|
|
 |
|
Viewing report
|
|
|
|
EFFICIENT ROBUST MODEL PREDICTIVE CONTROL VIA CONVEX
OPTIMIZATION. Edition No. 1
VDM Publishing House, Dec 2008, Pages: 160
This research monograph develops a systematic
approach to synthesize efficient robust MPC for
constrained LTV systems and nonlinear systems.
Specifically,
(a) by using the concept of invariant sets,
robustness is achieved without online computation;
(b) by using a two-level control structure,
optimization is separated from stabilization;
(c) by constructing a continuum of terminal sets,
both large operating regions and local optimality
can be achieved without large number of control
decision variables;
(d) by decomposing a nonlinear control problem into
a sequence of linear control problems, a nonlinear
non-convex optimization problem is reduced to a
convex optimization problem.
Algorithms developed in this monograph have been
formulated into linear objective minimisations
subject to linear matrix inequality constraints.
This optimization is convex and can be solved
efficiently using interior point methods. Since
state and decision variables appear linearly in the
objective function and the matrix inequality
constraints, linear combination of off-line MPC
solutions provides a feasible solution, which can
potentially replace online optimization in MPC.
|
|
|
|
