Activities per year
Abstract
This paper develops a new method for computing the state feedback gain of a Linear Quadratic Regulator (LQR) with input derivative weighting that circumvents solving the Riccati equation. The additional penalty on the derivatives of the input introduces intuitively tunable weights and enables smoother control characteristics without the need of model extension. This is motivated by position controlled mechanical systems. The physical limitations of these systems are usually their velocity and acceleration rather than the position itself. The presented algorithm is based on a discretization approach to the calculus of variations and translating the original problem into a leastsquares with equality constraints problem. The control performance is analyzed using a laboratory setup of an underactuated cranelike system.
Original language  English 

Pages (fromto)  48464851 
Number of pages  6 
Journal  IFACPapersOnLine 
Volume  56.2023 
Issue number  2 
Early online date  22 Nov 2023 
DOIs  
Publication status  Published  22 Nov 2023 
Event  IFAC World Congress 2023  Yokohama, Japan Duration: 9 Jul 2023 → 14 Jul 2023 
Activities
 1 Invited talk

Direct Numerical Solution of the LQR with Input Derivative Regularization Problem
Johannes Handler (Speaker)
12 Jul 2023Activity: Talk or presentation › Invited talk