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A Comparison of Nonsmooth, Nonconvex, Constrained Optimization Solvers for the Design of Time-Delay Compensators

Vyacheslav Kungurtsev(eslav.kungurtsev***at***fel.cvut.cz)
Tim Mitchell(mitchell***at***mpi-magdeburg.mpg.de)
Tomas Vyhlidal(tomas.vyhlidal***at***fs.cvut.cz)

Abstract: We present a detailed set of performance comparisons of two state-of-the-art solvers for the application of designing time-delay compensators, an important problem in the field of robust control. Formulating such robust control mechanics as constrained optimization problems often involves objective and constraint functions that are both nonconvex and nonsmooth, both of which present significant challenges to many solvers and their end-users hoping to obtain good solutions to these problems. In our particular engineering task, the main difficulty in the optimization arises in a nonsmooth and nonconvex stability constraint, which states that the infinite spectrum of zeros of the so-called shaper should remain in the open left half-plane. To perform our evaluation, we make use beta-relative minimization profiles, recently introduced visualization tools that are particularly suited for benchmarking solvers on nonsmooth, nonconvex, constrained optimization problems. Furthermore, we also introduce new visualization tools, called Global-Local Profiles, which for a given problem and a fixed computational budget, assess the tradeoffs of distributing the budget over few or many starting points, with the former getting more budget per point and latter less.

Keywords: nonsmooth optimization; time-delay systems; robust control; input shaper; benchmarking;computational budget

Category 1: Convex and Nonsmooth Optimization (Nonsmooth Optimization )

Category 2: Applications -- Science and Engineering (Control Applications )

Category 3: Optimization Software and Modeling Systems (Optimization Software Benchmark )

Citation: Preprint submitted December 30th, 2018.

Download: [PDF]

Entry Submitted: 12/30/2018
Entry Accepted: 12/30/2018
Entry Last Modified: 12/30/2018

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