Sökning: "Daniel Axehill"
Visar resultat 1 - 5 av 19 avhandlingar innehållade orden Daniel Axehill.
1. On Complexity Certification of Active-Set QP Methods with Applications to Linear MPC
Sammanfattning : In model predictive control (MPC) an optimization problem has to be solved at each time step, which in real-time applications makes it important to solve these efficiently and to have good upper bounds on worst-case solution time. Often for linear MPC problems, the optimization problem in question is a quadratic program (QP) that depends on parameters such as system states and reference signals. LÄS MER
2. Real-Time Certified MPC : Reliable Active-Set QP Solvers
Sammanfattning : In Model Predictive Control (MPC), optimization problems are solved recurrently to produce control actions. When MPC is used in real time to control safety-critical systems, it is important to solve these optimization problems with guarantees on the worst-case execution time. LÄS MER
3. Applications of Integer Quadratic Programming in Control and Communication
Sammanfattning : The main topic of this thesis is integer quadratic programming with applications to problems arising in the areas of automatic control and communication. One of the most widespread modern control principles is the discrete-time method Model Predictive Control (MPC). LÄS MER
4. Integer Quadratic Programming for Control and Communication
Sammanfattning : The main topic of this thesis is integer quadratic programming with applications to problems arising in the areas of automatic control and communication. One of the most widespread modern control methods is Model Predictive Control (MPC). In each sampling time, MPC requires the solution of a Quadratic Programming (QP) problem. LÄS MER
5. Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments
Sammanfattning : During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the development of systems such as self-driving cars, unmanned aerial vehicles and robotic manipulators. LÄS MER
