Name
Title | ||
|---|---|---|
Event-triggered optimal control of nonlinear continuous-time systems in affine form by using neural networks |
Abstract | ||
|---|---|---|
The proposed event-triggered control design uses the adaptive dynamic programming (ADP) technique to solve the infinite-horizon optimal control of nonlinear continuous time system in affine form with complete unknown system dynamics in a forward time and online manner. The approximation property of the neural network (NN) is used to estimate the system dynamics and the value function with event-based sampling of state vector. Subsequently the estimated values are used to design the near optimal control policy. In addition, the NN weights are updated as a jump at every trigger instant, hence aperiodic in nature, to save computation when compared to the traditional NN-based approaches. Further, the closed-loop dynamics are formulated as a nonlinear impulsive dynamical system and the extension of the Lyapunov technique is utilized to prove the locally ultimate boundedness of all the closed-loop signals by deriving an adaptive event-trigger condition. Nonetheless, a positive lower bound on the inter-event time is guaranteed to avoid accumulation point. Finally, the analytical design is evaluated by using an example. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CDC.2014.7039549 | Decision and Control |
Keywords | Field | DocType |
Lyapunov methods,adaptive control,closed loop systems,continuous time systems,control system synthesis,dynamic programming,infinite horizon,neurocontrollers,nonlinear control systems,nonlinear dynamical systems,optimal control,ADP technique,Lyapunov technique,NN weights,adaptive dynamic programming,adaptive event-trigger condition,affine form,approximation property,closed-loop dynamics,closed-loop signals,event-based sampling,event-triggered control design,event-triggered optimal control,infinite-horizon optimal control,inter-event time,neural network,nonlinear continuous time system,nonlinear impulsive dynamical system,optimal control policy,state vector,ultimate boundedness,unknown system dynamics,value function | Affine transformation,Lyapunov function,Mathematical optimization,State vector,Nonlinear system,Optimal control,Computer science,Control theory,System dynamics,Variable structure control,Sliding mode control | Conference |
ISSN | Citations | PageRank |
0743-1546 | 3 | 0.37 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Avimanyu Sahoo | 1 | 155 | 10.66 |
| Hao Xu | 2 | 214 | 14.63 |
| Sarangapani Jagannathan | 3 | 1136 | 94.89 |
| Travis Dierks | 4 | 397 | 23.62 |