scholarly journals Automatic target adjusting braking of a shunting stock with an adaptive control law

2021 ◽  
Vol 2094 (5) ◽  
pp. 052069
Author(s):  
S P Kruglov ◽  
S V Kovyrshin ◽  
P Yu Ivanov ◽  
A A Korsun ◽  
A S Kovshin
Keyword(s):  
Adaptive Control ◽  
Reference Model ◽  
Control Object ◽  
Parametric Identification ◽  
Simulation Modelling ◽  
Target Point ◽  
Braking Control ◽  
Adaptive Control Algorithm ◽  
Adaptive Control Law ◽  
A Current

Abstract The article deals with the problem of automation of target adjusting braking of a shunting stock. It is proposed to build it on the basis of an adaptive control algorithm capable of functioning under the current uncertainty of the parameters of the control object. It is based on a scheme with a current parametric identification assigned by an implicit reference model and using “simplified adaptivity conditions”. For the synthesis of the control, the approach implemented in a standard locomotive system for automatic braking control to maintain the target speed of movement depending on the distance to the target point is used. The results of simulation modelling are presented.

Model Reference Adaptive Algorithm Designed for Automatic Train Braking Control

2012 ◽  
Vol 253-255 ◽  
pp. 1374-1379 ◽  
Author(s):  
Heng Yu Luo ◽  
Hong Ze Xu
Keyword(s):  
Adaptive Control ◽  
Control Algorithm ◽  
Reference Model ◽  
Lyapunov Stability Theory ◽  
Reference Trajectory ◽  
Train Operation ◽  
Braking Control ◽  
Braking Process ◽  
Automatic Train Operation ◽  
Adaptive Control Algorithm

This paper investigates the automatic train braking control problem of ATC (Automatic Train Control) system under uncertain disturbances. An adaptive control algorithm is developed to ensure high precision tracking performance of the acceleration during the braking process, according to a standard reference model which has been widely used in the urban vehicles. The control parameter’s adaptive law is strictly deduced based on the Lyapunov Stability Theory. Rigorous analysis has shown that the train controlled by this method based ATO (Automatic Train Operation) system can effectively track the reference trajectory. Numerical simulation also verifies the effectiveness of this adaptive control algorithm.

scholarly journals Using the fractional order calculus in the combination of the MIT and Lyapunov stability method

2020 ◽  
Vol 11 (3) ◽  
pp. 220-225
Author(s):  
Simona Coman ◽  
Cristian Boldisor
Keyword(s):  
Adaptive Control ◽  
Fractional Order ◽  
Lyapunov Stability ◽  
Reference Model ◽  
Main Idea ◽  
Control Technique ◽  
Fractional Order Calculus ◽  
Original Contribution ◽  
Stability Method ◽  
Adaptive Control Law

AbstractThe main idea of the current paper consists in introducing the fractional order calculus in a control system. To control the system, an adaptive control technique with reference model is used. The fractional order models for the plant and reference model are obtained. To achieve the performances imposed by the fractional order reference model, a fractional order adaptive control law is proposed, which is a combination of two methods (MIT and Lyapunov stability). The original contribution in this paper is the use of fractional order calculus in the combined MIT and Lyapunov stability method and showing the dynamic behavior of the system. Several simulations are used to emphasize the effectiveness and benefits of the proposed method.

An Efficient Robust Adaptive Control Law For Robot Manipulators

1996 ◽  
Vol 210 (4) ◽  
pp. 363-372 ◽  
Author(s):  
H Yu ◽  
S Lloyd
Keyword(s):  
Adaptive Control ◽  
Variable Structure ◽  
Robust Adaptive Control ◽  
Control Law ◽  
Computationally Efficient ◽  
Structure Control ◽  
Robust Adaptive ◽  
The Stability ◽  
Adaptive Control Algorithm ◽  
Adaptive Control Law

A computationally efficient robust adaptive control algorithm is proposed in this paper. The regressors are implemented using the desired trajectories to replace the actual trajectories in order to reduce the computational burden. To reduce the disturbance introduced by this replacement, an adaptive variable structure control law is proposed. The proposed adaptive control law results in a system that is robust to bounded input disturbances. A small modification of the control law makes the system robust to more general input disturbances. The stability analysis is in the Lyapunov sense. Simulation results demonstrate the validity of the proposed scheme.

