Vehicle trajectory linearisation to enable efficient optimisation of the constant speed racing line

A driver model is presented capable of optimising the trajectory of a simple dynamic nonlinear vehicle, at constant forward speed, so that progression along a predefined track is maximised as a function of time. In doing so, the model is able to continually operate a vehicle at its lateral-handling limit, maximising vehicle performance. The technique used forms a part of the solution to the motor racing objective of minimising lap time. A new approach of formulating the minimum lap time problem is motivated by the need for a more computationally efficient and robust tool-set for understanding on-the-limit driving behaviour. This has been achieved through set point-dependent linearisation of the vehicle model and coupling the vehicle-track system using an intrinsic coordinate description. Through this, the geometric vehicle trajectory had been linearised relative to the track reference, leading to new path optimisation algorithm which can be formed as a computationally efficient convex quadratic programming problem. © 2012 Copyright Taylor and Francis Group, LLC.

Predictive control of a Boeing 747 aircraft using an FPGA

New embedded predictive control applications call for more eficient ways of solving quadratic programs (QPs) in order to meet demanding real-time, power and cost requirements. A single precision QP-on-a-chip controller is proposed, implemented in afield-programmable gate array (FPGA) with an iterative linear solver at its core. A novel offline scaling procedure is introduced to aid the convergence of the reduced precision solver. The feasibility of the proposed approach is demonstrated with a real-time hardware-in-the-loop (HIL) experimental setup where an ML605 FPGA board controls a nonlinear model of a Boeing 747 aircraft running on a desktop PC through an Ethernet link. Simulations show that the quality of the closed-loop control and accuracy of individual solutions is competitive with a conventional double precision controller solving linear systems using a Riccati recursion. © 2012 IFAC.

Kernelized sorting

Object matching is a fundamental operation in data analysis. It typically requires the definition of a similarity measure between the classes of objects to be matched. Instead, we develop an approach which is able to perform matching by requiring a similarity measure only within each of the classes. This is achieved by maximizing the dependency between matched pairs of observations by means of the Hilbert Schmidt Independence Criterion. This problem can be cast as one of maximizing a quadratic assignment problem with special structure and we present a simple algorithm for finding a locally optimal solution.

Low-rank optimization on the cone of positive semidefinite matrices

We propose an algorithm for solving optimization problems defined on a subset of the cone of symmetric positive semidefinite matrices. This algorithm relies on the factorization X = Y Y T , where the number of columns of Y fixes an upper bound on the rank of the positive semidefinite matrix X. It is thus very effective for solving problems that have a low-rank solution. The factorization X = Y Y T leads to a reformulation of the original problem as an optimization on a particular quotient manifold. The present paper discusses the geometry of that manifold and derives a second-order optimization method with guaranteed quadratic convergence. It furthermore provides some conditions on the rank of the factorization to ensure equivalence with the original problem. In contrast to existing methods, the proposed algorithm converges monotonically to the sought solution. Its numerical efficiency is evaluated on two applications: the maximal cut of a graph and the problem of sparse principal component analysis. © 2010 Society for Industrial and Applied Mathematics.

Predictive control using an FPGA with application to aircraft control

Alternative and more efficient computational methods can extend the applicability of model predictive control (MPC) to systems with tight real-time requirements. This paper presents a system-on-a-chip MPC system, implemented on a field-programmable gate array (FPGA), consisting of a sparse structure-exploiting primal dual interior point (PDIP) quadratic program (QP) solver for MPC reference tracking and a fast gradient QP solver for steady-state target calculation. A parallel reduced precision iterative solver is used to accelerate the solution of the set of linear equations forming the computational bottleneck of the PDIP algorithm. A numerical study of the effect of reducing the number of iterations highlights the effectiveness of the approach. The system is demonstrated with an FPGA-in-the-loop testbench controlling a nonlinear simulation of a large airliner. This paper considers many more manipulated inputs than any previous FPGA-based MPC implementation to date, yet the implementation comfortably fits into a midrange FPGA, and the controller compares well in terms of solution quality and latency to state-of-the-art QP solvers running on a standard PC. © 1993-2012 IEEE.

