Constant Acceleration Control of Valve-Control-Cylinder System Based on Neural Network

Abstract:

To solve the serious problem of the nonlinear and Time-varying uncertainty of the valve-control-cylinder system, a control system was designed with neural-proportion-integral-differential (PID) theory. Because of the capacity of neural network, the control system showed adaptive capacity in the system of valve-control-cylinder. In this paper, the basic theory of a single neural element self-adaptive PID controller and a model identifier based on Radial Basis Function were described. The mathematic model of the valve-control-cylinder control system was set up. The simulation results prove that the neural-PID system can regulate the PID parameters dynamically by self-learning so that the system with the neural-PID controller showed quick track performance and capacity against the disturbance. The results also prove the validity and applicability of the system. The algorithm is simple, PID initial parameters are easy to adjust, easy in application of the real-time control the valve-control-cylinder system.

• Periodical: Advanced Materials Research (Volumes 430-432)
• Pages: 2041-2045
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.430-432.2041
• Online since: January 2012
• Authors: Jun Gong Ma, Xian Yang Shang
• Keywords: Identification, Neural Network (NN), Self-Adaptive PID, Valve-Control-Cylinder

References

[1] Pei Xuechong: Improved PID Control Based on RBF Neural Network (Harbin University of Science and Technology 2010).

[2] Li Jinjing and Li Hong: Research about Self-adaption Controller Based on the Platform of Electro-hydraulic Position Servo Control System for Test(Science & Technology Information 2010).