TY  - CHAP
T2  - Proceedings of the 19th IFAC World Congress
EP  - 2926
N1  - 19th IFAC World Congress, August 24-29, 2014, Cape Town, South Africa
ID  - eprints2328
UR  - http://www.ifac-papersonline.net/Detailed/66145.html
AV  - public
TI  - Fixed-point implementation of a proximal Newton method for embedded model predictive control (I)
Y1  - 2014/08//
KW  - Identification and control methods; Cyber-Physical Systems
N2  - Extending the success of model predictive control (MPC) technologies in embedded applications heavily depends on the capability of improving quadratic programming (QP) solvers. Improvements can be done in two directions: better algorithms that reduce the number of arithmetic operations required to compute a solution, and more efficient architectures in terms of speed, power consumption, memory occupancy and cost. This paper proposes a fixed point implementation of a proximal Newton method to solve optimization problems arising in input-constrained MPC. The main advantages of the algorithm are its fast asymptotic convergence rate and its relatively low computational cost per iteration since it the solution of a small linear system is required. A detailed analysis on the effects of quantization errors is presented, showing the robustness of the algorithm with respect to finite-precision computations. A hardware implementation with specific optimizations to minimize computation times and memory footprint is also described, demonstrating the viability of low-cost, low-power controllers for high-bandwidth MPC applications. The algorithm is shown to be very effective for embedded MPC applications through a number of simulation experiments. 
SP  - 2921
A1  - Guiggiani, Alberto
A1  - Patrinos, Panagiotis
A1  - Bemporad, Alberto
SN  - 978-3-902823-62-5
PB  - IFAC
ER  -