Model-Reference Longitudinal Control for Automated Vehicle Systems

1980 ◽  
Vol 102 (2) ◽  
pp. 77-84 ◽  
Author(s):  
R. J. Caudill ◽  
S. L. Blasnik
Keyword(s):  
Behavioral Characteristics ◽  
Longitudinal Control ◽  
Model Reference ◽  
Automated Vehicle ◽  
Simulation Techniques ◽  
Traction Motors ◽  
Model Reference Control ◽  
Vehicle Systems ◽  
Control Concept ◽  
Fixed End

The problem of designing longitudinal control systems which provide acceleration and jerk limited response for automated vehicle systems is examined. Non-dimensional models of vehicles propelled by d-c traction motors are used to evaluate the feasibility of the model-reference control concept. Analytical and computer simulation techniques are used to evaluate performance and assure critical string behavioral characteristics - asymptotic string stability and fixed end-point speed transition region (proper curve negotiation).

Longitudinal Control for Automated Highway Vehicles

1982 ◽  
Vol 104 (2) ◽  
pp. 180-187 ◽  
Author(s):  
R. J. Caudill ◽  
P. Di Matteo ◽  
S. P. Thomas
Keyword(s):  
Control Systems ◽  
Internal Combustion Engines ◽  
Controller Design ◽  
Vehicle Control ◽  
Combustion Engines ◽  
Longitudinal Control ◽  
Model Reference Control ◽  
Control Concept ◽  
Simulation Results ◽  
Automated Highway

The problem of designing longitudinal control systems for automated highway vehicles powered by internal combustion engines is examined. Careful controller design is required so that the movement of freight and people may be achieved in the same roadway while maintaining stringent safety and operational standards. Individual vehicle control is achieved utilizing a modified proportional-error controller with switching boundaries. Longitudinal control of vehicle strings is based upon the model reference control concept. Analytical and computer simulation results indicate it is feasible to operate mixed vehicle strings.

Optimal Model Reference Control Scheme Design for Nonlinear Strict-Feedback Systems

2020 ◽  
Vol 38 (9A) ◽  
pp. 1342-1351
Author(s):  
Musadaq A. Hadi ◽  
Hazem I. Ali
Keyword(s):  
Reference Model ◽  
Feedback System ◽  
Optimization Method ◽  
Feedback Systems ◽  
Model Reference ◽  
Scheme Design ◽  
Model Reference Control ◽  
Control Scheme ◽  
Lyapunov Stability Analysis ◽  
Strict Feedback

In this paper, a new design of the model reference control scheme is proposed in a class of nonlinear strict-feedback system. First, the system is analyzed using Lyapunov stability analysis. Next, a model reference is used to improve system performance. Then, the Integral Square Error (ISE) is considered as a cost function to drive the error between the reference model and the system to zero. After that, a powerful metaheuristic optimization method is used to optimize the parameters of the proposed controller. Finally, the results show that the proposed controller can effectively compensate for the strictly-feedback nonlinear system with more desirable performance.

Data-driven model reference control design by prediction error identification

2017 ◽  
Vol 354 (6) ◽  
pp. 2628-2647 ◽  
Author(s):  
Lucíola Campestrini ◽  
Diego Eckhard ◽  
Alexandre Sanfelice Bazanella ◽  
Michel Gevers
Keyword(s):  
Prediction Error ◽  
Control Design ◽  
Data Driven ◽  
Error Identification ◽  
Model Reference ◽  
Model Reference Control
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