Multiplexed model predictive control

This paper proposes a form of MPC in which the control variables are moved asynchronously. This contrasts with most MIMO control schemes, which assume that all variables are updated simultaneously. MPC outperforms other control strategies through its ability to deal with constraints. This requires on-line optimization, hence computational complexity can become an issue when applying MPC to complex systems with fast response times. The Multiplexed MPC (MMPC) scheme described in this paper solves the MPC problem for each subsystem sequentially, and updates subsystem controls as soon as the solution is available, thus distributing the control moves over a complete update cycle. The resulting computational speed-up allows faster response to disturbances, which may result in improved performance, despite finding sub-optimal solutions to the original problem. This paper describes nominal and robust MMPC, states some stability results, and demonstrates the effectiveness of MMPC through two examples. © 2011 Elsevier Ltd. All rights reserved.

Centrifuge modelling and dynamic testing of municipal solid waste (MSW) landfills

An investigation into the seismic behaviour of municipal solidwaste (MSW) landfills by dynamic centrifuge testing was undertaken. This paper presents physical modelling of MSW landfills for dynamic centrifuge testing, with regard to the following research areas: 1. amplification characteristics of municipal solid waste; 2. tension induced in geomembranes placed on landfill slopes due to earthquake loading; 3. damage to landfill liners due to liquefaction of foundation soil. A model waste, that has engineering properties similar to MSW, is presented. A model geomembrane that can be used in centrifuge tests is also presented. Results of dynamic centrifuge tests with the model geomembrane showed that an earthquake loading induces additional permanent tension (∼25%) in the geomembrane. © 2006 Taylor & Francis Group, London.

Bias-free identification of a linear model-predictive steering controller from measured driver steering behavior

Recent developments in modeling driver steering control with preview are reviewed. While some validation with experimental data has been presented, the rigorous application of formal system identification methods has not yet been attempted. This paper describes a steering controller based on linear model-predictive control. An indirect identification method that minimizes steering angle prediction error is developed. Special attention is given to filtering the prediction error so as to avoid identification bias that arises from the closed-loop operation of the driver-vehicle system. The identification procedure is applied to data collected from 14 test drivers performing double lane change maneuvers in an instrumented vehicle. It is found that the identification procedure successfully finds parameter values for the model that give small prediction errors. The procedure is also able to distinguish between the different steering strategies adopted by the test drivers. © 2006 IEEE.

Experience using MEMS-based accelerometers in dynamic testing

Measurement of acceleration in dynamic tests is carried out routinely, and in most cases, piezoelectric accelerometers are used at present. However, a new class of instruments based on MEMS technology have become available and are gaining use in many applications due to their small size, low mass and low-cost. This paper describes a centrifuge lateral spreading experiment in which MEMS and piezoelectric accelerometers were placed at similar depths. Good agreement was obtained when the instruments were located in dense sands, but significant differences were observed in loose, liquefiable soils. It was found that the performance of the piezoelectric accelerometer is poor at low frequency, and that the relative phase difference between the piezoelectric and MEMS accelerometer varies significantly at low frequency. © 2010 Taylor & Francis Group, London.

Testing in harsh conditions: Tracking resources on construction sites with machine vision

When tracking resources in large-scale, congested, outdoor construction sites, the cost and time for purchasing, installing and maintaining the position sensors needed to track thousands of materials, and hundreds of equipment and personnel can be significant. To alleviate this problem a novel vision based tracking method that allows each sensor (camera) to monitor the position of multiple entities simultaneously has been proposed. This paper presents the full-scale validation experiments for this method. The validation included testing the method under harsh conditions at a variety of mega-project construction sites. The procedure for collecting data from the sites, the testing procedure, metrics, and results are reported. Full-scale validation demonstrates that the novel vision tracking provides a good solution to track different entities on a large, congested construction site.

