In this work, we report the experimental implementation of a Quantitative Feedback Theory (QFT) based robust controller, designed online using hybrid global optimization and constraint propagation techniques. The hybrid global optimization combines interval global optimization and nonlinear local optimization methods. The constraint propagation techniques are very effective in discarding infeas...

This paper proposes a design framework that maximizes the robust performance of a closedloop system via weight optimization in H∞ loop-shaping control. In line with design objectives, frequency-dependent optimization problems are formulated in LMI framework to maximize robust performance at low and high frequencies, and directly improve the robust stability margin at mid frequencies. The philos...

Robust optimisation is a well established concept to deal with uncertainty. In particular, recovery-robust models are suitable for real-world contexts, where a certain amount of recovery – although limited – is often available. In this paper we describe a general framework to optimise event-based problems against delay propagation. We also present a real-world application to train platforming i...

In this paper we survey the primary research, both theoretical and applied, in the field of Robust Optimization (RO). Our focus will be on the computational attractiveness of RO approaches, as well as the modeling power and broad applicability of the methodology. In addition to surveying the most prominent theoretical results of RO over the past decade, we will also present some recent results ...

optimization models have been used to support decision making in production planning for a long time. however, several of those models are deterministic and do not address the variability that is present in some of the data. robust optimization is a methodology which can deal with the uncertainty or variability in optimization problems by computing a solution which is feasible for all possible ...

this paper discusses the portfolio selection based on robust optimization. since the parameters values of the portfolio optimization problem such as price of the stock, dividends, returns, etc. of per share are unknown, variable and their distributions are uncertain because of the market and price volatility, therefore, there is a need for the development and application of methodologies for de...

A systematic and affordable approach is proposed for the robust design of thick laminated composite structures. Our approach integrates the principles of the Robust Concept Exploration Method (RCEM) for designing complex engineering systems and the hierarchical multi-level optimization procedure for managing the complexity of composite structure optimization. Foundational to the proposed approa...