Abstract
One of the main problems underlying much optimization theory is local optimum. When major parametric uncertainties such as time delays, which are frequently encountered in physical systems, are presented, this problem becomes much more serious. In such situations, evolutionary optimization algorithms may be used as an attempt to overcome this difficulty. In this paper, genetic algorithm (GA) has been adopted to tackle the stated problem in the framework of robust H∞ control. GA is employed to find suitable feedback gains and delay-dependent linear matrix inequality (LMI) solvers to resolve issues related to stability conditions. In addition, to balance between exploration and exploitation, particle swarm optimization (PSO) and ant colony optimization (ACO) first individually and then as a hybrid are augmented with GA. Performance of these hybrid approach is then made with results obtained by only GA approach. The evolutionary LMI-based H∞ control scheme is applied to a single link robot arm. The controller satisfies the desired properties for not only any unknown-but-bounded disturbances but also any uncertain-but-known constant bounded time delay.
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Sabahi, F., Akbarzadeh-T., MR. (2019). Soft LMI-Based H∞ Control with Time Delay. In: Ane, B., Cakravastia, A., Diawati, L. (eds) Proceedings of the 18th Online World Conference on Soft Computing in Industrial Applications (WSC18). WSC 2014. Advances in Intelligent Systems and Computing, vol 864. Springer, Cham. https://doi.org/10.1007/978-3-030-00612-9_13
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DOI: https://doi.org/10.1007/978-3-030-00612-9_13
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