Multiplexed model predictive control

Most academic control schemes for MIMO systems assume all the control 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 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, and hence improved performance, despite finding sub-optimal solutions to the original problem. The multiplexed MPC scheme is also closer to industrial practice in many cases. This paper presents initial stability results for two variants of multiplexed MPC, and illustrates the performance benefit by an example. Copyright copy; 2005 IFAC. Copyright © 2005 IFAC.

On Solving Non-Standard H-/H2/H-Infinity Fault Detection Problems

We discuss solvability issues of H_-/H_2/infinity optimal fault detection problems in the most general setting. A solution approach is presented which successively reduces the initial problem to simpler ones. The last computational step generally may involve the solution of a non-standard H_-/H_2/infinity optimization problem for which we discuss possible solution approaches. Using an appropriate definition of the H- index, we provide a complete solution of this problem in the case of H2-norm. Furthermore, we discuss the solvability issues in the case of H-infinity-norm.

Initial modelling and controller design for active control of spacecraft microvibrations

Microvibrations, at frequencies between 1 and 1000 Hz, generated by on board equipment, propagate throughout a spacecraft structure affecting the performance of sensitive payloads. The purpose of this work is to investigate strategies to model and reduce these dynamic disturbances by active control. Initial studies were performed by considering a mass loaded panel where the disturbance excitation source consisted of point forces, the objective being to minimise the displacement at an arbitrary output location. Piezoelectric patches acting as sensors and actuators were used. The equations of motion are derived by using Lagrange's equation with modal shapes as Ritz functions. The number of sensors/actuators and their location is variable. The set of equations obtained is then transformed into state variables and some initial controller design studies have been undertaken. These are based on feedback control implemented using a full state feedback and an observer which reconstructs the state vector from the available sensor signal. Here, the basics behind the structural modelling and controller design will be described. This preliminary analysis will also be used to identify short to medium term further work.

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.

Reinforcement learning with reference tracking control in continuous state spaces

The contribution described in this paper is an algorithm for learning nonlinear, reference tracking, control policies given no prior knowledge of the dynamical system and limited interaction with the system through the learning process. Concepts from the field of reinforcement learning, Bayesian statistics and classical control have been brought together in the formulation of this algorithm which can be viewed as a form of indirect self tuning regulator. On the task of reference tracking using a simulated inverted pendulum it was shown to yield generally improved performance on the best controller derived from the standard linear quadratic method using only 30 s of total interaction with the system. Finally, the algorithm was shown to work on the simulated double pendulum proving its ability to solve nontrivial control tasks. © 2011 IEEE.

On solving non-standard ℍ -/ℍ 2/∞ fault detection problems

We discuss solvability issues of ℍ -/ℍ 2/∞ optimal fault detection problems in the most general setting. A solution approach is presented which successively reduces the initial problem to simpler ones. The last computational step generally may involve the solution of a non-standard ℍ -/ ℍ 2/∞ optimization problem for which we discuss possible solution approaches. Using an appropriate definition of the ℍ -- index, we provide a complete solution of this problem in the case of ℍ 2-norm. Furthermore, we discuss the solvability issues in the case of ℍ ∞-norm. © 2011 IEEE.

Optical trapping of nanotubes with cylindrical vector beams

We use laser beams with radial and azimuthal polarization to optically trap carbon nanotubes. We measure force constants and trap parameters as a function of power showing improved axial trapping efficiency with respect to linearly polarized beams. The analysis of the thermal fluctuations highlights a significant change in the optical trapping potential when using cylindrical vector beams. This enables the use of polarization states to shape optical traps according to the particle geometry, as well as paving the way to nanoprobe-based photonic force microscopy with increased performance compared to a standard linearly polarized configuration. © 2012 Optical Society of America.

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.

