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The controller is designed to be valid for the possible largest uncertain plant set while accomplishing the performance and control input constrains.
In this work we show that the anti-wind-up-bumpless-transfer controller emerges from the structure of model predictive control (MPC) with quadratic objective and input constrains.
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This paper proposes the design of anti-windup compensator gain for stability of actuator input constrained state delay systems using constrained pole-position of the closed-loop.
Then the state and input constrained optimal control problem is directly converted into a standard TPBVP without constraints.
In the input constrained case, the proposed indirect method gives more accurate solution with much faster convergence speed.
This paper discusses an on-line approach to Model Predictive Control (MPC) of input constrained linear systems.
A systematic approach to anti-windup synthesis based on the internal model control structure is proposed for open loop stable input constrained multivariable plants.
Based on this model, the input constrained point-to-point quasi-time-optimal control problem is formulated and the resulting two-point boundary value problem is numerically solved.
We present a method for the synthesis of a control law for input constrained linear systems that incorporates both a traditional linear output-feedback controller as well as a static anti-windup compensator.
From the results here obtained when only an average-power constraint is imposed, investigating the impact of an input constrained in both its average and its peak power as well as misalignment fading on the system model here proposed for representing OOK signaling is an interesting topic for future research.
The stability analysis subject to the effect of input saturation constrains are conducted with the help of an auxiliary design system based on the Lyapunov Krasovskii method.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com