模糊控制應用於渾沌系統和機器人系統;Fuzzy Control Applications to Chaotic and Robotic Systems

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题名:	模糊控制應用於渾沌系統和機器人系統;Fuzzy Control Applications to Chaotic and Robotic Systems
作者:	周顥恭;Chou, Hao-Gong
贡献者:	電機工程學系
关键词:	渾沌系統;六足機器人;模糊控制;D-H轉換;Chaotic System;Hexapod robot;Fuzzy Control;Denavit -Hartenberg convention;H infinity;T-S Fuzzy-Model-Based;Polynomial Fuzzy-Model-Based;sum-of-squares (SOS)
日期:	2017-08-17
上传时间:	2017-10-27 16:13:06 (UTC+8)
出版者:	國立中央大學
摘要:	本論文針對渾沌保密系統和六足機器人系統，提出了模糊控制之設計與實現。首先，針對渾沌保密系統，提出兩種基於模糊建模之混沌系統同步方法。第一種方法提出了基於Takagi–Sugeno 模糊模型的有限時間(finite-time)之混沌系統同步設計。首先，主僕系統分別被精確地表示為主僕T-S模糊模型。然後，設計出即使在僕系統中存在外部干擾，也能在有限時間T內實現主僕同步之模糊控制器，並利用具有Altera Cyclone IV 4CE115 FPGA晶片的開發板(Altera DE2-115）和電腦（PC）實現。在針對渾沌保密系統的第二種方法，則是提出考慮性能及輸入限制，並基於多項式模糊模型之設計，用以同步具有多混沌子的陳混沌系統(multi-scroll Chen chaotic systems )。首先，利用主僕多項式模糊模型分別精確的表示主僕的多混沌子的陳混沌系統模型，再設計多項式模糊控制器來同步主僕系統。此外，為了抑制外部干擾和實際應用，在多項式模糊控制設計中也考慮到了性能和輸入限制。透過兩台個人電腦和路由器實現保密通訊，其中主系統的電腦核心為Intel i5-5250U CPU，而從系統的電腦核心為Intel i5-3337U CPU。此外，主從系統和多項式模糊控制器的設計是利用MATLAB 2015b的Simulink實現。針對六足機器人系統，本文提出了一種六足形機器人可以穩定在斜坡上行走的模糊邏輯控制策略，並採用速度較快的三角步態。機器人的姿態是由模糊控制器根據傾斜坡度進行調整，目的是讓機器人的重心（COG）垂直投影，保持在各足底形成的支撐多邊形中。此外，利用Denavit-Hartenberg轉換和正運動學來計算馬達和各足的終端位置。並安裝慣性測量單元( IMU)在機器人身體中心以獲取機器人在斜面上的旋轉矩陣，藉此推算出重心的垂直投影。並提出一種模糊邏輯控制器來調整支撐足的馬達，讓重心的垂直投影接近支撐多邊形的理想重心。最後，透過實驗，以證明所提出的模糊控制策略的有效性。透過提出的模糊邏輯控制，可以讓六足機器人的穩定邊界(stability margin)最大化，讓機器人可以穩定地在斜坡上行走。 ;This dissertation proposes the design and implementation of fuzzy control for the chaos-based secure communication system (SCS) and hexapod robotic system. For the chaos-based SCS, two fuzzy-model-based approaches are proposed for synchronization the chaotic systems. The first approach proposes a T-S fuzzy-model-based finite-time chaotic synchronization design for the SCS. Firstly, the master and slave chaotic systems are exactly represented as the master and slave T-S fuzzy models respectively. Then the fuzzy controller is designed to guarantee that master-slave synchronization can be completely achieved within a pre-specified convergence time T even when an external disturbance exists in the slave system. The hardware of the chaos-based SCS with the proposed fuzzy control is implemented on a development board (Altera DE2-115), which comprises an Altera Cyclone IV 4CE115 FPGA chip, and on a personal computer (PC). In the second approach for SCS, a polynomial fuzzy-model-based design with considering a constraint on the control input is proposed to synchronize the multi-scroll Chen chaotic systems. Firstly, the master and slave multi-scroll Chen chaotic systems are exactly represented as the master and slave polynomial fuzzy models respectively. Then a polynomial fuzzy control is proposed for synchronizing the master and slave chaotic systems. Moreover, for restraining external disturbances and practical consideration, performance and a constraint on the control input are also considered in the polynomial fuzzy control design. The SCS is implemented by two personal computers (PCs) communicating with each other through a router. The master PC is with an Intel i5-5250U CPU, and the slave PC is with an Intel i5-3337U CPU. Moreover, the master and slave chaotic systems and the proposed polynomial fuzzy controller are implemented by the Simulink of MATLAB 2015b. For the hexapod robotic systems, a fuzzy logic control is proposed such that the hexapod robot can stably walk on an incline. We apply the tripod gait for relatively fast walking. Moreover, according to the slope of an incline, the proposed fuzzy logic control modifies the posture of the hexapod robot such that the vertical projection of the center of gravity (COG) can be maintained in the support polygon. Moreover, the Denavit-Hartenberg (D–H) convention and forward kinematics are applied to calculate the positions of the motors and end points of the legs in the coordinate system of the robot’s body. An inertial measurement unit is settled at the center of the robot’s body to obtain the rotation matrix for calculating the vertical projection of COG when the robot is walking on an incline. Then, a fuzzy logic control is proposed to adjust the motor angles of supporting legs for maintaining the vertical projection of COG close to the COG of support polygon. The stability margin of the hexapod robot is maximized by the proposed fuzzy logic control, hence the robot can stably walk on an incline.
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