Testing of Depth-Encoded Hough Voting for Infrastructure Object Detection

The lack of viable methods to map and label existing infrastructure is one of the engineering grand challenges for the 21st century. For instance, over two thirds of the effort needed to geometrically model even simple infrastructure is spent on manually converting a cloud of points to a 3D model. The result is that few facilities today have a complete record of as-built information and that as-built models are not produced for the vast majority of new construction and retrofit projects. This leads to rework and design changes that can cost up to 10% of the installed costs. Automatically detecting building components could address this challenge. However, existing methods for detecting building components are not view and scale-invariant, or have only been validated in restricted scenarios that require a priori knowledge without considering occlusions. This leads to their constrained applicability in complex civil infrastructure scenes. In this paper, we test a pose-invariant method of labeling existing infrastructure. This method simultaneously detects objects and estimates their poses. It takes advantage of a recent novel formulation for object detection and customizes it to generic civil infrastructure scenes. Our preliminary experiments demonstrate that this method achieves convincing recognition results.

Fault-tolerant model predictive control of a wind turbine benchmark

This paper aims to solve the fault tolerant control problem of a wind turbine benchmark. A hierarchical controller with model predictive pre-compensators, a global model predictive controller and a supervisory controller is proposed. In the model predictive pre-compensator, an extended Kalman Filter is designed to estimate the system states and various fault parameters. Based on the estimation, a group of model predictive controllers are designed to compensate the fault effects for each component of the wind turbine. The global MPC is used to schedule the operation of the components and exploit potential system-level redundancies. Extensive simulations of various fault conditions show that the proposed controller has small transients when faults occur and uses smoother and smaller generator torque and pitch angle inputs than the default controller. This paper shows that MPC can be a good candidate for fault tolerant controllers, especially the one with an adaptive internal model combined with a parameter estimation and update mechanism, such as an extended Kalman Filter. © 2012 IFAC.

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.

Channel-hopping model predictive control

In Multiplexed MPC, the control variables of a MIMO plant are moved asynchronously, following a pre-planned periodic sequence. The advantage of Multiplexed MPC lies in its reduced computational complexity, leading to faster response to disturbances, which may result in improved performance, despite finding sub-optimal solution to the original problem. This paper extends the original Multiplexed MPC in a way such that the control inputs are no longer restricted to a pre-planned periodic sequence. Instead, the most appropriate control input channel would be optimised and selected to counter the disturbances, hence the name 'Channel-Hopping'. In addition, the proposed algorithm is suitable for execution on modern computing platforms such as FPGA or GPU, exploits multi-core, parallel and pipeline computing techniques. The algorithm for the proposed Channel-hopping MPC (CH-MPC) will be described and its stability established. Illustrative examples are given to demonstrate the behaviour of the proposed Channel-Hopping MPC algorithm. © 2011 IFAC.

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.

UK-NEES - Distributed hybrid testing between Bristol, Cambridge and Oxford Universities: Connecting structural dynamics labs to a geotechnical centrifuge

Distributed hybrid testing is a natural extension to and builds upon the local hybrid testing technique. Taking advantage of the hybrid nature of the test, it allows a sharing of resources and expertise between researchers from different disciplines by connecting multiple geographically distributed sites for joint testing. As part of the UK-NEES project, a successful series of three-site distributed hybrid tests have been carried out between Bristol, Cambridge and Oxford Universities. The first known multi-site distributed hybrid tests in the UK, they connected via a dedicated fibre network, using custom software, the geotechnical centrifuge at Cambridge to structural components at Bristol and Oxford. These experiments were to prove the connection and useful insights were gained into the issues involved with this distributed environment. A wider aim is towards providing a flexible testing framework to facilitate multi-disciplinary experiments such as the accurate investigation of the influence of foundations on structural systems under seismic and other loading. Time scaling incompatibilities mean true seismic soil structure interaction using a centrifuge at g is not possible, though it is clear that distributed centrifuge testing can be valuable in other problems. Development is continuing to overcome the issues encountered, in order to improve future distributed tests in the UK and beyond.