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M. Killian, B. Mayer, A. Schirrer, M. Kozek:
"Cooperative Fuzzy Model Predictive Control";
IEEE Transactions on Fuzzy Systems, 24 (2016), 2; 471 - 482.

In this paper a cooperative fuzzy model predictive
control (CFMPC) is presented. The overall non-linear plant is
assumed to consist of several parallel input-coupled Takagi-
Sugeno (TS) fuzzy models. Each such TS-fuzzy subsystem is
represented in the form of a local linear model network (LLMN).
The control of each local linear model (LLM) in each LLMN is
realized by model predictive control (MPC). For each LLMN
the outputs of the associated MPCs are blended by the fuzzy
membership functions, which leads to a fuzzy model predictive
controller (FMPC). The resulting structure is one FMPC for each
LLMN-subsystem. Overall, a parallel combination of FMPCs
results, which mutually affects all LLMN-subsystems by their
respective manipulated variables. To compensate detrimental
cross-couplings in this setup, a cooperation between the FMPCs
is introduced. For this cooperation, convergence is proven and
for the closed-loop system a stability proof is given. It is
demonstrated in a simulation example that the proposed inputconstraint CFMPC algorithm achieves convergence of the fuzzy
LLMNs within few cooperative iteration steps. Simulations are
given to demonstrate the effectiveness of the theoretical results.

cooperative MPC, fuzzy MPC, fuzzy control, stability, Takagi-Sugeno model.

http://dx.doi.org/10.1109/TFUZZ.2015.2463674

Project Head Martin Kozek:
Robuste Prädiktive Regelstrategien zur Optimierung des Energieeinsatzes in Gebäuden