Linear quadratic game and non-cooperative predictive methods for potential application to modelling driver-AFS interactive steering control

This paper is concerned with the modelling of strategic interactions between the human driver and the vehicle active front steering (AFS) controller in a path-following task where the two controllers hold different target paths. The work is aimed at extending the use of mathematical models in representing driver steering behaviour in complicated driving situations. Two game theoretic approaches, namely linear quadratic game and non-cooperative model predictive control (non-cooperative MPC), are used for developing the driver-AFS interactive steering control model. For each approach, the open-loop Nash steering control solution is derived; the influences of the path-following weights, preview and control horizons, driver time delay and arm neuromuscular system (NMS) dynamics are investigated, and the CPU time consumed is recorded. It is found that the two approaches give identical time histories as well as control gains, while the non-cooperative MPC method uses much less CPU time. Specifically, it is observed that the introduction of weight on the integral of vehicle lateral displacement error helps to eliminate the steady-state path-following error; the increase in preview horizon and NMS natural frequency and the decline in time delay and NMS damping ratio improve the path-following accuracy. © 2013 Copyright Taylor and Francis Group, LLC.

Model-based influences on humans' choices and striatal prediction errors.

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making.

Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans.

Theories of instrumental learning are centred on understanding how success and failure are used to improve future decisions. These theories highlight a central role for reward prediction errors in updating the values associated with available actions. In animals, substantial evidence indicates that the neurotransmitter dopamine might have a key function in this type of learning, through its ability to modulate cortico-striatal synaptic efficacy. However, no direct evidence links dopamine, striatal activity and behavioural choice in humans. Here we show that, during instrumental learning, the magnitude of reward prediction error expressed in the striatum is modulated by the administration of drugs enhancing (3,4-dihydroxy-L-phenylalanine; L-DOPA) or reducing (haloperidol) dopaminergic function. Accordingly, subjects treated with L-DOPA have a greater propensity to choose the most rewarding action relative to subjects treated with haloperidol. Furthermore, incorporating the magnitude of the prediction errors into a standard action-value learning algorithm accurately reproduced subjects' behavioural choices under the different drug conditions. We conclude that dopamine-dependent modulation of striatal activity can account for how the human brain uses reward prediction errors to improve future decisions.

Static and dynamic errors in particle tracking microrheology.

Particle tracking techniques are often used to assess the local mechanical properties of cells and biological fluids. The extracted trajectories are exploited to compute the mean-squared displacement that characterizes the dynamics of the probe particles. Limited spatial resolution and statistical uncertainty are the limiting factors that alter the accuracy of the mean-squared displacement estimation. We precisely quantified the effect of localization errors in the determination of the mean-squared displacement by separating the sources of these errors into two separate contributions. A "static error" arises in the position measurements of immobilized particles. A "dynamic error" comes from the particle motion during the finite exposure time that is required for visualization. We calculated the propagation of these errors on the mean-squared displacement. We examined the impact of our error analysis on theoretical model fluids used in biorheology. These theoretical predictions were verified for purely viscous fluids using simulations and a multiple-particle tracking technique performed with video microscopy. We showed that the static contribution can be confidently corrected in dynamics studies by using static experiments performed at a similar noise-to-signal ratio. This groundwork allowed us to achieve higher resolution in the mean-squared displacement, and thus to increase the accuracy of microrheology studies.

A discretized proportional base driver for Silicon Carbide Bipolar Junction Transistors

Silicon Carbide Bipolar Junction Transistors require a continuous base current in the on-state. This base current is usually made constant and is corresponding to the maximum collector current and maximum junction temperature that is foreseen in a certain application. In this paper, a discretized proportional base driver is proposed which will reduce, for the right application, the steady-state power consumption of the base driver. The operation of the proposed base driver has been verified experimentally, driving a 1200V/40A SiC BJT in a DC-DC boost converter. In order to determine the potential reduction of the power consumption of the base driver, a case with a dc-dc converter in an ideal electric vehicle driving the new European drive cycle has been investigated. It is found that the steady-state power consumption of the base driver can be reduced by approximately 63 %. The total reduction of the driver consumption is 2816 J during the drive cycle, which is slightly more than the total on-state losses for the SiC BJTs used in the converter. © 2013 IEEE.

Switch mode constant current LED Driver with high efficiency, high precision and wide dimming ratio

A high efficiency hard switching constant current LED driver is presented with high overall efficiency, high current precision, high LED efficacy, flicker-free and wide constant current dimming ratio. The high stable lighting source provides the best solution for office light, reading light and LCD backlight. © 2013 IEEE.

A discretized proportional base driver for silicon carbide bipolar junction transistors

Silicon carbide (SiC) bipolar junction transistors (BJTs) require a continuous base current in the on-state. This base current is usually made constant and is corresponding to the maximum collector current and maximum junction temperature that is foreseen in a certain application. In this paper, a discretized proportional base driver is proposed which will reduce, for the right application, the steady-state power consumption of the base driver. The operation of the proposed base driver has been verified experimentally, driving a 1200-V/40-A SiC BJT in a dc-dc boost converter. In order to determine the potential reduction of the power consumption of the base driver, a case with a dc-dc converter in an ideal electric vehicle driving the new European drive cycle has been investigated. It is found that the steady-state power consumption of the base driver can be reduced by approximately 60%. The total reduction of the driver consumption is 3459 J during the drive cycle, which is slightly more than the total on-state losses for the SiC BJTs used in the converter. © 2013 IEEE.