Skip to main content

Nonlinear Rectification of Sensor Based on Particle Swarm Optimization with Chaos

Buy Article:

$113.00 plus tax (Refund Policy)


A Chaotic Particle Swarm Optimization (CPSO) algorithm is proposed. In this method, the known tent map is incorporated into PSO algorithm to gain balance between global search and local search, thus improving the speed and accuracy of the algorithm convergence. A nonlinear rectification principle of sensor is introduced which is different from the traditional methods, then the CPSO algorithm is applied to parameter estimation of nonlinear rectification of sensor. Finally, the effectiveness of the proposed algorithm is tested through simulation experiments on the nonlinear rectification of electric-eddy-type micro displacement sensor. The experiment results show that, compared with traditional PSO, with the CPSO, the parameter estimation of nonlinear rectification of sensor is enabled to achieve a better global optimization and a higher converging speed, the rectification curve is more accurate, and the rectification value has an excellent linear relation with input signal. So it can be concluded that this proposed algorithm can be seen as a very promising option to solve nonlinear rectification of sensor.


Document Type: Research Article


Publication date: 2011-10-01

More about this publication?
  • The growing interest and activity in the field of sensor technologies requires a forum for rapid dissemination of important results: Sensor Letters is that forum. Sensor Letters offers scientists, engineers and medical experts timely, peer-reviewed research on sensor science and technology of the highest quality. Sensor Letters publish original rapid communications, full papers and timely state-of-the-art reviews encompassing the fundamental and applied research on sensor science and technology in all fields of science, engineering, and medicine. Highest priority will be given to short communications reporting important new scientific and technological findings.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free ContentFree content
  • Partial Free ContentPartial Free content
  • New ContentNew content
  • Open Access ContentOpen access content
  • Partial Open Access ContentPartial Open access content
  • Subscribed ContentSubscribed content
  • Partial Subscribed ContentPartial Subscribed content
  • Free Trial ContentFree trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more