Controller Design for Systems with Mismatched Sinusoidal Disturbance Using Disturbance Compensation Gain

2018 ◽  
Vol 24 (6) ◽  
pp. 482-489
Author(s):  
Minsoo Han ◽  
In Hyuk Kim ◽  
Su Young Jang ◽  
Young Ik Son
Keyword(s):  
Controller Design ◽  
Disturbance Compensation ◽  
Sinusoidal Disturbance

Adaptive Sinusoidal Disturbance Rejection in Linear Discrete-Time Systems—Part II: Experiments

1999 ◽  
Vol 121 (4) ◽  
pp. 655-659 ◽  
Author(s):  
Foued Ben Amara ◽  
Pierre T. Kabamba ◽  
A. Galip Ulsoy
Keyword(s):  
Controller Design ◽  
Adaptive Controller ◽  
Companion Paper ◽  
Noise Cancellation ◽  
Adaptive Noise Cancellation ◽  
Stabilizing Controllers ◽  
Discrete Time Systems ◽  
Sinusoidal Disturbance ◽  
Adaptive Noise ◽  
Time Systems

The problem of adaptive noise cancellation in an acoustic duct is discussed. An adaptive controller design approach based on parametrizing the set of stabilizing controllers using the Youla parametrization and tuning the Youla parameter to achieve regulation was presented in a companion paper [3]. Three controller adaptation algorithms are implemented to solve the noise cancellation problem in an acoustic duct. The experimental results indicate a mixed performance for each of the adaptation algorithms, with good performances observed only in some frequency ranges. The discrepancy between the expected and the observed performances is attributed to unmodeled nonlinearities in the speakers.

Continuous Time Controller Design

IEE Review ◽  
1991 ◽  
Vol 37 (6) ◽  
pp. 228
Author(s):  
Stephen Barnett
Keyword(s):  
Continuous Time ◽  
Controller Design

Path Tracking Controller Design of Automatic Guided Vehicle Based on Four-Wheeled Omnidirectional Motion Model

2020 ◽  
Vol 17 (2) ◽  
pp. 7996-8010
Author(s):  
X. Wu ◽  
Y. Yang
Keyword(s):  
Control System ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Threshold Value ◽  
Position Angle ◽  
Path Tracking ◽  
Global Coordinate System ◽  
Automatic Guided Vehicle ◽  
Input Variables ◽  
Industrial Pc

This paper presents a new design of omnidirectional automatic guided vehicle based on a hub motor, and proposes a joint controller for path tracking. The proposed controller includes two parts: a fuzzy controller and a multi-step predictive optimal controller. Firstly, based on various steering conditions, the kinematics model of the whole vehicle and the pose (position, angle) model in the global coordinate system are introduced. Secondly, based on the modeling, the joint controller is designed. Lateral deviation and course deviation are used as the input variables of the control system, and the threshold value is switched according to the value of the input variable to realise the correction of the large range of posture deviation. Finally, the joint controller is implemented by using the industrial PC and the self-developed control system based on the Freescale minimum system. Path tracking experiments were made under the straight and circular paths to test the ability of the joint controller for reducing the pose deviation. The experimental results show that the designed guided vehicle has excellent ability to path tracking, which meets the design goals.

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