- 期刊
Adaptive Hierarchical Sliding Control of Overhead Crane System with Haar Wavelet Function Estimator
以哈爾小波為基礎的二維天車系統之適應性分層滑動控制
摘要
本研究針對欠致動之二維天車系統之定位與擺動問題，提出一以哈爾小波（Haar wavelet）為基礎之適應性分層式滑動控制（adaptive hierarchical sliding mode control）。大多數的天車系統都具有欠致動（under-actuated）和非線性的特性。所謂欠致動，即利用較少數目的控制輸入來控制較多的輸出數目。且天車系統之參數具有時變（time-varying）的特性。這些特性將大大限制了該系統的操作性能與應用環境。本文中之所有時變參數均假設為未知，且其變化範圍亦不可得知。既然系統的參數具有時變性質，故本研究將採用函數估測的技術（function estimation technique）來克服此問題。然而如同大多數以函數估測為基礎之適應性控制器，奇異值問題（singularity problem）亦會發生於輸入增益函數（input gain）的估測過程，這將會造成控制信號的發散。本研究將提出一適應性控制器來解決天車定位與擺動的問題，且奇異值問題亦可被克服。在二維天車之電腦模擬結果，驗證了本文所提出控制器之性能與可行性。
關鍵字
無資料並列摘要
In this paper, adaptive hierarchical sliding control with a Haar wavelet function estimator is presented to solve the swing problem of an overhead crane system. Most overhead crane systems belong to under-actuated nonlinear systems, which only allow a limited number of control inputs to control a large number of outputs. Moreover, the uncertainties of overhead crane systems are time varying. The operational performance and application field are strongly constrained because of these properties. In this research, all time-varying uncertainties are assumed to be unknown and variation bounds are assumed to be unavailable. Because the uncertainties are time varying, we can employ some well-known function estimation approaches to deal with this problem. However, the singularity problem may occur during the procedure of unknown input gain estimation, which may cause the control effort to become unbounded. Therefore, this study aims to develop an adaptive controller for the swing problem of an overhead crane. Furthermore, the singularity problem of input gain estimation can also be solved by the proposed control strategy. A 2-DOF crane system is used in a computer simulation to verify the validity and effectiveness of the proposed control law.