An Optimal Preview Acceleration Driver Model with a Correction Factor for Vehicle Directional Control

2013 ◽  
Vol 437 ◽  
pp. 623-628 ◽  
Author(s):  
Hsin Guan ◽  
Li Zeng Zhang ◽  
Xin Jia
Keyword(s):  
Correction Factor ◽  
Closed Loop ◽  
Reference Model ◽  
Driver Model ◽  
Closed Loop System ◽  
Moving Vehicle ◽  
Directional Control ◽  
Modeling Errors ◽  
Acceleration Model ◽  
Model Reference Adaptive

Parameters of the optimal preview acceleration driver model for vehicle directional control are determined by drivers delay/lag time and parameters of the reference model of the controlled vehicle. A moving vehicle is a time-varying and nonlinear system, so it is difficult to obtain accurate parameters of the reference model. If large modeling errors of the reference model occur, the classic driver model cannot ensure the driver/vehicle closed-loop system have a satisfactory performance. In this paper, an improved optimal preview acceleration model with a correction factor was proposed, which is based on sensitivity analysis and MRAC (the model reference adaptive control). Simulation results show that the improved driver model has more satisfactory adaptability and robustness comparing with the classic driver model.

scholarly journals Design of a model reference adaptive PID control algorithm for a tank system

2021 ◽  
Vol 11 (1) ◽  
pp. 300
Author(s):  
Yohan Darcy Mfoumboulou
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Closed Loop ◽  
Reference Model ◽  
Pi Controller ◽  
Loop System ◽  
Closed Loop System ◽  
Model Reference ◽  
Adaptive Pid Control ◽  
Model Reference Adaptive

This paper describes the design of an adaptive controller based on model reference adaptive PID control (MRAPIDC) to stabilize a two-tank process when large variations of parameters and external disturbances affect the closed-loop system. To achieve that, an innovative structure of the adaptive PID controller is defined, an additional PI is designed to make sure that the reference model produces stable output signals and three adaptive gains are included to guarantee stability and robustness of the closed-loop system. Then, the performance of the model reference adaptive PID controller on the behaviour of the closed-loop system is compared to a PI controller designed on MATLAB when both closed-loop systems are under various conditions. The results demonstrate that the MRAPIDC performs significantly better than the conventional PI controller.

A Parametric Study of the Modified Model Reference Adaptive Control Scheme

1998 ◽  
Vol 120 (3) ◽  
pp. 814-821
Author(s):  
H. M. Sardar ◽  
M. Ahmadian
Keyword(s):  
Closed Loop ◽  
Simulation Analysis ◽  
Adaptive Controller ◽  
Loop System ◽  
Closed Loop System ◽  
Model Reference ◽  
Modified Model ◽  
Control Scheme ◽  
Inertial Nonlinearities ◽  
Model Reference Adaptive

The validity of the claim by many studies that the damping and stiffness forces can be ignored when designing a model reference adaptive controller, is examined. For a simple plant, the sensitivity of the closed loop system to the inertial, damping, and stiffness nonlinearities are investigated, through a simulation analysis. It is shown that the closed loop system is sensitive to the changes in the inertial nonlinearities, and relatively insensitive to variations in the damping and stiffness forces. This supports the assumption made in many previous studies.

scholarly journals A NARX Model Reference Adaptive Control Scheme: Improved Disturbance Rejection Fractional-Order PID Control of an Experimental Magnetic Levitation System

Algorithms ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 201
Author(s):  
Hossein Alimohammadi ◽  
Baris Baykant Alagoz ◽  
Aleksei Tepljakov ◽  
Kristina Vassiljeva ◽  
Eduard Petlenkov
Keyword(s):  
Control System ◽  
Disturbance Rejection ◽  
Closed Loop ◽  
Control Structure ◽  
Magnetic Levitation ◽  
Reference Model ◽  
Control Performance ◽  
Control Loops ◽  
Model Reference Adaptive ◽  
Narx Model

Real control systems require robust control performance to deal with unpredictable and altering operating conditions of real-world systems. Improvement of disturbance rejection control performance should be considered as one of the essential control objectives in practical control system design tasks. This study presents a multi-loop Model Reference Adaptive Control (MRAC) scheme that leverages a nonlinear autoregressive neural network with external inputs (NARX) model in as the reference model. Authors observed that the performance of multi-loop MRAC-fractional-order proportional integral derivative (FOPID) control with MIT rule largely depends on the capability of the reference model to represent leading closed-loop dynamics of the experimental ML system. As such, the NARX model is used to represent disturbance-free dynamical behavior of PID control loop. It is remarkable that the obtained reference model is independent of the tuning of other control loops in the control system. The multi-loop MRAC-FOPID control structure detects impacts of disturbance incidents on control performance of the closed-loop FOPID control system and adapts the response of the FOPID control system to reduce the negative effects of the additive input disturbance. This multi-loop control structure deploys two specialized control loops: an inner loop, which is the closed-loop FOPID control system for stability and set-point control, and an outer loop, which involves a NARX reference model and an MIT rule to increase the adaptation ability of the system. Thus, the two-loop MRAC structure allows improvement of disturbance rejection performance without deteriorating precise set-point control and stability characteristics of the FOPID control loop. This is an important benefit of this control structure. To demonstrate disturbance rejection performance improvements of the proposed multi-loop MRAC-FOPID control with NARX model, an experimental study is conducted for disturbance rejection control of magnetic levitation test setup in the laboratory. Simulation and experimental results indicate an improvement of disturbance rejection performance.

