A backward particle interpretation of Feynman-Kac formulae

We design a particle interpretation of Feynman-Kac measures on path spaces based on a backward Markovian representation combined with a traditional mean field particle interpretation of the flow of their final time marginals. In contrast to traditional genealogical tree based models, these new particle algorithms can be used to compute normalized additive functionals "on-the-fly" as well as their limiting occupation measures with a given precision degree that does not depend on the final time horizon. We provide uniform convergence results with respect to the time horizon parameter as well as functional central limit theorems and exponential concentration estimates. Our results have important consequences for online parameter estimation for non-linear non-Gaussian state-space models. We show how the forward filtering backward smoothing estimates of additive functionals can be computed using a forward only recursion.

Surface excavation with model predictive control

This paper describes the application of variable-horizon model predictive control to trajectory generation in surface excavation. A nonlinear dynamic model of a surface mining machine digging in oil sand is developed as a test platform. This model is then stabilised with an inner-loop controller before being linearised to generate a prediction model. The linear model is used to design a predictive controller for trajectory generation. A variable horizon formulation is augmented with extra terms in the cost function to allow more control over digging, whilst still preserving the guarantee of finite-time completion. Simulations show the generation of realistic trajectories, motivating new applications of variable horizon MPC for autonomy that go beyond the realm of vehicle path planning. ©2010 IEEE.

Modelling of long-term ground response to tunnelling under St James's Park, London

Following a tunnel excavation in low-permeability soil, it is commonly observed that the ground surface continues to settle and ground loading on the tunnel lining changes, as the pore pressures in the ground approach a new equilibrium condition. The monitored ground response following the tunnelling under St James's Park, London, shows that the mechanism of subsurface deformation is composed of three different zones: swelling, consolidation and rigid body movement. The swelling took place in a confined zone above the tunnel crown, extending vertically to approximately 5 m above it. On the sides of the tunnel, the consolidation of the soil occurred in the zone primarily within the tunnel horizon, from the shoulder to just beneath the invert, and extending laterally to a large offset from the tunnel centreline. Above these swelling and consolidation zones the soil moved downward as a rigid body. In this study, soil-fluid coupled three-dimensional finite element analyses were performed to simulate the mechanism of long-term ground response monitored at St James's Park. An advanced critical state soil model, which can simulate the behaviour of London Clay in both drained and undrained conditions, was adopted for the analyses. The analysis results are discussed and compared with the field monitoring data. It is found that the observed mechanism of long-term subsurface ground and tunnel lining response at St James's Park can be simulated accurately only when stiffness anisotropy, the variation of permeability between different units within the London Clay and non-uniform drainage conditions for the tunnel lining are considered. This has important implications for future prediction of the long-term behaviour of tunnels in clays.

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.

Hybrid model predictive control applied to switching control of burner load for a compact marine boi

This paper discusses the application of hybrid model predictive control to control switching between different burner modes in a novel compact marine boiler design. A further purpose of the present work is to point out problems with finite horizon model predictive control applied to systems for which the optimal solution is a limit cycle. Regarding the marine boiler control the aim is to find an optimal control strategy which minimizes a trade-off between deviations in boiler pressure and water level from their respective setpoints while limiting burner switches.The approach taken is based on the Mixed Logic Dynamical framework. The whole boiler systems is modelled in this framework and a model predictive controller is designed. However to facilitate on-line implementation only a small part of the search tree in the mixed integer optimization is evaluated to find out whether a switch should occur or not. The strategy is verified on a simulation model of the compact marine boiler for control of low/high burner load switches. It is shown that even though performance is adequate for some disturbance levels it becomes deteriorated when the optimal solution is a limit cycle. Copyright © 2007 International Federation of Automatic Control All Rights Reserved.

Air quality and public health impacts of UK airports. Part I: Emissions

The potential adverse human health and climate impacts of emissions from UK airports have become a significant political issue, yet the emissions, air quality impacts and health impacts attributable to UK airports remain largely unstudied. We produce an inventory of UK airport emissions - including aircraft landing and takeoff (LTO) operations and airside support equipment - with uncertainties quantified. The airports studied account for more than 95% of UK air passengers in 2005. We estimate that in 2005, UK airports emitted 10.2 Gg [-23 to +29%] of NOx, 0.73 Gg [-29 to +32%] of SO2, 11.7 Gg [-42 to +77%] of CO, 1.8 Gg [-59 to +155%] of HC, 2.4 Tg [-13 to +12%] of CO2, and 0.31 Gg [-36 to +45%] of PM2.5. This translates to 2.5 Tg [-12 to +12%] CO2-eq using Global Warming Potentials for a 100-year time horizon. Uncertainty estimates were based on analysis of data from aircraft emissions measurement campaigns and analyses of aircraft operations.The First-Order Approximation (FOA3) - currently the standard approach used to estimate particulate matter emissions from aircraft - is compared to measurements and it is shown that there are discrepancies greater than an order of magnitude for 40% of cases for both organic carbon and black carbon emissions indices. Modified methods to approximate organic carbon emissions, arising from incomplete combustion and lubrication oil, and black carbon are proposed. These alterations lead to factor 8 and a 44% increase in the annual emissions estimates of black and organic carbon particulate matter, respectively, leading to a factor 3.4 increase in total PM2.5 emissions compared to the current FOA3 methodology. Our estimates of emissions are used in Part II to quantify the air quality and health impacts of UK airports, to assess mitigation options, and to estimate the impacts of a potential London airport expansion. © 2011 Elsevier Ltd.

