Discrete-Time Linear Model Predictive Control
| dc.contributor.advisor | Mitiku, Semu (PhD) | |
| dc.contributor.author | Tigabu, Dereje | |
| dc.date.accessioned | 2018-07-12T11:49:35Z | |
| dc.date.accessioned | 2023-11-04T12:32:22Z | |
| dc.date.available | 2018-07-12T11:49:35Z | |
| dc.date.available | 2023-11-04T12:32:22Z | |
| dc.date.issued | 2016-07-04 | |
| dc.description.abstract | Model predictive control is a form of control in which the current control action is obtained by solving on-line, at each sampling instant, a _nite horizon optimal control problem, using the current state of the plant as the initial state; the optimization yields an optimal control sequence and the _rst control in this sequence is applied to the plant. An important advantage of this type of control is its ability to cope with hard constraints on controls and states. In this project, we discuss model predictive control(MPC) schemes for discrete-time linear time-invariant state space system with and without constraints on inputs, states and outputs. The constraints on inputs, states and outputs are in the form of bounds, that can be formulated as linear inequalities. In particular, the project focus on performance criteria based on quadratic form. And also, discuss some solution techniques of discrete-time model predictive control using quadratic programming solution techniques. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/123456789/8359 | |
| dc.language.iso | en | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Discrete-Time Linear | en_US |
| dc.title | Discrete-Time Linear Model Predictive Control | en_US |
| dc.type | Thesis | en_US |