Following another vehicle can be automated by controlling the inter-vehicle distance using cooperative adaptive cruise control systems (CACC). On the one hand, this distance should be as small as possible in order to ...
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Following another vehicle can be automated by controlling the inter-vehicle distance using cooperative adaptive cruise control systems (CACC). On the one hand, this distance should be as small as possible in order to reduce aerodynamic drag which decreases fuel consumption. On the other hand, a minimal spacing can increase the probability and severity of collisions. In order to ensure a satisfying performance in the presence of various information topologies and relevant uncertainties such as errors in data transmission or extreme maneuvers of the lead vehicle, a stochastic optimization approach is suggested and demonstrated for a preexisting CACC scheme. Simulation experiments show the performance and the potential energy savings achieved by the robust calibration of the controller.
This paper presents a successful implementation of a model predictive controller (MPC) in an continuous annealing furnace, based on a compact process model with few physical parameters. The complete furnace structure,...
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ISBN:
(纸本)9780889868724
This paper presents a successful implementation of a model predictive controller (MPC) in an continuous annealing furnace, based on a compact process model with few physical parameters. The complete furnace structure, including the conveyed strip, the heater elements, and the thermal effects of the cladding, is therefore described by a discrete state space model of low order. To ensure stability of the discretized process model a physically motivated sufficient stability criterion is presented. For state estimation, an efficient Kalman filter algorithm is introduced. A model based predictive controller, which also respect considers process constraints, is customized to the special application of the continuous annealing furnace. Experimental results demonstrate the effective industrial implementation and the potential of constrained model based predictive control.
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