@conference {MSVBB-CDC08, title = {Hybrid system reduction}, booktitle = {Proc. IEEE Int. Conf. on Decision and Control}, year = {2008}, pages = {227 -232}, keywords = {Embedded Control, Robotics}, author = {E. Mazzi and A. Sangiovanni Vincentelli and A. Balluchi and A. Bicchi} } @conference {BBMSS-07, title = {Hybrid Multi-rate Control of the Common-Rail}, booktitle = {European Control Conference}, year = {2007}, pages = {54-61}, abstract = {

We present an industrial case study in automotive control of significant complexity: the new common-rail fuel- injection system for Diesel engines developed by Magneti Marelli Powertrain. In this system, an inlet metering valve, inserted before the High Pressure (HP) pump, regulates the fuel flow that supplies the common rail according to the engine operating point (e.g. engine speed and torque). The standard approach to controller design adopted in the automotive in- dustry is based on mean-value models of the plant. However, the fuel injection system exhibits complex discrete-continuous interactions, due to the slow time-varying frequency of the HP pump cycles and the fast sampling frequency of sensing and actuation. Hence, a hybrid approach to controller design is very promising. In this paper, we present the synthesis of a hybrid multi-rate controller for a Magneti Marelli Powertrain common-rail fuel- injection system for four-cylinder multi-jet engines. Controller design is based on a hybrid model of the injection system. The resulting hybrid controller performs significantly better then previous controllers developed in the company on the basis of mean-value models of the plant.

}, keywords = {Embedded Control, Robotics}, author = {A. Balluchi and A. Bicchi and E. Mazzi and A. Sangiovanni-Vincentelli and G. Serra} } @conference {BBMSS06, title = {Hybrid Modelling and Control of the Common Rail Injection System}, booktitle = {Hybrid Systems: Computation and Control}, series = {Lecture Notes in Computer Science}, volume = {3927 / 2006}, year = {2006}, pages = {79-92}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, abstract = {

We present an industrial case study in automotive control of significant complexity: the new common rail fuel injection system for Diesel engines, currently under production by Magneti Marelli Powertrain. In this system, a flow-rate valve, introduced before the High Pressure (HP) pump, regulates the fuel flow that supplies the common rail according to the engine operating point. The standard approach followed in automotive control is to use a mean-value model for the plant and to develop a controller based on this model. In this particular case, this approach does not provide a satisfactory solution as the discrete-continuous interactions in the fuel injection system, due to the slow time-varying frequency of the HP pump cycles and the fast sampling frequency of sensing and actuation, play a fundamental role. We present a design approach based on a hybrid model of the Magneti Marelli Powertrain common-rail fuel-injection system for four-cylinder multi-jet engines and a hybrid approach to the design of a rail pressure controller. The hybrid controller is compared with a classical mean-value based approach to automotive control design whereby the quality of the hybrid solution is demonstrated.

}, keywords = {Embedded Control, Robotics}, author = {A. Balluchi and A. Bicchi and E. Mazzi and A. Sangiovanni Vincentelli and G. Serra}, editor = {J. Hespanha and A. Tiwari} } @article {BSB04, title = {Path-Following with a Bounded-Curvature Vehicle: a Hybrid Control Approach}, journal = {International Journal of Control}, volume = {78}, number = {15}, year = {2005}, month = {October}, pages = {1228-1247}, abstract = {

In this paper, we consider the problem of stabilizing the kinematic model of a car to a path in the plane under rather general conditions. The path is subject to very mild restrictions, while the car model, although rather simplified, contains the most relevant limitations inherent in wheeled robots kinematics. Namely, the car can only move forward, its steering radius is lower bounded and a limited sensory information only provides a partial knowledge of some state parameters. In particular, we consider the case that the current distance and the heading angle error with respect to the closest point on the reference path can be measured but only the sign of the path curvature is detected. These constraints are such to make classical control techniques inefficient. As the feedback information is both continuous and discrete, the hybrid systems formalism turns out to be well appropriate to model the problem. The proposed approach is based on optimal control techniques successfully applied in a previous work for following rectilinear path. We propose here an extension to the tracking of more general paths with moderate curvature. The stability of the closed-loop system is proved by means of the hybrid system formalism and hybrid formal verification techniques. Finally, the practicality of the proposed approach, in spite of non{\textendash}idealities in real-world applications, is discussed by reporting experimental results.

}, keywords = {Embedded Control, Robotics}, author = {A. Balluchi and A. Bicchi and P. Sou{\`e}res} } @conference {ABBPSZ05, title = {Randomized Algorithms for Platform{\textendash}based Design}, booktitle = {Proc. IEEE Int. Conf. on Decision and Control}, year = {2005}, pages = {6638 - 6643}, abstract = {

The design of automotive control systems is becoming increasingly complex as the level of performance required by car manufactures grows continuously and the constraints on cost and development time imposed by the market become tighter. A successful design, without costly and time consuming re-design cycles, can be achieved only by using an efficient design methodology that allows for component re-use and evaluation of platform requirements at the early stages of the design flow. In this paper, we illustrate a control-implementation design methodology for the development of embedded controllers by composition of algorithms picked up from libraries. Randomized algorithms and hybrid system theory are used to develop techniques for functional and architecture evaluations, which are implemented in a prototype tool.

}, keywords = {Embedded Control, Robotics}, author = {A. Agostini and A. Balluchi and A. Bicchi and B. Piccoli and Sangiovanni Vincentelli, A. and K. Zadarnowska} } @article {BB02, title = {Necessary and Sufficient Conditions for Robust Perfect Tracking under Variable Structure Control}, journal = {International Journal of Robust and Nonlinear Control}, volume = {13}, number = {2}, year = {2003}, month = {02/2003}, pages = {141-151}, abstract = {

The tracking control of linear MIMO systems with structured uncertainty is considered. A necessary and sufficient condition for robust asymptotic tracking employing variable structure techniques in the presence of multiplicative uncertainty is derived. The constructive proof of the theorem provides an explicit formula for controller synthesis.

}, keywords = {Embedded Control, Robotics}, author = {A. Balluchi and A. Bicchi} } @conference {ZBSVB03, title = {Stabilization of a class of discrete-time hybrid automata}, booktitle = {Proc. IEEE Int. Conf. on Decision and Control}, year = {2003}, pages = {1147-1152}, abstract = {

In this paper, the problem of stabilizing linear discrete time hybrid automata is considered. A synthesis methodology is obtained by extending to hybrid systems the stabilization techniques based on stable convex combinations, originally developed for switching systems. An algorithm to explore the candidate stabilizing controller actions is proposed and an application to an automotive engine control problem is described.

}, keywords = {Embedded Control, Robotics}, author = {M. Zoncu and A. Balluchi and A. Sangiovanni Vincentelli and A. Bicchi} } @conference {SBB00, title = {Optimal Feedback Control for Route Tracking with a Bounded-Curvature Vehicle}, booktitle = {Proc. IEEE Int. Conf. on Robotics and Automation}, year = {2000}, month = {April}, pages = {2473-2478}, address = {San Francisco, CA, USA}, keywords = {Robotics}, author = {P. Sou{\`e}res and A. Balluchi and A. Bicchi} }