Intelligent robust control system for motorcycle using soft computing optimizer
US7251638B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 3, 2004 |
| Grant date | Jul 31, 2007 |
| Priority date | — |
| Expiry date | Jun 25, 2025 |
Classification
- Technology area (CPC B)Performing Operations; Transporting
- CPC primaryB62K21/00
- WIPO fieldTransport
- WIPO sectorMechanical engineering
Abstract
A Soft Computing (SC) optimizer for designing a Knowledge Base (KB) to be used in a control system for controlling a motorcycle is described. In one embodiment, a simulation model of the motorcycle and rider control is used. In one embodiment, the simulation model includes a feedforward rider model. The SC optimizer includes a fuzzy inference engine based on a Fuzzy Neural Network (FNN). The SC Optimizer provides Fuzzy Inference System (FIS) structure selection, FIS structure optimization method selection, and teaching signal selection and generation. The user selects a fuzzy model, including one or more of: the number of input and/or output variables; the type of fuzzy inference; and the preliminary type of membership functions. A Genetic Algorithm (GA) is used to optimize linguistic variable parameters and the input-output training patterns. A GA is also used to optimize the rule base, using the fuzzy model, optimal linguistic variable parameters, and a teaching signal. The GA produces a near-optimal FNN. The near-optimal FNN can be improved using classical derivative-based optimization procedures. The FIS structure found by the GA is optimized with a fitness function based on a …
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.