scholarly journals ADAPTIVE CONTROL ALGORITHM FOR MECHANICAL SYSTEMS WITH IMPLICIT REFERENCE MODEL AND FILTRATION

2018 ◽  
pp. 124-130 ◽  
Author(s):  
O.P. Tomchina ◽  
◽  
D.V. Gorlatov ◽  
D.V. Tomchin ◽  
T.A. Sventzitzkaya ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Control Algorithm ◽  
Reference Model ◽  
Mechanical Systems ◽  
Adaptive Control Algorithm

An Improved Multi-Level Adaptive Control Algorithm Based on Parameters Self-Tuning for a Class of SISO Nonlinear Systems

2015 ◽  
Vol 740 ◽  
pp. 247-250
Author(s):  
Feng Qiao ◽  
Zhi Zhen Liu
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Partial Derivative ◽  
Control Algorithm ◽  
Control Law ◽  
Self Tuning ◽  
On Line ◽  
Multi Level ◽  
Adaptive Control Algorithm ◽  
Adaptive Control Law

In this paper, a multi-level adaptive control algorithm using parameters self-tuning is proposed for improving the tracking performance of a class of SISO nonlinear systems. This scheme is comprised of the pseudo partial derivative estimation law and the adaptive control law. The adaptive control law is derived from a novel higher order weighted one-step-ahead criterion function which exploits more previous control information. In order to identify the laws’ penalty factors which partly imply the dynamics of the system, an approach of parameters self-tuning is proposed with on-line recursive gradient algorithm. This design is model free and depends directly on the pseudo partial derivative updating on-line with the input and output data Simulation examples are provided to illustrate the effectiveness of the proposed method.

scholarly journals REPETITIVE ADAPTIVE CONTROL OF NONLINEAR UNCERTAIN PLANT WITH INPUT SATURATION

2021 ◽  
pp. 122-135
Author(s):  
E.A. Shelenok ◽  
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Control Algorithm ◽  
Reference Model ◽  
Input Saturation ◽  
Adaptive Control System ◽  
Bounded Disturbances ◽  
Adaptive Control Algorithm ◽  
Fast Acting ◽  
Nonlinear Plant

The article proposes solution to the problem of synthesizing adaptive control algorithm for dy-namic T-periodic nonlinear plant operating under conditions of structural and parametric uncer-tainty, in the presence of input restrictions and constant bounded disturbances. The hyperstabil-ity criterion, L-dissipativity conditions, fast-acting filter-correctors, and an implicit reference model are used as the methods for synthesis of repetitive adaptive control system.

scholarly journals The MRAC based-adaptive control system for controlling the speed of direct current motor

2020 ◽  
Vol 19 (2) ◽  
pp. 723
Author(s):  
Manh-Cuong Nguyen ◽  
Duc-Phuc Vuong ◽  
Trong-Thang Nguyen
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Direct Current ◽  
Reference Model ◽  
Control Object ◽  
Adaptive Controller ◽  
Adaptive Control System ◽  
Control Loop ◽  
Control Loops

<p><span>This research aims to propose an adaptive control system for controlling the speed of the Direct Current (DC) motor. The system consists of two control loops: the first control loop is a traditional PID controller and the second control loop is an adaptive controller. The role of the adaptive controller is adjusting the output of the control object follows with the output of the reference model. The adjustment mechanism is very simple, but the quality of the whole system is very high: the conversion time is short and there isn't overshoot. The quality of the proposed adaptive control system is also compared to the traditional PID control system to show the advantages of the new system.</span></p>

scholarly journals IMPLEMENTATION OF AN ADAPTIVE CONTROL ALGORITHM WITH A REFERENCE MODEL FOR PROGRAMMABLE LOGIC CONTROLLERS

2021 ◽  
pp. 30-38
Author(s):  
A.N. Rybalev ◽  
Keyword(s):  
Adaptive Control ◽  
Control Algorithm ◽  
Reference Model ◽  
Software Implementation ◽  
Programmable Logic ◽  
Adaptive Control System ◽  
Practical Evaluation ◽  
Combined Models ◽  
Parametric Adjustment ◽  
Adaptive Control Algorithm

The paper proposes approaches to the software implementation of an adaptive control system with a reference model and parametric adjustment of the regulator on programmable logic con-trollers (PLC) and with practical evaluation of synthesized systems on combined models, includ-ing a simulation model of the controlled plant and a virtual or real controller.

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