Although nonlinear model predictive control (NMPC) has become a well-established control approach its application to fast systems with millisecond timescales is still a challenge. In order to reduce the online computa...
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Although nonlinear model predictive control (NMPC) has become a well-established control approach its application to fast systems with millisecond timescales is still a challenge. In order to reduce the online computational effort significantly, we propose to combine two recently developed techniques: the adjoint based real-time iteration scheme which allows treatment of nonlinear processes while keeping constraint sensitivities fixed and the online active set strategy for fast solution of the resulting parametricquadratic program. Considerable performance enhancement compared with the standard real-time iteration scheme is demonstrated by controlling a system with fast dynamics.
Nearly all algorithms for linear model predictive control (MPC) either rely on the solution of convex quadratic programs (QPs) in real time, or on an explicit precalculation of this solution for all possible problem i...
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Nearly all algorithms for linear model predictive control (MPC) either rely on the solution of convex quadratic programs (QPs) in real time, or on an explicit precalculation of this solution for all possible problem instances. In this paper, we present an online active set strategy for the fast solution of parametric QPs arising in MPC. This strategy exploits solution information of the previous QP under the assumption that the active set does not change much from one QP to the next. Furthermore, we present a modification where the CPU time is limited in order to make it suitable for strict real-time applications. Its performance is demonstrated with a challenging test example comprising 240 variables and 1191 inequalities, which depends on 57 parameters and is prohibitive for explicit MPC approaches. In this example, our strategy allows CPU times of well below 100ms per QP and was about one order of magnitude faster than a standard active set QP solver. Copyright (c) 2007 John Wiley & Sons, Ltd.
An ongoing stream in financial analysis proposes mean-semivariance in place of mean-variance as an alternative approach to portfolio selection, since segments of investors are more averse to returns below the mean val...
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We propose a principal pivoting method for solving the one-parametric linear complementarity problem where all the coefficients are linear functions of the parameter K and the matrix of the problem is sufficient for a...
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