Name
Abstract | ||
|---|---|---|
A new implicit dual control method is proposed providing a suboptimal solution of the optimal control problem for discrete linear stochastic state space model with unknown and unobservable parameters. The solution is based on Bellman optimization recursion where two stages of optimization recursion will be pursued. The resulting controller ensures both dual properties of the suboptimal control, i.e. caution and probing. In order to be able to determine the control, the stochastic integration rule is employed for approximate evaluation of expectations. The dual control is then obtained using suitable iterative numerical algorithm. The proposed implicit dual controller is compared to the explicit dual controllers which are easier to derive but require proper tuning of design parameters. |
Year | Venue | Keywords |
|---|---|---|
2013 | Control Conference | control system synthesis,discrete systems,iterative methods,linear systems,optimisation,recursive estimation,state-space methods,stochastic systems,suboptimal control,bellman optimization recursion,design parameters,discrete linear stochastic state space model,implicit dual control method,iterative numerical algorithm,optimal control problem,optimization recursion,stochastic integration rule,suboptimal solution,vectors,optimal control,uncertainty,cost function,estimation |
Field | DocType | Citations |
Control theory,Mathematical optimization,Optimal control,Dual (category theory),Dual control theory,Linear system,Iterative method,Control theory,Mathematics,Recursion,Stochastic control | Conference | 2 |
PageRank | References | Authors |
0.42 | 4 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Flidr, M. | 1 | 2 | 0.42 |
| Simandl, M. | 2 | 2 | 0.42 |