Roberto Horowitz

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A macroscopic traffic flow model, called the switchingmode model (SMM), has been derived from the cell transmission model (CTM) and then applied to the estimation of traffic densities at unmonitored locations along a highway. The SMM is a hybrid system that switches among different sets of linear difference equations, or modes, depending on the mainline(More)
Two concepts are advocated for the task specification and control of mechanical manipulators: 1) coding tasks in terms of velocity fields; 2) designing controllers so that the manipulator when under feedback control, interacts in an energetically passive manner with its physical environment. Based on these two concepts, a new passive velocity field(More)
The onramp metering control problem is posed using a cell transmission-like model called the asymmetric cell transmission model (ACTM). The problem formulation captures both freeflow and congested conditions, and includes upper bounds on the metering rates and on the onramp queue lengths. It is shown that a near-global solution to the resulting nonlinear(More)
The paper characterizes the behavior of the cell transmissionmodel of a freeway, divided intoN sections or cells, each with one on-ramp and one off-ramp. The state of the dynamical system is theN-dimensional vector n of vehicle densities in theN sections. A feasible stationary demand pattern induces a unique equilibrium flow in each section. However, there(More)
In this paper, we use a cell transmission model based switching state-space model to estimate vehicle densities and congestion modes at unmeasured locations on a highway section. The mixture Kalman filter algorithm, which is based on sequential Monte Carlo method, is employed to approximately solve the difficult problem of inference on a switching(More)
In this paper, we present our latest results on developing and implementing a traffic congestion mode and vehicle density estimator for a segment of Interstate 210 in Southern California. Using a mixture Kalman filtering (MKF) algorithm on the switching-mode traffic model, the estimator is able to provide estimated vehicle densities at unmeasured locations,(More)
Learning control encompasses a class of control algorithms for programmable machines such as robots which attain, through an iterative process, the motor dexterity that enables the machine to execute complex tasks. In this paper we discuss the use of function identiication and adaptive control algorithms in learning controllers for robot manipulators. In(More)
This paper discusses the design and testing of two track-following controllers for dual-stage servo systems in hard disk drives. The ®rst controller is designed using the l-synthesis multivariable robust optimal controller design methodology. The second is designed using classical single-input-single-output (SISO) frequency shaping design techniques, based(More)