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Chattering can be removed in DSMC with an integrator as a low-pass filter, placed before the input control signal of the plant. As a result, the augmented system (which contains the integrator) in DSMC has one more dimension than the actual system. Then the plant model must be completely known. To overcome this problem and to identify the plant model, an adaptive radial basis-function neural network has been employed and a robust procedure developed to train the parameters of a neural network based on Lyapunov theory. A smooth controller has been developed and some numerical simulations have been performed to verify the validity of the proposed approach. Two nonlinear systems were used for simulation: a Duffing\u2013Holmes chaotic system and a switch reluctance motor. The advantage of the presented approach is that the system model can be considered unknown and can be in non-affine form.<\/jats:p>","DOI":"10.1177\/0142331218819705","type":"journal-article","created":{"date-parts":[[2019,1,29]],"date-time":"2019-01-29T01:33:07Z","timestamp":1548725587000},"page":"3033-3042","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["State tracking control of nonlinear systems using neural adaptive dynamic sliding mode"],"prefix":"10.1177","volume":"41","author":[{"given":"Ali","family":"Karami-Mollaee","sequence":"first","affiliation":[{"name":"Electrical and Computer Engineering Faculty, Hakim Sabzevari University, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamed","family":"Tirandaz","sequence":"additional","affiliation":[{"name":"Electrical and Computer Engineering Faculty, Hakim Sabzevari University, 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