Robust predictive control with feasible contingencies for fault tolerance

This paper introduces the notion of M-step robust fault tolerance for discrete-time systems where finite-time completion of a control manoeuvre is desired. It considers a scenario with two distinct objectives; a primary and secondary target are specified as sets to be reached in finite-time, whilst satisfying operating constraints on the states and inputs. The primary target is switched to the secondary target when a fault affects the system. As it is unknown when or if the fault will occur, the trajectory to the primary target is constrained to ensure reachability of the secondary target within M steps. A variable-horizon linear MPC formulation is developed to illustrate the concept. The formulation is then extended to provide robustness to bounded disturbances by use of tightened constraints. Simulations demonstrate the efficacy of the controller formulation on a double-integrator model. © 2011 IFAC.

ℓasso MPC: Smart regulation of over-actuated systems

In this paper, a novel MPC strategy is proposed, and referred to as asso MPC. The new paradigm features an 1-regularised least squares loss function, in which the control error variance competes with the sum of input channels magnitude (or slew rate) over the whole horizon length. This cost choice is motivated by the successful development of LASSO theory in signal processing and machine learning. In the latter fields, sum-of-norms regularisation have shown a strong capability to provide robust and sparse solutions for system identification and feature selection. In this paper, a discrete-time dual-mode asso MPC is formulated, and its stability is proven by application of standard MPC arguments. The controller is then tested for the problem of ship course keeping and roll reduction with rudder and fins, in a directional stochastic sea. Simulations show the asso MPC to inherit positive features from its corresponding regressor: extreme reduction of decision variables' magnitude, namely, actuators' magnitude (or variations), with a finite energy error, being particularly promising for over-actuated systems. © 2012 AACC American Automatic Control Council).

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.

Predictive control for spacecraft rendezvous in an elliptical orbit using an FPGA

A field programmable gate array (FPGA)-based predictive controller for a spacecraft rendezvous manoeuvre is presented. A linear time varying prediction model is used to accommodate elliptical orbits, and a variable prediction horizon is used to facilitate finite time completion of manoeuvres. The resulting constrained optimisation problems are solved using a primal dual interior point algorithm. The majority of the computational demand is in solving a set of linear equations at each iteration of this algorithm. To accelerate this operation, a custom circuit is implemented, using a combination of Mathworks HDL Coder and Xilinx System Generator for DSP, and used as a peripheral to a MicroBlaze soft core processor. The system is demonstrated in closed loop by linking the FPGA with a simulation of the plant dynamics running in Simulink on a PC, using Ethernet. © 2013 EUCA.

Field programmable gate array based predictive control system for spacecraft rendezvous in elliptical orbits

Copyright © 2014 John Wiley & Sons, Ltd. Copyright © 2014 John Wiley & Sons, Ltd. Summary A field programmable gate array (FPGA) based model predictive controller for two phases of spacecraft rendezvous is presented. Linear time-varying prediction models are used to accommodate elliptical orbits, and a variable prediction horizon is used to facilitate finite time completion of the longer range manoeuvres, whilst a fixed and receding prediction horizon is used for fine-grained tracking at close range. The resulting constrained optimisation problems are solved using a primal-dual interior point algorithm. The majority of the computational demand is in solving a system of simultaneous linear equations at each iteration of this algorithm. To accelerate these operations, a custom circuit is implemented, using a combination of Mathworks HDL Coder and Xilinx System Generator for DSP, and used as a peripheral to a MicroBlaze soft-core processor on the FPGA, on which the remainder of the system is implemented. Certain logic that can be hard-coded for fixed sized problems is implemented to be configurable online, in order to accommodate the varying problem sizes associated with the variable prediction horizon. The system is demonstrated in closed-loop by linking the FPGA with a simulation of the spacecraft dynamics running in Simulink on a PC, using Ethernet. Timing comparisons indicate that the custom implementation is substantially faster than pure embedded software-based interior point methods running on the same MicroBlaze and could be competitive with a pure custom hardware implementation.

Stable dynamic walking over uneven terrain

We propose a constructive control design for stabilization of non-periodic trajectories of underactuated robots. An important example of such a system is an underactuated "dynamic walking" biped robot traversing rough or uneven terrain. The stabilization problem is inherently challenging due to the nonlinearity, open-loop instability, hybrid (impact) dynamics, and target motions which are not known in advance. The proposed technique is to compute a transverse linearization about the desired motion: a linear impulsive system which locally represents "transversal" dynamics about a target trajectory. This system is then exponentially stabilized using a modified receding-horizon control design, providing exponential orbital stability of the target trajectory of the original nonlinear system. The proposed method is experimentally verified using a compass-gait walker: a two-degree-of-freedom biped with hip actuation but pointed stilt-like feet. The technique is, however, very general and can be applied to a wide variety of hybrid nonlinear systems. © The Author(s) 2011.