Suboptimal control algorithm for nonlinear MIMO System

Author(s):  
Sergey Vrazhevsky ◽  
Artem Kremlev
2019 ◽  
Vol 22 (2) ◽  
pp. 424-443 ◽  
Author(s):  
Wojciech Przemysław Hunek

Abstract A new perfect control algorithm dedicated to fractional-order right-invertible systems, i.e. plants with a greater number of input than output variables, is presented in this paper. It is shown that such a control strategy can be particularly applied with regard to practical tasks. Henceforth, the Grünwald-Letnikov difference operator Δα of an assumed order α can be truncated without loss of generality. For that reason, the so-called pole-free perfect control formula can be used to minimize the essential drawback of the Grünwald-Letnikov approach engaged, so as to define the intriguing issue regarding the robust perfect control for non-integer-order right-invertible LTI discrete-time state-space systems. Simulation examples show that the presented method can compete with a classical stable-pole one, for which the actual systems described by a fractional-order model often correspond with an inconvenient asymptotic perfect control solution given by the unlimited original operator Δα. In the end, the possibility of employing of author’s nonunique right inverses dedicated to nonsquare MIMO system matrices is demonstrated, thus giving rise to the introduction of a new powerful tool for robustification of non-integer-order closed-loop perfect control plants as well.


Author(s):  
Andreas A. Malikopoulos

The growing demand for making autonomous intelligent systems that can learn how to improve their performance while interacting with their environment has induced significant research on computational cognitive models. Computational intelligence, or rationality, can be achieved by modeling a system and the interaction with its environment through actions, perceptions, and associated costs. A widely adopted paradigm for modeling this interaction is the controlled Markov chain. In this context, the problem is formulated as a sequential decision-making process in which an intelligent system has to select those control actions in several time steps to achieve long-term goals. This paper presents a rollout control algorithm that aims to build an online decision-making mechanism for a controlled Markov chain. The algorithm yields a lookahead suboptimal control policy. Under certain conditions, a theoretical bound on its performance can be established.


2020 ◽  
pp. 107754632093274
Author(s):  
Lingjun Zhuo ◽  
Haili Liao ◽  
Mingshui Li

Flutter control is necessary in the design of a long-span bridge. With the help of active flaps, flutter control can suppress flutter vibration and increase aerodynamic stability. This study aims to build a theoretical framework for active flutter control using a system consisting of a streamlined box girder with adjacently mounted active flaps (noted as a “deck–flap system”). An adaptive expression was proposed for the system’s self-excited forces, and an identification method was established for obtaining the system flutter derivatives in consideration of the bluff characteristics of the bridge deck and the aerodynamic interactions between the bridge girder and flaps. Then, the suboptimal control algorithm was implemented into the deck–flap system to simultaneously stabilize the divergent oscillation at the designed wind speed. Based on the proposed approach, numerical simulations were conducted to investigate the system flutter derivatives and the effectiveness of the control law. A comparison between the critical speeds of the two-dimensional flutter analysis and a fluid–structure interaction simulation showed a satisfactory performance from the theoretical model and the reliability of the identification method. The vibrations of the deck–flap system were successfully suppressed by the controlled motions of the active flaps under the application of the suboptimal control algorithm. This study provides a reliable framework for conducting an analysis of active control for bridge flutter and for significantly increasing the flutter stability of a deck–flap system.


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