Simulation And Application Of Multi-mode Adaptive Control System

Since the mid-twentieth century, science and technology in the developmentprocess, automatic control technology played an extremely important role. With thecontinuous development of production technology, it was the request for the controlsystem would be getting higher and higher, the traditional control technology could nolonger meet the actual needs, it was based on the actual needs of a multi-modeladaptive control and adaptive control.Multiple-Model Adaptive (MMAC) is an effective approach to solve complicatedproblems such as nonlinear, uncertainties and operating points variations etc. Howeverthe problem existed in Multi-Model Control method was that, although it has beenever-increasingly used in practice, little has been done on the theoretical studies,especially, nonlinear control approach has not been employed for this study yet. Thiswork was based on a large number of domestic and foreign paper. A betterunderstanding of the multiple model adaptive control was acquired,on the basis of twoinstances. Through two examples we could be more intuitive to understand theadvantages of multi-model adaptive control, and widely used in practice.This work first multi-model adaptive control system for the generation anddevelopment of so to introduce, and then on the multi-model adaptive controlalgorithm composition and introduction, and then gave some examples of practicalapplication and results of simulation analysis, the final design in summing up theproblems encountered. In this context, it was proposed to approximate the use ofmulti-model system dynamic performance, and then designed a multi-model based onmulti-model adaptive controller, the controller for complex systems to achieve bettercontrol accuracy, speed and tracking stability. The design of the main matlabsimulation achieved, Matlab provided a large number of aspects of the automaticcontrol of the function, modules and kits, the use of Matlab could be convenient,intuitive control system for modeling and simulation. The main theoretical results couldbe extracted in a summary form.(1) The performance of the control system could beimproved, through genetic algorithm and based on weighted multi-model adaptivecontrol algorithm.(2) The changes in a wide range of system could be well overcomedin this system. However, the system output and PID control to improve smallincreased, due to the errors of adaptive mechanism, when the other parameterschanged. And adaptive institutions in entering the order was instability, leading to the divergence of the entire control system.(3) The more model simulation was used, thecloser the result to the actual situation.