Font Size: a A A

Intelligent Control Algorithm Research And Implementation In Rectilinear Multi-Stage Inverted Pendulum System

Posted on:2012-08-14Degree:MasterType:Thesis
Country:ChinaCandidate:Y J HanFull Text:PDF
GTID:2178330335972384Subject:Pattern Recognition and Intelligent Systems
Abstract/Summary:PDF Full Text Request
With the development of artificial intelligence and computer technology has the potential of automatic control and artificial intelligence and systems science related disciplines in the number of branches combine to create a complex system for control theory and technology. For many complex systems, it is difficult to establish an effective mathematical model and the use of conventional control theory to the quantitative calculation and analysis, quantitative methods must be combined with the qualitative approach control. Intelligent control is produced under these conditions. Main topic of the work to complete the following three aspects:1. Limitations for the simple genetic algorithm, in the linear quadratic regulator (LQR) control, based on improved genetic algorithm, to join the elite strategy with adaptive crossover and mutation are searching for and determine the weight matrix parameters LQR Q and R. Two-stage design of linear inverted pendulum swing stability GA-LQR controller, to do real-time simulation and implementation in the inverted pendulum. Measured and the results prove the effectiveness of the controller, enabling rapid response to disturbances, and dynamic stability and robustness.2. The fuzzy control algorithm, dimension reduction based on integration of functions of the fuzzy control. Based on the GA-LQR, a linear fusion function is set up. The state variables of double inverted pendulum fusion into an integrated error E and a change of integrated error EC, as an input for stability of double inverted pendulum swing fuzzy controller. Simulation and stability for the linear double inverted pendulum, the test results show that the algorithm fast response and good stability.3. Feedback design is completed based on the theory of energy from the inverted pendulum swing the controller and the GA-LQR stability pendulum controller. Straight from the swing controller to achieve an inverted pendulum from swing, through the inverted upright position when immediately after the switch to the GA-LQR control steady swing to complete the swing from the beginning placed the full stability control.
Keywords/Search Tags:GA-LQR control, fuzzy control, energy feedback, Inverted pendulum, real-time control
PDF Full Text Request
Related items