Related Experiment Videos
A reduction approach for fuzzy rule bases of fuzzy controllers
1Dept. of Electr. Eng., Nat. I-Lan Inst. of Technol., Taiwan.
Abstract:
In this paper, a new approach to reducing the number of rules in a given fuzzy rule base of a fuzzy controller is presented. The fuzzy mechanism of the fuzzy controller under consideration consists of the product-sum inference, singleton output consequents and centroid defuzzification. The output consequents in the cells of the rule table are collected and represented as an output consequent matrix. The feature of the output consequent matrix is extracted by the singular values of the matrix. The output consequent matrix is reasonably approximated with a dominant consequent matrix. Also, the elements of the dominant consequent matrix is determined to minimize the approximation error function. Then the size of the dominant consequent matrix (the size of the fuzzy rule base) is reduced through the rule combination approach. The scaling factors for the fuzzy controller with the reduced rule table are adjusted to have the control system satisfy the performance indices. The effectiveness of the proposed approach is shown using simulation and experimental results.
Related Concept Videos
Block Diagram Reduction
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
Controller Configurations
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller aligns...
Feedback control systems
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
Woodward–Hoffmann Selection Rules and Microscopic Reversibility
Mason's Rule
Loop gain is determined by identifying and tracing a path from a node back to itself. This involves computing the product of branch gains along the loop. Each loop's gain is crucial for further...
Root-Locus Method
This system can be represented by a block diagram,...