Algorithm for Approximate Model Matching for Loops With Non-Negligible Feedback Dynamics

1998 ◽  
Vol 120 (3) ◽  
pp. 394-398
Author(s):  
Luis Antonio Aguirre
Keyword(s):  
Closed Loop ◽  
Reference Model ◽  
Approximate Model ◽  
New Method ◽  
Moment Matching ◽  
Model Matching ◽  
Closed Loop System ◽  
Matching Problem ◽  
New Approach ◽  
Numerical Examples

This paper develops a new algorithm to solve the model matching problem in cases where the feedback dynamics should be taken into account in the design of the closed-loop system. One of the main features of the new method is that the matching is carried out by moment matching and is therefore approximate. The new algorithm is computationally simple and it permits the designer to choose relatively simple structures for the reference model and the controller. Numerical examples are included to illustrate the new approach.

scholarly journals Directional Control of a Driver-Heavy-Vehicle Closed-Loop System

2011 ◽  
Vol 2-3 ◽  
pp. 33-38
Author(s):  
Shao Hua Li ◽  
Shao Pu Yang ◽  
Na Chen
Keyword(s):  
Closed Loop ◽  
Single Point ◽  
Equations Of Motion ◽  
Loop System ◽  
Dynamic Responses ◽  
Heavy Vehicle ◽  
Closed Loop System ◽  
Time Step ◽  
Steering Angle ◽  
Directional Control

A two degree of freedom (DOF) lateral dynamic model for a three-axe heavy vehicle is set up and the vehicle ordinary differential equations of motion are derived. The nonlinear lateral tire forces are obtained by Gim model with vertical loads, slip angles and cornering performances of front and rear tires being input parameters. A revised closed-loop single-point preview method is proposed to model the driver’s directional control performance. In this proposed method, the steering angle of front wheels is calculated in real time according to the track error between a certain point ahead of the vehicle and the required route. Then the steering angle is input into the vehicle model to gain the dynamic responses and position of the vehicle in next time step. Thus the driver-heavy-vehicle closed-loop system is built. The dynamic responses of the system are simulated on the condition of double lane change and the effects of system parameters on the path following behavior of the vehicle are researched. Then the advice on how to improve the vehicle directional control ability can be brought forward.

scholarly journals H∞ Tracking Control of Fuzzy Dynamic Output for Nonlinear Networked System with Packet Dropouts

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Yang Wang ◽  
Jinna Li ◽  
Xiaolei Ji
Keyword(s):  
Output Feedback ◽  
Tracking Control ◽  
Closed Loop ◽  
Reference Model ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
Loop System ◽  
Dynamic Output Feedback ◽  
Closed Loop System ◽  
Dynamic Output

The tracking control of H∞ dynamic output feedback is proposed for the fuzzy networked systems of the same category, in which each system is discrete-time nonlinear and is missing measurable data. In other words, the loss of data packet occurs randomly in both the uplink and the downlink. The independent variables that are called the Bernoulli random variables are considered to design the loss of data packets. The method of parallel distributed compensation (PDC) in terms of the T-S fuzzy model is applied to investigate the dynamic controller of tracking control on the systems. Then, it is presented that the analytical H∞ performance of the output error between the reference model and the fuzzy model for the closed-loop system containing dynamic output feedback controller is proven. Furthermore, the achieved sufficient conditions in terms of LMIs ensure that the closed-loop system is stochastically stable in the H∞ sense. Finally, a numerical system is offered to show the effectiveness of the established technique.

A Study on the Effect of Driver Model Parameters on the Performance of Driver-Vehicle-Road Closed-Loop System

2013 ◽  
Vol 470 ◽  
pp. 604-608
Author(s):  
Li Zeng Zhang ◽  
Hsin Guan ◽  
Xin Jia ◽  
Ping Ping Lu ◽  
Yong Shang Chen
Keyword(s):  
Delay Time ◽  
Closed Loop ◽  
System Simulation ◽  
Lag Time ◽  
Loop System ◽  
Driver Model ◽  
Model Parameters ◽  
Closed Loop System

The concept of DODF and other two evaluation indices based on DODF were proposed. Based on the optimal preview acceleration driver model, the effect of driver model parameters on the performance of driver-vehicle-road closed-loop system was studied by the closed-loop system simulation. The results show that the preview time of a driver who has good driving habits should be always larger than a certain valueTP0, the increase of both nerve delay timetdand muscle lag timeThlead to the increase ofTP0, andtdhas more effect onTP0thanThdoes. The increase of bothtdandThlead to the decrease of DODF, andtdhas more effect on DODF thanThdoes. Furthermore, the increase of bothtdandThalso lead to the increase of both tracking indexJEMand driving load indexTCM,tdhas more effect onJEMthanThdoes, andThhas more effect onTCMthantddoes.

Simulation for Vehicle Handling Performance Based on the Cybernetic Model of “Driver-Vehicle-Road” Closed-Loop System

2011 ◽  
Vol 299-300 ◽  
pp. 1256-1261
Author(s):  
Hui He ◽  
Kun Zhang ◽  
Peng Wang
Keyword(s):  
Closed Loop ◽  
Steering System ◽  
Loop System ◽  
System Model ◽  
Driver Model ◽  
Closed Loop System ◽  
Cybernetic Model ◽  
Vehicle Performance ◽  
Vehicle Handling ◽  
Handling Performance

In this paper, a cybernetic model of “driver-vehicle-road” closed-loop system including a driver model and a steering system model is built under the MATLAB/Simulink environment. Then, the influence of different dynamic characteristics of steering system on vehicle handling and stability is studied. The results suggest that the “driver-vehicle” model built has a high tracking precision in following the path; Increasing the rigidity of steering system or decreasing the dilatory distance of front tire can enhance the tracking precision and can minish the driving burden and the fatalness of side-tip, the total evaluation result of vehicle performance will be optimized as well.

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