Simulation results show that the designed FMPC has the best performance, and control performance can be guaranteed in a real-time environment.
The first class [24,25] requires a centralized controller to make the scheduling decisions and focuses on developing scheduling algorithms whose stability can be guaranteed in a fraction of the capacity region.
The advantage of the algorithm is that strong convergence of iterative sequences can be guaranteed in a reflexive, strictly convex, and smooth Banach space such that both E and E ∗ have the Kadec-Klee property without any compact assumptions.
A moving sliding function is adopted on the control design, the input can thus be confined within a predefined boundary during transient period, while a robust performance can be guaranteed in the steady state.
This paper demonstrates that, unlike in AC grids, convergence and uniqueness of the solution can be guaranteed in this type of grid under well defined practical considerations.
It has been shown that system-tracking stability can be guaranteed in the closed-loop system irrespective of whether uncertainties occur or not.
It is shown that with the proposed controller global stability of the overall system and perfect regulation can be guaranteed in the presence of these interactions.
In addition, by incorporating the multiplicative uncertainty model in the decoupled subsystem, the robust stability margin of system against uncertainties such as various load changes, system parameters variations etc., can be guaranteed in terms of the multiplicative stability margin (MSM).
The adaptive learning rates are derived in the sense of discrete-type Lyapunov stability theorem, so that the convergence of the tracking error can be guaranteed in the closed-loop system.
All adaptive learning algorithms in the SMNN control system are derived from the sense of Lyapunov stability analysis, so that system-tracking stability can be guaranteed in the closed-loop system whether the uncertainties occur or not.
It is shown that the reachabilities of the proposed sliding mode surfaces can be guaranteed in both the state estimate space and the estimation error space simultaneously under the designed control schemes.
