An Adaptive Suboptimal Control Algorithm with Variable Design Parameter for Systems with Stochastic Parameters

2015 ◽  
Vol 26 (3) ◽  
pp. 215-224
Author(s):  
Aderson Jamier Santos Reis ◽  
André Laurindo Maitelli
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.


2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Ruisheng Sun ◽  
Qiao Hong ◽  
Gang Zhu

This paper presents a new parametric optimization approach based on a modified particle swarm optimization (PSO) to design a class of impulsive-correction projectiles with discrete, flexible-time interval, and finite-energy control. In terms of optimal control theory, the task is described as the formulation of minimum working number of impulses and minimum control error, which involves reference model linearization, boundary conditions, and discontinuous objective function. These result in difficulties in finding the global optimum solution by directly utilizing any other optimization approaches, for example, Hp-adaptive pseudospectral method. Consequently, PSO mechanism is employed for optimal setting of impulsive control by considering the time intervals between two neighboring lateral impulses as design variables, which makes the briefness of the optimization process. A modification on basic PSO algorithm is developed to improve the convergence speed of this optimization through linearly decreasing the inertial weight. In addition, a suboptimal control and guidance law based on PSO technique are put forward for the real-time consideration of the online design in practice. Finally, a simulation case coupled with a nonlinear flight dynamic model is applied to validate the modified PSO control algorithm. The results of comparative study illustrate that the proposed optimal control algorithm has a good performance in obtaining the optimal control efficiently and accurately and provides a reference approach to handling such impulsive-correction problem.


2015 ◽  
Vol 2 (1) ◽  
pp. 6-12
Author(s):  
Agus Sugiarta ◽  
Houtman P. Siregar ◽  
Dedy Loebis

Automation of process control in chemical plant is an inspiring application field of mechatronicengineering. In order to understand the complexity of the automation and its application requireknowledges of chemical engineering, mechatronic and other numerous interconnected studies.The background of this paper is an inherent problem of overheating due to lack of level controlsystem. The objective of this research is to control the dynamic process of desired level more tightlywhich is able to stabilize raw material supply into the chemical plant system.The chemical plant is operated within a wide range of feed compositions and flow rates whichmake the process control become difficult. This research uses modelling for efficiency reason andanalyzes the model by PID control algorithm along with its simulations by using Matlab.


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