Advanced control based on Recurrent Neural Networks learned using Virtual Reference Feedback Tuning and application to an Electronic Throttle Body (with supplementary material)

In this paper the application of Virtual Reference Feedback Tuning (VRFT) for control of nonlinear systems with regulators defined by Echo State Networks (ESN) and Long Short Term Memory (LSTM) networks is investigated. The capability of this class of regulators of constraining the control variable is pointed out and an advanced control scheme that allows to achieve zero steady-state error is presented. The developed algorithms are validated on a benchmark example that consists of an electronic throttle body (ETB)

An Add-on Model Predictive Control Strategy for the Energy Management of Hybrid Electric Tractors

The hybridization process has recently touched also the world of agricultural vehicles. Within this context, we develop an Energy Management Strategy (EMS) aiming at optimizing fuel consumption, while maintaining the battery state of charge. A typical feature of agricultural machines is that their internal combustion engine is speed controlled, tracking the reference requested by the driver. In view of avoiding any modification on this original control loop, an add-on EMS strategy is proposed. In particular, we employ a multi-objective Model Predictive Control (MPC), taking into account the fuel consumption minimization and the speed tracking requirement, including the engine speed controller in the predictive model. The proposed MPC is tested in an experimentally-validated simulation environment, representative of an orchard vineyard tractor.Comment: Submitted to IEEE Transactions on Vehicular Technolog

Engine knock margin control using in-cylinder pressure data: preliminary results

Knock is an undesired phenomenon occurring in spark ignited engines and is controlled acting on the spark timing. This paper presents a closed-loop architecture that makes possible to address the knock control problem with a standard model-based design approach. An engine knock margin estimate is feedback controlled through a PI regulator and its target value is computed starting from the desired knock probability. A black-box modelling approach is used to identify the dynamics between the spark timing and the knock margin and a traditional model-based controller synthesis is performed. Experimental results at the test bench show that, compared to a conventional strategy, the proposed approach allows for a better compromise between the controller speed and the variability of the spark timing. Moreover, another advantage w.r.t. the conventional strategies is that closed-loop performance prove to be constant for different reference probabilities, leading to a more regular engine behaviour

Longitudinal Velocity Estimation in Single-Track Vehicles

Vehicle dynamics control systems are becoming available for single-track vehicles. The dynamics of single-track vehicles have some unique features that require ad hoc solutions. One of the most critical aspects is the estimation of the vehicle body velocity. In this paper the problem of estimating the body velocity of a two wheeled vehicle for traction control applications is discussed. The front wheel velocity and the longitudinal acceleration measurements are used to estimate the vehicle velocity according to a sensor fusion philosophy. The complementary filter approach is compared against a more advanced Kalman filter. It is shown that the mentioned Kalman filter can be written as a second order complementary filter; this allows to derive quantitative guidelines for the tuning of the filter. The proposed methods are shown to be more robust to wheelies than the front wheel velocity based estimate. Experimental tests on an instrumented bike validate the methods for traction control applications

Wheelie detection for single-track vehicles

Single-track vehicles electronic control systems have been experiencing an important growth in the last years. Despite some similarities with four-wheeled vehicles the dynamics of two-wheeled vehicles have some unique features that require ad hoc solutions. One of those is the lift of the front wheel from the ground during severe accelerations, usually known as wheelie. This phenomenon is particularly important since, if not controlled, can lead to vehicle instabilities. Moreover, it has a significant impact on the vehicle longitudinal speed estimation, essential for the development of wheel slip-based traction control systems, so widely spreading. In this paper the problem of detecting a wheelie occurrence is discussed. Two algorithms, that employ only standard vehicle equipment sensors, are presented. Their parameter tuning procedure is described and experimental data are used to show their effectiveness, as well as for a performances comparison

Single-Track Vehicle Dynamics Control: State of the Art and Perspective

The reduction of hardware costs and the availability of smaller, lighter electromechanical actuators have led to the development of numerous control systems for powered two wheelers (PTW). Although the community working on PTW dynamics control is smaller than the community addressing automotive control, a considerable number of contributions are available. This paper presents a review on the control of PTW, and anticipates future research and industrial trends. This paper proposes a reasoned classification of different approaches based on the controlled vehicle dynamics, separating between control systems dealing with the in-plane and out-of-plane dynamics and then presents an analysis of the state-of-the-art of each control problem. A section is then devoted to the control of narrow track tilting vehicles that share many features with PTW

Design of a lane change driver assistance system, with implementation and testing on motorbike

This paper addresses the problem of the development, implementation and testing of a Lane Change Decision Aid System on a motorcycle, by using a short range radar sensor and a set of LEDs to interface with the driver. First, a feasibility analysis for such application is performed, then the algorithm is described, and finally the results of on-road tests are presented to illustrate and validate the method. The algorithm is composed by a first block for stabilizing the detected objects through a finite state machine and filtering the data coming from the sensor by implementing a Kalman filter that reduces the sensors inaccuracies. A decision block sets the state of the system by checking the position and speed of the detected objects, and finally an HMI block computes the Hazard Level considering position and Time-To-Collision of the detected objects and delivers a warning to the driver

Iterative tuning of engine speed controller for launch control applications in sport motorcycles

In this work, engine rotational speed controller tuning issue is analyzed. To cope with actuation limitations, controller tuning is addressed in an iterative framework by means of the Iterative Feedback Tuning method. Subsequent iterations are needed to gain information on the controlled system and to meet closed-loop performance defined by means of a reference model. Finally, tuning results are discussed and closed-loop performance are analyzed