Active control of high frequency vibration in uncertain structures

The active suppression of structural vibration is normally achieved by either feedforward or feedback control. In the absence of a suitable reference signal feedforward control cannot be employed and feedback control is the only viable approach. Conventional feedback control algorithms (e.g. LQR and LQG) are designed on the basis of a mathematical model of the system and ideally the performance of the system should be robust against uncertainties in this model. The aim of this paper is to numerically investigate the robustness of LQR and LQG algorithms by designing the controller for a nominal system, and then assessing (via Monte Carlo simulation) the effects of uncertainties in the system. The ultimate concern is with the control of high frequency vibrations, where the short wavelength of the structural deformation induces a high sensitivity to imperfection. It is found that standard algorithms such as LQR and LQG are generally unfeasible for this case. This leads to a consideration of design strategies for the robust active control of high frequency vibrations. The system chosen for the numerical simulation concerns two coupled plates, which are randomized by the addition of point masses at random locations.

Joint experimental and numerical approach to three-dimensional shock control bump research

Previous studies of transonic shock control bumps have often been either numerical or experimental. Comparisons between the two have been hampered by the limitations of either approach. The present work aims to bridge the gap between computational fluid dynamics and experiment by planning a joint approach from the outset. This enables high-quality validation data to be produced and ensures that the conclusions of either aspect of the study are directly relevant to the application. Experiments conducted with bumps mounted on the floor of a blowdown tunnel were modified to include an additional postshock adverse pressure gradient through the use of a diffuser as well as introducing boundary-layer suction ahead of the test section to enable the in-flow boundary layer to be manipulated. This has the advantage of being an inexpensive and highly repeatable method. Computations were performed on a standard airfoil model, with the flight conditions as free parameters. The experimental and computational setups were then tuned to produce baseline conditions that agree well, enabling confidence that the experimental conclusions are relevant. The methods are then applied to two different shock control bumps: a smoothly contoured bump, representative of previous studies, and a novel extended geometry featuring a continuously widening tail, which spans the wind-tunnel width at the rear of the bump. Comparison between the computational and experimental results for the contour bump showed good agreement both with respect to the flow structures and quantitative analysis of the boundary-layer parameters. It was seen that combining the experimental and numerical data could provide valuable insight into the flow physics, which would not generally be possible for a one-sided approach. The experiments and computational fluid dynamics were also seen to agree well for the extended bump geometry, providing evidence that, even though thebumpinteracts directly with the wind-tunnel walls, it was still possible to observe the key flow physics. The joint approach is thus suitable even for wider bump geometries. Copyright © 2013 by S. P. Colliss, H. Babinsky, K. Nubler, and T. Lutz. Published by the American Institute of Aeronautics and Astronautics, Inc.

Experimental demonstration of optical data links using a hybrid CAP/QAM modulation scheme.

The first known experimental demonstrations of a 10 Gb/s hybrid CAP-2/QAM-2 and a 20 Gb/s hybrid CAP-4/QAM-4 transmitter/receiver-based optical data link are performed. Successful transmission over 4.3 km of standard single-mode fiber (SMF) is achieved, with a link power penalty ∼0.4 dBo for CAP-2/QAM-2 and ∼1.5 dBo for CAP-4/QAM-4 at BER=10(-9).

Self-configuring intelligent control for short reach 100Gb/s optical packet routing

An advanced control architecture is proposed which recognizes and configures new connections, automatically performs calibration and initiates the routing of 100Gb/s data packets. The scheme is proposed for high capacity, low overhead, short reach networking. © 2005 Optical Society of America.

Motor control optimization of compliant one-legged locomotion in rough terrain

While underactuated robotic systems are capable of energy efficient and rapid dynamic behavior, we still do not fully understand how body dynamics can be actively used for adaptive behavior in complex unstructured environment. In particular, we can expect that the robotic systems could achieve high maneuverability by flexibly storing and releasing energy through the motor control of the physical interaction between the body and the environment. This paper presents a minimalistic optimization strategy of motor control policy for underactuated legged robotic systems. Based on a reinforcement learning algorithm, we propose an optimization scheme, with which the robot can exploit passive elasticity for hopping forward while maintaining the stability of locomotion process in the environment with a series of large changes of ground surface. We show a case study of a simple one-legged robot which consists of a servomotor and a passive elastic joint. The dynamics and learning performance of the robot model are tested in simulation, and then transferred the results to the real-world robot. ©2007 IEEE.