied seldom due to specifics of a controller designing. The work presented in this paper shows the design process of the adaptive controller built by Lyapunov’s function method for a hydraulic servo system. The modeling of the hydraulic servo system were conducting with MATLAB® software including Simulink® and Symbolic Math Toolbox™. In this study, the Jacobi matrix linearization of the object’s mathematical model and derivation of the suitable reference models based on Newton’s characteristic polynomial were applied. In addition, an intelligent adaptive control algorithm and system model including its nonlinearities was developed to solve Lyapunov’s equation. Developed algorithm works properly and considered plant is met requirement of functioning with. The results shows that the developed adaptive control algorithm increases system performance in use devices significantly and might be used for correction of system’s behavior and dynamics.

Control of a Nonlinear Pressure-Regulating Engine Bleed Valve in Aircraft Air Management Systems

2013 ◽  
Author(s):  
John R. Cooper ◽  
Chengyu Cao ◽  
Jiong Tang
Keyword(s):  
Adaptive Control ◽  
Control Algorithm ◽  
Control Method ◽  
Control Valve ◽  
System Model ◽  
Management Systems ◽  
Commercial Aircraft ◽  
Integral Controller ◽  
Proportional Integral Controller ◽  
Adaptive Control Algorithm

This paper presents an adaptive control algorithm, based on the ℒ 1 adaptive control method, for controlling the pressure of engine bleed air in a commercial aircraft. The pressure is affected by a control valve that is part of a larger air management system which includes control valves for temperature and flow rate as well as a heat exchanger or precooler. A system model is presented including valve hysteresis due to backlash and dry friction. Simulations are conducted for a control valve subject to unmeasured disturbance, and the adaptive control results are compared to those of a traditional proportional-integral controller.

Adaptive Control Algorithm of the RF-537 Controller

1997 ◽  
Vol 30 (7) ◽  
pp. 201-206
Author(s):  
Zbigniew Świder ◽  
Leszek Trybus
Keyword(s):  
Adaptive Control ◽  
Control Algorithm ◽  
Adaptive Control Algorithm

Online parameter estimation and adaptive control with limited information in structures

2021 ◽  
pp. 107754632110191
Author(s):  
Fereidoun Amini ◽  
Elham Aghabarari
Keyword(s):  
Parameter Estimation ◽  
Adaptive Control ◽  
Least Squares ◽  
Control Algorithm ◽  
Least Squares Method ◽  
Recursive Least Squares ◽  
Limited Information ◽  
Online Identification ◽  
Recursive Least Squares Method ◽  
Adaptive Control Algorithm

An online parameter estimation is important along with the adaptive control, that is, a time-dependent plant. This study uses both online identification and the simple adaptive control algorithm with velocity feedback. The recursive least squares method was used to identify the stiffness and damping parameters of the structure’s stories. Identification was carried out online without initial estimation and only by measuring the structural responses. The limited information regarding sensor measurements, parameter convergence, and the effects of the covariance matrix is examined. The integration of the applied online identification, the appropriate reference model selection in simple adaptive control, and adopting the proportional integral filter was used to limit the structural control response error. Some numerical examples are simulated to verify the ability of the proposed approach. Despite the limited information, the results show that the simultaneous use of online identification with the recursive least squares method and simple adaptive control algorithm improved the overall structural performance.

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