CONTROLADOR ACTIVO LINEAL APLICADO AL VEHÍCULO EN SOFTWARE SCILAB (LINEAR ACTIVE CONTROLLER APPLIED TO THE VEHICLE IN SCILAB SOFTWARE)

Resumen     En este artículo se muestra un problema clásico en la teoría de control, el cual es el diseño de una ley de retroalimentación, teniendo el propósito de que la salida de cualquier sistema siga asintóticamente una señal de referencia. En este trabajo, se pretende que la velocidad lateral siga a una maniobra del conductor o sensor del volante, pero en sentido contrario. Se propone que el vehículo se encuentra realizando pruebas de manejo conocidas por la norma internacional ISO 7401, por ende el problema de la teoría de regulación lineal vía retroalimentación de estados por medio de una función de Lyapunov es la solución idónea a nuestro problema ya que se supone la medición de la velocidad angular de viraje. Los actuadores que integraremos en este artículo serán los frenos () y el sistema frontal activo (AFS, por sus siglas en inglés), por medio de la simulación del software Scilab.Palabra(s) clave: Retroalimentación de estados, Scilab, velocidad lateral, velocidad angular de viraje. Abstract    This article shows a classic problem of control theory, which is the design of a feedback law, it has the purpose that the output of any system follows a reference signal asymptotically. In this paper we aim that the lateral velocity follows a drivers´s maneuver or steering wheel sensor, but in the opposite direction. It is proposed that the vehicle performs driving test knowed by the ISO 7401 international standard, thus, to solve this problem we are going to use the feedback-state lineal theory by means of a Lyapunov function, because it is supposed to measure the yaw velocity. The actuators that we will be integrating in this paper, will be the brakes () and Front Active System (AFS), through simulations in the software Scilab.Keywords: Feedback state, lateral velocity, Scilab, yaw velocity

PLATAFORMAS PARA CONTROLADOR ACTIVO LINEAL APLICADO A LA DIRECCIÓN ASISTIDA AUTOMOTRIZ (PLATFORMS FOR LINEAR ACTIVE CONTROLLER APPLIED TO THE AUTOMOTIVE ASSISTED STEERING)

En este artículo se muestra un problema clásico en la teoría de control, el cual es el diseño de una ley de retroalimentación, teniendo el propósito de que la salida de cualquier sistema siga asintóticamente una señal de referencia. En este trabajo, se pretende que la velocidad lateral siga a una maniobra del conductor, pero en sentido contrario. Se propone que el vehículo se encuentra realizando pruebas de manejo conocidas por norma internacional ISO 7401, por ende el problema de la teoría de regulación lineal vía retroalimentación de estados por medio de una función de Lyapunov es la solución idónea a nuestro problema ya que se supone la medición de la velocidad angular de viraje. Los actuadores que integraremos en este artículo serán los frenos () y el sistema frontal activo (AFS, por sus siglas en inglés), por medio de la simulación de Matlab-Simulink-CarSim y una plataforma propia.Palabra(s) clave: Retroalimentación de estados, velocidad lateral, velocidad angular de viraje, CarSim. AbstractThis article shows a classic problem of control theory, which is the design of a feedback law, it has the purpose that the output of any system follows a reference signal asymptotically. In this paper we aim that the lateral velocity follows a drivers´s maneuver, but in the opposite direction. It is proposed that the vehicle performs driving test knowed by the ISO 7401 international standard, thus, to solve this problem we are going to use the feedback-state lineal theory by means of a Lyapunov function, because it is supposed to measure the yaw velocity. The actuators that we will be integrating in this paper, will be the brakes () and Front Active System (AFS), through simulations in Matlab- Simulink-CarSim and own platform.Keywords: Feedback state, lateral velocity, yaw velocity, CarSim

Steering Angle Control of Rack Steering Vehicle using Antiwindup-PI-Control

The precision of the steering in a vehicle is one of the issues that need to be tackled for safety and energy efficiencies, especially in the motion at the cornering or turning. The issue is crucial especially for vehicles with a non-holonomic system such as rack steering vehicles, as it is more prone towards high collisions to the peer walls or off-road incidents due to the inertia factor. Therefore, this has taken the initiative to propose a steering precision control strategy using the proportional and integral (PI) control that considers the Rack Steering Vehicle (RSV) dynamics and its friction as well as aerodynamics disturbances. The control objective is emphasized on steering input precision in which steering feedback response is derived from the vehicle dynamics with disturbances. The RSV model and the antiwindup-PI control are model and simulated in order to verify the proposed control strategy for the RSV system. The results show that with small fine tunes on the antiwindup-PI controller, the steering input is controlled precisely with a very minor steady-state error if compare to the single PI controller. Regarding vehicle axial velocities, both horizontal (X-axis) and vertical (Y-axis) velocities are controllable without radical fluctuated as well as oscillation speed if compare to the RSV with PI controller

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme

On the experimental analysis of single input single output control of yaw rate and sideslip angle

Electric vehicles with individually controlled drivetrains allow torque-vectoring, which improves vehicle safety and drivability. This paper investigates a new approach to the concurrent control of yaw rate and sideslip angle. The proposed controller is a simple single input single output (SISO) yaw rate controller, in which the reference yaw rate depends on the vehicle handling requirements, and the actual sideslip angle. The sideslip contribution enhances safety, as it provides a corrective action in critical situations, e.g., in case of oversteer during extreme cornering on a low friction surface. The proposed controller is experimentally assessed on an electric vehicle demonstrator, along two maneuvers with quickly variable tire-road friction coefficient. Different longitudinal locations of the sideslip angle used as control variable are compared during the experiments. Results show that: i) the proposed SISO approach provides significant improvements with respect to the vehicle without torque-vectoring, and the controlled vehicle with a reference yaw rate solely based on the handling requirements for high-friction maneuvering; and ii) the control of the rear axle sideslip angle provides better performance than the control of the sideslip angle at the centre of gravity

Real-time lateral stability and steering characteristic control using non-linear model predictive control

This paper presents a non-linear integrated control strategy that primarily focuses maintaining vehicle lateral stability using active front steering and differential braking. The proposed control strategy utilises a non-linear model predictive controller to improve lateral stability. A stable linear reference model is used for reference generation. By including the understeer gradient in the reference model, different kinematic responses are obtained from the controlled vehicle. The prediction model utilises the road friction estimate to create dynamic stability constraints that include rollover and sliding of the vehicle. The design of the model predictive controller allows easy activation of different control actuators and dynamic modification to the control behaviour. The control methodology is validated using MATLAB/Simulink and a validated MSC ADAMS model. A sensitivity analysis is conducted to identify the susceptibility of the control strategy to various parameters and states.https://www.tandfonline.com/loi/nvsd20hj2023Mechanical and Aeronautical Engineerin

Hybrid model predictive control of damping multi-mode switching damper for vehicle suspensions

This paper investigates the design and verification of a hybrid model predictive controller of a damping multi-mode switching damper for application in vehicle suspensions. Since the damping mode switches induce different modes of operation, the vehicle suspension system including this damper poses challenging hybrid control problem. To solve this problem, a novel approach to the modelling and controller design problem is proposed based on hybrid modelling and model predictive control techniques. The vehicle suspension system with the damping multi-mode switching damper is formulated as a mixed logical dynamical model comprising continuous and discrete system inputs. Based on this model, a constrained optimal control problem is solved to manage the switching sequences of the damping mode with respect to the suspension performance requirements. Numerical simulation results demonstrate the effectiveness of the proposed control methodology finally