TY - GEN
T1 - Stable model predictive control of fuzzy affine systems with input and state constraints
AU - Zhang, Tiejun
AU - Feng, Gang
AU - Lu, Jianhong
PY - 2007
Y1 - 2007
N2 - In this paper, a fuzzy affine model, which is more capable of representing strongly nonlinear dynamics, is used for predictive controller design. Based on piecewise quadratic Lyapunov functions, the proposed fuzzy affine model predictive control approach can ensure both the closed-loop system stability and the satisfactory transient control performance even under input and state constraints. With the help of partitioned degenerate ellipsoids and S-procedure, the large terminal invariant set of a fuzzy affine system can be achieved offline by solving a convex semi-definite programming problem subject to some linear matrix inequalities, rather than the non-convex bilinear matrix inequalities as in conventional fuzzy affine model based control. Then with the associated terminal cost, the resulting online open-loop predictive control approach can be formulated as a standard quadratic programming problem, which is readily solvable. Simulation results have demonstrated the performance of the proposed approach. © 2007 IEEE.
AB - In this paper, a fuzzy affine model, which is more capable of representing strongly nonlinear dynamics, is used for predictive controller design. Based on piecewise quadratic Lyapunov functions, the proposed fuzzy affine model predictive control approach can ensure both the closed-loop system stability and the satisfactory transient control performance even under input and state constraints. With the help of partitioned degenerate ellipsoids and S-procedure, the large terminal invariant set of a fuzzy affine system can be achieved offline by solving a convex semi-definite programming problem subject to some linear matrix inequalities, rather than the non-convex bilinear matrix inequalities as in conventional fuzzy affine model based control. Then with the associated terminal cost, the resulting online open-loop predictive control approach can be formulated as a standard quadratic programming problem, which is readily solvable. Simulation results have demonstrated the performance of the proposed approach. © 2007 IEEE.
UR - http://www.scopus.com/inward/record.url?scp=50249090337&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-50249090337&origin=recordpage
U2 - 10.1109/FUZZY.2007.4295357
DO - 10.1109/FUZZY.2007.4295357
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 1424412102
SN - 9781424412105
BT - IEEE International Conference on Fuzzy Systems
T2 - 2007 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2007)
Y2 - 23 July 2007 through 26 July 2007
ER -