Adaptive PI Hermite neural control for MIMO uncertain nonlinear systems

[[abstract]]This paper presents an adaptive PI Hermite neural control (APIHNC) system for multi-input multi-output (MIMO) uncertain nonlinear systems. The proposed APIHNC system is composed of a neural controller and a robust compensator. The neural controller uses a three-layer Hermite neural network (HNN) to online mimic an ideal controller and the robust compensator is designed to eliminate the effect of the approximation error introduced by the neural controller upon the system stability in the Lyapunov sense. Moreover, a proportional–integral learning algorithm is derived to speed up the convergence of the tracking error. Finally, the proposed APIHNC system is applied to an inverted double pendulums and a two-link robotic manipulator. Simulation results verify that the proposed APIHNC system can achieve high-precision tracking performance. It should be emphasized that the proposed APIHNC system is clearly and easily used for real-time applications.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

New developments in mathematical control and information for fuzzy systems

Hamid Reza Karimi, Mohammed Chadli and Peng Sh

Adaptive hermite-polynomial-based CMAC neural control for chaos synchronization

[[abstract]]An adaptive Hermite-polynomial-based CMAC neural control (AHCNC) system which is composed of a neural controller and a smooth compensator is proposed. The neural controller using a Hermite-polynomial-based CMAC neural network (HCNN) is main controller and the smooth compensator is designed to guarantee system stable in the Lyapunov stability theorem.[[notice]]缺頁數[[incitationindex]]EI[[conferencetype]]國際[[conferencedate]]20121130~20121202[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Yunlin, Taiwa

Adaptive hermite-polynomial-based CMAC neural control for chaos synchronization

[[abstract]]Gyros are a particularly interesting form of nonlinear systems that have attracted many researchers due to their applications in the navigational, aeronautical and space engineering domains. In this paper, a problem of synchronization between two chaotic gyros based on a mater-slave scheme is studied. An adaptive Hermite-polynomial-based CMAC neural control (AHCNC) system which is composed of a neural controller and a smooth compensator is proposed. The neural controller using a Hermite-polynomial-based CMAC neural network (HCNN) is main controller and the smooth compensator is designed to guarantee system stable in the Lyapunov stability theorem. Finally, the simulation results show that the proposed AHCNC scheme can achieve favorable chaos synchronization after the controller parameters learning.[[sponsorship]]Chinese Automatic Control Society (CACS); National Formosa University Taiwan[[conferencetype]]國際[[conferencedate]]20121130~20121202[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Yunlin, Taiwa

Komputasi Parameter Adaptif Fuzzy Controller pada Sistem Pengering Kayu

Komputasi terhadap parameter kontrol menjadi penting dilakukan sesuai hasil pengukuran pada sebuah prototipe sistem pengering kayu, dengan tujuan untuk mendapatkan hasil yang lebih riil. Parameter yang dianalisis berkaitan dengan penerapan adaptif fuzzy controller (AFC) pada prototipe alat pengering kayu tenaga panas surya, yaitu berupa besaran control priode sistem untuk perlakukan yang berbeda-beda dari aktuator. AFC di implementasikan dengan mekanisme adaptasi yang diarahkan bekerja pada sistem ketika terjadi Perubahan humiditi drying dari sebuah jadwal pengeringan kayu sengon, tetapi dengan kondisi temperatur drying yang tetap. Mekanisme ini membandingkan model reference dan situasi riil ruang pengering sesuai kondisi cuaca untuk mendapatkan kondisi yang diinginkan. Hasil implementasi disajikan dalam bentuk look-up table dari perlakuan aktuator pada rule AFC

An annotated bibligraphy of multisensor integration

technical reportIn this paper we give an annotated bibliography of the multisensor integration literature

Supervised fault tolerant control architecture for nonlinear systems

Scope: The growing complexity of physical plants and control missions inevitably leads to increasing occurrence, diversity and severity of faults. Availability, defined as the probability that a system or equipment will operate satisfactory and effectively at any point of time, becomes a factor of increasing importance. Fault Tolerant Control (FTC) is a field of research that aims to increase availability and reduce the risk of safety hazards and other undesirable consequences by specifically designing control algorithms capable of maintaining stability and/or performance despite the occurrence of faults. This report presents a novel FTC solution based on a hierarchical architecture in which an adaptive critic controller is overseen by a supervisor managing a dynamic model bank of fault solutions.Findings and Conclusions: The presented work has demonstrated that the implementation of a synergistic combination of a reconfigurable controller and a fault diagnosis and controller malfunction detection supervisor based on three distinct quality indexes generates an efficient and reliable FTC architecture. The application of adaptive critic designs as reconfigurable controllers is shown to give the hierarchical algorithm the degree of flexibility required to deal with both abrupt and incipient unknown changes in the plant dynamics due to faults. The proposed supervisor system is used to accelerate the convergence of the method by loading new initial conditions to the controller when the plant is affected by a known abrupt fault. Moreover, the developed fault diagnosis decision logic is capable of recognizing new fault scenarios and assimilating them online to the dynamic model bank, along with parameters for the corresponding controller. The introduction of the weight quality index has made possible to distinguish between faults in the plant and controller malfunctions caused by online training divergence or local minima convergence. In order to achieve application-specific key FTC specifications, a methodology for initializing and tuning twelve distinct parameters of the quality indexes was also developed. Finally, a series of key steps that form the basis for the fault development information extraction module capable of providing the probability of occurrence of future faults to the user, are also included in this report