@inbook {PLPB02,
	title = {Optimal control of quantized input systems},
	booktitle = {Hybrid Systems: Computation and Control},
	series = {Lecture Notes in Computer Science},
	volume = {LNCS 2289},
	year = {2002},
	pages = {351-363},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	address = {Heidelberg, Germany},
	abstract = {<p>In this paper we consider the problem of optimal control (specifically, minimum-time steering) for systems with quantized inputs. In particular, we propose a new approach to the solution of the optimal control problem for an important class of nonlinear systems, i.e. chained-form systems. By exploiting results on the structure of the reachability set of these systems under quantized control, the optimal solution is determined solving an integer linear programming problem. Our algorithm represents an improvement with respect to classical approaches in terms of exactness, as it does not resort to any a priori state-space discretization. Although the computational complexity of the problem in our formulation is still formally exponential, it lends itself to application of Branch and Bound techniques, which substantially cuts down computations in many cases, as it has been experimentally observed.</p>
},
	keywords = {Embedded Control, Robotics},
	author = {S. Pancanti and L. Leonardi and L. Pallottino and A. Bicchi},
	editor = {C. Tomlin and M. Greenstreet}
}
@conference {PPB02,
	title = {On Optimal Steering of Quantized Input Systems},
	booktitle = {Proceedings of the NSF/ONR Workshop on Future Directions in Nonlinear Control of Mechanical Systems},
	year = {2002},
	address = {Urbana, IL.},
	abstract = {<p>In this paper we consider the problem of optimal control (specifically, minimum-time steering) for systems with quantized inputs. In particular, we propose a new approach to the solution of the optimal control problem for an important class of nonlinear systems, i.e. chained-form systems. By exploiting results on the structure of the reachability set of these systems under quantized control, the optimal solution is determined solving an integer linear programming problem. Our algorithm represents an improvement with respect to classical approaches in terms of exactness, as it does not resort to any a priori state-space discretization. Although the computational complexity of the problem in our formulation is still formally exponential, it lends itself to application of Branch and Bound techniques, which substantially cuts down computations in many cases, as it has been experimentally observed.</p>
},
	keywords = {Embedded Control, Robotics},
	author = {S. Pancanti and L. Pallottino and A. Bicchi}
}
