Comparison of stochastic methods for control in air traffic management

This paper provides a direct comparison of two stochastic optimisation techniques (Markov Chain Monte Carlo and Sequential Monte Carlo) when applied to the problem of conflict resolution and aircraft trajectory control in air traffic management. The two methods are then also compared to another existing technique of Mixed-Integer Linear Programming which is also popular in distributed control.Work supported by EPSRC (Engineering and Physical Sciences Research Council - UK) Grant No. EP/G066477/1International Federation of Automatic Control World Congress, 201

Repeatability of exterior traits estimations in different species of fur animals

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On Polyhedral Projection and Parametric Programming

This paper brings together two fundamental topics: polyhedral projection and parametric linear programming. First, it is shown that, given a parametric linear program (PLP), a polyhedron exists whose projection provides the solution to the PLP. Second, the converse is tackled and it is shown how to formulate a PLP whose solution is the projection of an appropriately defined polyhedron described as the intersection of a finite number of halfspaces. The input to one operation can be converted to an input of the other operation and the resulting output can be converted back to the desired form in polynomial time—this implies that algorithms for computing projections or methods for solving parametric linear programs can be applied to either problem clas

Stochastic optimization on continuous domains with finite-time guarantees by Markov chain Monte Carlo methods

We introduce bounds on the finite-time performance of Markov chain Monte Carlo algorithms in approaching the global solution of stochastic optimization problems over continuous domains. A comparison with other state-of-the-art methods having finite-time guarantees for solving stochastic programming problems is included.Comment: 29 pages, 6 figures. Revised version based on referees repor

Improved Bernstein Optimization Based Nonlinear Model Predictive Control Scheme for Power Systems

© 2017 This paper presents a improved Bernstein global optimization algorithm based model predictive control (MPC) scheme for the nonlinear systems. A new improvement in the Bernstein algorithm is the introduction of a box pruning operator, which during a branch-and-bound search, discard portions of the solution search space that do not contain global solution, thereby speeding up the algorithm. The applicability of this MPC scheme is demonstrated with a simulation studies on a nonlinear single machine infinite bus power system over a wide range of operating conditions. The simulation results show improvement in the system damping and settling time compared with the classical power system stabilizer and partial feedback linearization control schemes.National Research Foundation, Singapore

Nonlinear model predictive control based on Bernstein global optimization with application to a nonlinear CSTR

© 2016 EUCA. We present a model predictive control based tracking problem for nonlinear systems based on global optimization. Specifically, we introduce a 'Bernstein global optimization' procedure and demonstrate its applicability to the aforementioned control problem. This Bernstein global optimization procedure is applied to predictive control of a nonlinear CSTR system. Its strength and benefits are compared with those of a sub-optimal procedure, as implemented in MATLAB using fmincon function, and two well established global optimization procedures, BARON and BMIBNB.National Research Foundation, Singapore

Banded Null Basis and ADMM for Embedded MPC

© 2017 In this paper, we propose an improved QP solver for embedded implementations of MPC controllers. We adopt a “reduced Hessian” approach for handling the equality constraints that arise in the well-known “banded” formulation of MPC (in which the predicted states are not eliminated). Our key observation is that a banded basis exists for the null space of the banded equality-constraint matrix, and that this leads to a QP of the same size as the “condensed” formulation of MPC problems, which is considerably smaller than the “banded” formulation. We use the Alternating Direction Method of Multipliers (ADMM) - which is known to be particularly suitable for embedded implementations - to solve this smaller QP problem. Our C implementation results for a particular MPC example (a 9-state, 3-input quadrotor) show that our proposed algorithm is about 4 times faster than an existing well-performing ADMM variant (“indirect indicator” ADMM or “iiADMM”) and 3 times faster than the well-known QP solver CVXGEN. The convergence rate and code size of the proposed ADMM variant is also comparable with iiADMM.National Research Foundation, Singapore

Time Domain Simulations of Arm Locking in LISA

Arm locking is a technique that has been proposed for reducing laser frequency fluctuations in the Laser Interferometer Space Antenna (LISA), a gravitational-wave observatory sensitive in the milliHertz frequency band. Arm locking takes advantage of the geometric stability of the triangular constellation of three spacecraft that comprise LISA to provide a frequency reference with a stability in the LISA measurement band that exceeds that available from a standard reference such as an optical cavity or molecular absorption line. We have implemented a time-domain simulation of arm locking including the expected limiting noise sources (shot noise, clock noise, spacecraft jitter noise, and residual laser frequency noise). The effect of imperfect a priori knowledge of the LISA heterodyne frequencies and the associated 'pulling' of an arm locked laser is included. We find that our implementation meets requirements both on the noise and dynamic range of the laser frequency.Comment: Revised to address reviewer comments. Accepted by Phys. Rev.

A generic method to model carbon emission of combined cycle for environmental power dispatch

© 2017 IEEE. This paper proposes a generic methodology for combined cycle gas turbines (CCGT) modeling. The main objectives are the estimation of the CO2 emissions for specific units and their integration in an environmental power dispatch that considers several plants. At first a design procedure aims at calibrating the model using the sparse information advised by the manufactures. Off-design points are also investigated in order to estimate the CO2 emissions on the whole operating range of the units. The obtained results show a good consistency with the emission coefficients found in the literature for that type of units. Then those carbon costs are used as input parameters for a unit commitment problem (UC). The Mixed Integer Linear Programming (MILP) formulation minimizes the global emissions for a set of different units on Jurong Island in Singapore. The grid emission factor finally obtained for the simulated network displays values close to the registered field data which validates the developed model.National Research Foundation, Singapore

Model predictive control system design and implementation for spacecraft rendezvous

This paper presents the design and implementation of a model predictive control (MPC) system to guide and control a chasing spacecraft during rendezvous with a passive target spacecraft in an elliptical or circular orbit, from the point of target detection all the way to capture. To achieve an efficient system design, the rendezvous manoeuvre has been partitioned into three main phases based on the range of operation, plus a collision-avoidance manoeuvre to be used in event of a fault. Each has its own associated MPC controller. Linear time-varying models are used to enable trajectory predictions in elliptical orbits, whilst a variable prediction horizon is used to achieve finite-time completion of manoeuvres, and a 1-norm cost on velocity change minimises propellant consumption. Constraints are imposed to ensure that trajectories do not collide with the target. A key feature of the design is the implementation of non-convex constraints as switched convex constraints, enabling the use of convex linear and quadratic programming. The system is implemented using commercial-off-the-shelf tools with deployment using automatic code generation in mind, and validated by closed-loop simulation. A significant reduction in total propellant consumption in comparison with a baseline benchmark solution is observed