In　order　to　reduce　the　computational　burden　effectively　and　ensure　that　the　system　has　good　control　performance,　an　event-driven　near-optimal　control　algorithm　is　developed　for　discrete-time　nonlinear　systems　with　input　constraints.　A　single　network　adaptive　critic　algorithm　is　adopted　to　address　the　constrained　optimal　control　problem.　First,　the　optimal　cost　function　and　the　optimal　control　strategy　are　obtained　theoretically　through　the　iterative　algorithm.　Then,　an　appropriate　triggering　threshold　is　established,　so　that　the　system　satisfies　the　event-driven　mechanism.　In　addition,　the　action　network　of　classical　adaptive　dynamic　programming　is　omitted.　The　derivative　of　the　approximate　cost　function　is　the　output　of　the　critic　network　and　then　is　used　to　obtain　the　approximate　optimal　control　law.　Furthermore,　the　convergence　analysis　of　the　iterative　algorithm　is　proved.　Finally,　a　simulation　example　is　conducted　to　verify　the　effectiveness　of　the　proposed　scheme.