Efficient minimum manoeuvre time optimisation of an oversteering vehicle at constant forward speed

A receding horizon steering controller is presented, capable of pushing an oversteering nonlinear vehicle model to its handling limit while travelling at constant forward speed. The controller is able to optimise the vehicle path, using a computationally efficient and robust technique, so that the vehicle progression along a track is maximised as a function of time. The resultant method forms part of the solution to the motor racing objective of minimising lap time. © 2011 AACC American Automatic Control Council.

Minimum dissolved oxygen tolerance of four different sizes of milkfish

Four size groups of milkfish were tested, 4-18 g, 20-34 g, 35-95 g and 200-300 g. A number of fish from each group were placed separately in identical 1.2 m2 wooden tanks containing seawater filled up to 30 cm depth. The aggregate weight of fish per size group was approximately 1 kg. The fish were held for 72 h, fed with lab-lab and provided with continuous aeration to allow recovery from stress during transport and handling. After the recovery period, aeration was stopped and 200 g of the fine rice bran was spread over the water in each tank creating a film of bran particles on the water surface. This was designed to speed up depletion of dissolved oxygen considering the combined effects of the screening-off of sunlight, the reduction of air-water interface and the breakdown of the bran particles. It is probable that stress on milkfish in brackishwater ponds could start when oxygen level drops to about 1.4 ppm. A further decrease to 0.04 ppm could produce a total kill of all specimens above 4 grams with marketable size and bigger size fish dying first.

Minimum sensor duty cycle with guaranteed estimator performance

In this paper, we consider Kalman filtering over a network and construct the optimal sensor data scheduling schemes which minimize the sensor duty cycle and guarantee a bounded error or a bounded average error at the remote estimator. Depending on the computation capability of the sensor, we can either give a closed-form expression of the minimum sensor duty cycle or provide tight lower and upper bounds of it. Examples are provided throughout the paper to demonstrate the results. © 2012 IEEE.

Decentralised minimum-time consensus

We consider the discrete-time dynamics of a network of agents that exchange information according to a nearest-neighbour protocol under which all agents are guaranteed to reach consensus asymptotically. We present a fully decentralised algorithm that allows any agent to compute the final consensus value of the whole network in finite time using the minimum number of successive values of its own state history. We show that the minimum number of steps is related to a Jordan block decomposition of the network dynamics, and present an algorithm to compute the final consensus value in the minimum number of steps by checking a rank condition of a Hankel matrix of local observations. Furthermore, we prove that the minimum number of steps is related to graph theoretical notions that can be directly computed from the Laplacian matrix of the graph and from the minimum external equitable partition. © 2013 Elsevier Ltd. All rights reserved.

Minimum maneuver time calculation using convex optimization

The problem of calculating the minimum lap or maneuver time of a nonlinear vehicle, which is linearized at each time step, is formulated as a convex optimization problem. The formulation provides an alternative to previously used quasi-steady-state analysis or nonlinear optimization. Key steps are: the use of model predictive control; expressing the minimum time problem as one of maximizing distance traveled along the track centerline; and linearizing the track and vehicle trajectories by expressing them as small displacements from a fixed reference. A consequence of linearizing the vehicle dynamics is that nonoptimal steering control action can be generated, but attention to the constraints and the cost function minimizes the effect. Optimal control actions and vehicle responses for a 90 deg bend are presented and compared to the nonconvex nonlinear programming solution. Copyright © 2013 by ASME.

Identification of Prorocentrum minimum and Takayama pulchella by fluorescence in situ hybridization through epifluorescence microscopy and flow cytometry

Partial rDNA sequences of Prorocentrum minimum and Takayama pulchella were amplified, cloned and sequenced. and these sequence data were deposited in the GenBank. Eight oligonucleotide probes (DNA probes) were designed based on the sequence analysis. The probes were employed to detect and identify P. minimum and T. pulchella in unialgal and mixed algal samples with a fluorescence in situ hybridization method using flow cytometry. Epifluorescence micrographs showed that these specific probes labeled with fluorescein isothiocyanate entered the algal cells and bound to target sequences, and the fluorescence signal resulting from whole-cell hybridization varied from probe to probe. These DNA probes and the hybridization protocol we developed were specific and effective for P. minimum and T. pulchella, without any specific binding to other algal species. The hybridization efficiency of different probes specific to P. minimum was in the order: PM18S02 > PM28S02 > PM28S01 > PM18S01, and that of the probes specific to T. pulchella was TP18S02 > TP28S01 > TP28S02 > TP18S01. The different hybridization efficiency of the DNA probes could also be shown in the fluorescent signals between the labeled and unlabeled cells demonstrated using flow cytometry. The DNA probes PM18S02, PM28S02; TP18S02 and TP28S01, and the protocol, were also useful for the detection of algae in natural samples.

Dense active appearance models using a bounded diameter minimum spanning tree

We present a method for producing dense Active Appearance Models (AAMs), suitable for video-realistic synthesis. To this end we estimate a joint alignment of all training images using a set of pairwise registrations and ensure that these pairwise registrations are only calculated between similar images. This is achieved by defining a graph on the image set whose edge weights correspond to registration errors and computing a bounded diameter minimum spanning tree (BDMST). Dense optical flow is used to compute pairwise registration and we introduce a flow refinement method to align small scale texture. Once registration between training images has been established we propose a method to add vertices to the AAM in a way that minimises error between the observed flow fields and a flow field interpolated between the AAM mesh points. We demonstrate a significant improvement in model compactness using the proposed method and show it dealing with cases that are problematic for current state-of-the-art approaches.