Model based control for closed loop testing of 1-D engine simulation models

1-D engine simulation models are widely used for the analysis and verification of air-path design concepts and prediction of the resulting engine transient response. The latter often requires closed loop control over the model to ensure operation within physical limits and tracking of reference signals. For this purpose, a particular implementation of Model Predictive Control (MPC) based on a corresponding Mean Value Engine Model (MVEM) is reported here. The MVEM is linearised on-line at each operating point to allow for the formulation of quadratic programming (QP) problems, which are solved as the part of the proposed MPC algorithm. The MPC output is used to control a 1-D engine model. The closed loop performance of such a system is benchmarked against the solution of a related optimal control problem (OCP). As an example this study is focused on the transient response of a light-duty car Diesel engine. For the cases examined the proposed controller implementation gives a more systematic procedure than other ad-hoc approaches that require considerable tuning effort. © 2012 IFAC.

Output feedback H2 model matching for decentralized systems with delays

This paper gives a new solution to the output feedback H2 model matching problem for a large class of delayed information sharing patterns. Existing methods for similar problems typically reduce the decentralized problem to a centralized problem of higher state dimension. In contrast, this paper demonstrates that the decentralized model matching solution can be constructed from the original centralized solution via quadratic programming. © 2013 AACC American Automatic Control Council.

On differentially dissipative dynamical systems

Dissipativity is an essential concept of systems theory. The paper provides an extension of dissipativity, named differential dissipativity, by lifting storage functions and supply rates to the tangent bundle. Differential dissipativity is connected to incremental stability in the same way as dissipativity is connected to stability. It leads to a natural formulation of differential passivity when restricting to quadratic supply rates. The paper also shows that the interconnection of differentially passive systems is differentially passive, and provides preliminary examples of differentially passive electrical systems. © IFAC.

Model-based control of thermoacoustic instabilities in partially premixed lean combustion - A design case study

Self-excited oscillation is becoming a major issue in low-emission, lean partially premixed combustion systems, and active control has been shown to be a feasible method to suppress such instabilities. A number of robust control methods are employed to obtain a feedback controller and it is observed that the robustness to system uncertainty is significantly better for a low complexity controller in spite of the norms being similar. Moreover, we demonstrate that closed-loop stability for such a complex system can be proved via use of the integral quadratic constraint method. Open- and closed-loop nonlinear simulations are provided. © 2013 Copyright Taylor and Francis Group, LLC.

Low-rank optimization with trace norm penalty

The paper addresses the problem of low-rank trace norm minimization. We propose an algorithm that alternates between fixed-rank optimization and rank-one updates. The fixed-rank optimization is characterized by an efficient factorization that makes the trace norm differentiable in the search space and the computation of duality gap numerically tractable. The search space is nonlinear but is equipped with a Riemannian structure that leads to efficient computations. We present a second-order trust-region algorithm with a guaranteed quadratic rate of convergence. Overall, the proposed optimization scheme converges superlinearly to the global solution while maintaining complexity that is linear in the number of rows and columns of the matrix. To compute a set of solutions efficiently for a grid of regularization parameters we propose a predictor-corrector approach that outperforms the naive warm-restart approach on the fixed-rank quotient manifold. The performance of the proposed algorithm is illustrated on problems of low-rank matrix completion and multivariate linear regression. © 2013 Society for Industrial and Applied Mathematics.

Efficient decoding with generative score-spaces using the expectation semiring

State-of-the-art speech recognisers are usually based on hidden Markov models (HMMs). They model a hidden symbol sequence with a Markov process, with the observations independent given that sequence. These assumptions yield efficient algorithms, but limit the power of the model. An alternative model that allows a wide range of features, including word- and phone-level features, is a log-linear model. To handle, for example, word-level variable-length features, the original feature vectors must be segmented into words. Thus, decoding must find the optimal combination of segmentation of the utterance into words and word sequence. Features must therefore be extracted for each possible segment of audio. For many types of features, this becomes slow. In this paper, long-span features are derived from the likelihoods of word HMMs. Derivatives of the log-likelihoods, which break the Markov assumption, are appended. Previously, decoding with this model took cubic time in the length of the sequence, and longer for higher-order derivatives. This paper shows how to decode in quadratic time. © 2013 IEEE.

Output disturbance rejection using parallel model predictive control

The solution time of the online optimization problems inherent to Model Predictive Control (MPC) can become a critical limitation when working in embedded systems. One proposed approach to reduce the solution time is to split the optimization problem into a number of reduced order problems, solve such reduced order problems in parallel and selecting the solution which minimises a global cost function. This approach is known as Parallel MPC. The potential capabilities of disturbance rejection are introduced using a simulation example. The algorithm is implemented in a linearised model of a Boeing 747-200 under nominal flight conditions and with an induced wind disturbance. Under significant output disturbances Parallel MPC provides a significant improvement in performance when compared to Multiplexed MPC (MMPC) and Linear Quadratic Synchronous MPC (SMPC). © 2013 IEEE.

