Inverted pendulum control system on fuzzy - neural network 神經(jīng)網(wǎng)絡(luò)控制在直接轉(zhuǎn)矩控制系統(tǒng)中的應(yīng)用
Simulation study on triple inverted - pendulum control system based on lqr arithmetic 算法的三級(jí)倒立擺控制系統(tǒng)的仿真研究
As an improvement measure to fcmac , ga - fcmac control algorithms is proposed and implemented on the inverted pendulum control successfully 作為fcmac控制的一種改進(jìn)措施,本文提出了ga - fcmac控制算法,并成功的應(yīng)用于一級(jí)倒立擺的控制中。
In the neural networks control , the structure and the working principle of the cerebella model articulation controller ( cmac ) are discussed firstly , and then based on the mutual supplements and the similarities between fcmac and fuzzy logic , fuzzified cerebella model articulation controller ( fcmac ) is proposed . the learning control system based fcmac are introduced in detail . through the example of fcmac used in the swinging up a pendulum control , the excellent control effects are demonstrated 在神經(jīng)網(wǎng)絡(luò)控制方面,本文主要研究了小腦模型關(guān)節(jié)控制器( cmac ) ,并進(jìn)而根據(jù)cmac與模糊邏輯的互補(bǔ)性與相似性,提出了模糊小腦神經(jīng)網(wǎng)絡(luò)控制器( fcamc ) ,詳細(xì)討論了fcmac的學(xué)習(xí)控制系統(tǒng)與fcmac的自學(xué)習(xí)機(jī)理,通過fcamc對(duì)倒單擺控制的具體例子表明, fcmac控制具有優(yōu)良的控制效果和強(qiáng)的魯棒性。