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Compact Ant Colony Optimization Algorithm Based Fuzzy Neural Network Backstepping Controller for MIMO Nonlinear Systems
(2010-07-03) W.-Y. Wang; C.-K. Chen; Y.-G. Leu; C.-Y. Chen
In this paper, a compact ant colony algorithm used to tune parameters of fuzzy-neural networks is proposed for function approximation and adaptive control of nonlinear systems. In adaptive control procedure for nonlinear systems, weights of the fuzzy neural controller are online adjusted by the compact ant algorithm in order to generate appropriate control input. For the purpose of evaluating the stability of the closed-loop systems, an energy fitness function is used in the ant algorithm. Finally, a computer simulation example demonstrates the feasibility and effectiveness of the proposed method.
SOC Estimation of Series Connected Lithium-Ion Batteries and Supercapacitors Using Hierarchical Fuzzy Neural Network
(2010-07-02) W.-L. Chang; I-H. Li; Y.-S. Lee; S.-F. Su; W.-Y. Wang
Adaptive Nonlinear Parametric Neural Control of Nonaffine Nonlinear Systems
(2010-07-03) Y.-G. Leu; W.-C. Leu; W.-Y. Wang; Z.-H. Lee
By using B-spline neural networks, an adaptive nonlinear parametric control scheme for nonlinear systems is proposed in this paper. The control scheme which is utilized to design the control input incorporates the adaptive control design technique with the mean-estimation B-spline neural networks. Compared with other neural networks, the B-spline neural networks possess output behavior the characteristic feature of locally controlling. Therefore, they are very suitable to online estimate system dynamics by tuning both control and knot points. The B-spline neural networks with a mean苟stimation technique are used in an attempt to avoid difficulty of differentiating B-spline basis functions. In addition, two robust controllers are used to compensate un modeling dynamics. Finally, an example is provided to demonstrate the feasibility of the proposed scheme, and a comparative study is given by computer simulation.
An Image-Based Area Measurement System
(2011-06-10) C.-T. Chuang; C.-P. Tsai; M.-C. Lu; W.-Y. Wang; Y.-H. Chien
A novel image-based area measurement system is proposed in this paper, we can convert the pixels of object into real area by image processes. No matter the system is vertical to the measuring plane or not and the height of system, it could calculates arbitrary two points on the image convert into the actual distance. This paper proposed a new structure for achieve our goal, there are four laser projects and camera fixed on same base, then generate four laser spots on the object or measurement plant, and assume connect each two laser spots as parallel lines, finally it could simulated a ruler in the image. Without consider photography angle for this system, it can measure area of floor or height of building.
Map Construction for Self-Propelled Vehicle Using Fuzzy Measure Theory
(2011-11-27) G.-Y. Pan; Y.-C. Lin; W.-Y. Wang; Y.-G. Leu
Image-Based Landslide Monitoring System
(2011-06-10) M.-C. Lu; T.-Y. Tang; C.-P. Tsai; W.-Y. Wang; I-H. Li
a novel image-based landslide monitoring system proposed in this paper, which is using digital image processes methods to detect landslide occurred in any landslide occurred situation to achieve a non-contact landslide monitoring system by one image. The theory of this system is based on using a laser projector to project a laser beam to measurement box, which have two acrylic boards in the measurement box. When landslide occurred, the laser beam will generate two laser spots in image. To identify the coordinate of laser spots through an easy calculation, the system could get the landslide displacement and offset angle. According the measurement result, it could announce the warning and prevent the damage.
Design and Implementation of FPGA-Based Landslide Detection and Real-Time Monitoring System
(2011-11-27) C.-P. Tsai; W.-Y. Wang; M.-C. Lu; Y.-H. Chien; S.-F. Su
Fuzzy measure based mobile robot controller for autonomous movement control
(2011-06-10) G.-Y. Pan; C.-P. Tsai; M.-C. Chen; W.-Y. Wang; C.-R. Tsai
This paper proposes a novel fuzzy measure based mobile robot controller design method. We apply this method in a simulation where the movement of a mobile robot along a wall is governed by this controller. The ultrasonic range finder sensors onboard the mobile robot are used to measure the distance between the robot and the wall. The measurement results are recorded as fuzzy measure inputs and the results of the fuzzy measure are used to control the movement of the mobile robot along the wall. Our simulations compare the movements of the mobile robot with and without the fuzzy measure controller. The simulation results show that the mobile robot using the fuzzy measure controller exhibits a more controlled movement behavior than that using a controller without fuzzy measure.
Development and Verification of Particle Swarm Optimization Integrated with Taguchi Method
(2011-11-27) Y.-H. Huang; Y.-L. Chen; J.-Y. Chen; W.-Y. Wang; C.-H. Liu
Design of Adaptive T-S Fuzzy-Neural Controller for a Class of Robot Manipulators Using Projection Update Laws
(2010-10-13) Y.-H. Chien; W.-Y. Wang; T.-T. Lee
An on-line tracking controller design based on using T-S fuzzy-neural modeling for a class of general robot manipulators is investigated in this paper. Also, we use rojection update laws to tune adjustable parameters for preventing parameters drift. In addition, stability of the closed-loop systems is proven by using strictly-positive-real (SPR) Lyapunov theory. The proposed overall scheme guarantees that all signals involved are bounded and the outputs of the closed-loop system asymptotically track the desired output trajectories. Finally, an example including two cases confirms the effectiveness of the proposed method.

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