Dietary phosphorus requirement of juvenile black seabream, Sparus macrocephalus

A growth trial was conducted to estimate the optimum requirement of dietary available phosphorus (P) for black seabream (Sparus macrocephalus) in indoor net cages (1.5x1.0x1.0 m). Triplicate groups of black seabream (11.45 +/- 0.02 g) were fed diets containing graded levels (0.18, 0.36, 0.54, 0.72, 0.89 and 1.07%) of available P to satiation for 8 weeks. The basal diet (diet 1), containing 0.18% available P, was supplemented with graded levels of monosodium phosphate (NaH2PO4 2H(2)O) to formulate five experimental diets. The fish were fed twice daily (08:00 h and 16:00 h) and reared in seawater (salinity, 26-29 g l(-1)) at a temperature of 28 +/- 1 degrees C. Dissolved oxygen during the experiment was above 5 mg l(-1). The specific growth rate (SGR), weight gain (WG), feed efficiency (FE) and protein efficiency ratio (PER) were all significantly improved by dietary phosphorus up to 0.54% (P<0.05) and then leveled off beyond this level. Hepatosomatic index (HSI) was inversely correlated with dietary phosphorus levels (P< 0.05). Efficiency of P utilization stabled in fish fed diets containing 0.18%-0.54% available P and then decreased dramatically with further supplementation of dietary phosphorus. Body composition analysis showed that the whole-body lipid, ash, calcium and phosphorus contents were all significantly affected by dietary available P concentration (P<0.05), however, no significance were found in whole-body calcium/phosphorus (Ca/P) ratios among all the treatments (P>0.05). Dietary phosphorus levels also affected the mineralization of vertebrae, skin and scale (P<0.05). Ca/P ratios in vertebrae and scale were not influenced by dietary P supplementation, while skin Ca/P ratio increased statistically with dietary available P levels (quadratic effect, P<0.001). The blood chemistry analysis showed that dietary available P had distinct effects on enzyme activities of alkaline phosphatase (ALP) and plasma lysozyme (LSZ), as well as contents of triacyglycerol (TG) and total cholesterol (T-CHO) (P<0.05). Broken-line analysis showed maximum weight gain (WG) was obtained at dietary available P concentrations of 0.55%. Quadratic analysis based on P contents in whole fish, vertebrae or scale indicated that the requirements were 0.81, 0.87 and 0.88%, respectively. Signs of phosphorus deficiency were characterized by poor growth, slightly reduced mineralization and an increase in body lipid content. (C) 2008 Published by Elsevier B.V.

Effect of dietary cyanobacteria on growth and accumulation of microcystins in Nile tilapia (Oreochromis niloticus)

A 12-week growth trial was conducted in a flow-through system to investigate the chronic toxic effect of dietary intake of cyanobacteria on growth, feed utilization and microcystins accumulation in Nile tilapia (Oreochromis niloticus L.) (initial body weight: 5.6 g). Six isonitrogenous and isocaloric diets were formulated to include different contents of cyanobacteria with the dietary microcystins increasing from 0 to 5460.06 ng/g diet. The results showed that dietary intake of cyanobacteria could increase the growth of tilapia while there are no impacts on feed conversion efficiency or mortality. Feeding rate was higher for the diets containing highest cyanobacteria. Microcystins were mostly accumulated in fish liver. The relationship between microcystins contents in muscle, liver, spleen and dietary intake could be described by quadratic equations. Microcystins content in the muscle of Nile tilapia in present study exceeded the upper limit of the tolerable daily intake (TDI) of microcystins suggested by the WHO (0.04 mu g/kg body weight/d). It is suggested that Nile tilapia fed on toxic cyanobacteria is not suitable for human food. (c) 2006 Elsevier B.V. All rights reserved.

The effect of an electric field on the nonlinear response of InAs/GaAs quantum dots

The refractive nonlinearities of InAs/GaAs quantum dots under a dc electric field at photon energies above its band gap energy have been studied using the reflection Z-scan technique. The effect of the dc electric field on the nonlinear response of InAs/GaAs quantum dots showed similar linear and quadratic electro-optic effects as in the linear response regime at low fields. This implies that the electro-optic effect in the nonlinear regime is analogous to the response in the linear regime for semiconductor quantum dots. Our experimental results show the potential for voltage tunability in InAs quantum dot-based nonlinear electro-optic devices.