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An independent design of adaptive multiloop fractional order internal model control based PID (FOIMC-PID) controller for a two input two output process (TITO) is presented.
This paper presents an Internal Model Control based structure to realise fault tolerance towards sensor faults.
The internal model control based strategy is used to improve robustness for communication delays of the secondary level.
An encouraging aspect of the proposed scheme is that for globally exponentially stable systems, a particularly simple choice of anti-windup compensator exists and, moreover, this could be regarded as a "nonlinear„ internal model control based anti-windup compensator.
The control designs are (1) feedback linearization with measured outputs, (2) gain-scheduling IMC (internal model control) based on identified model, (3) PI control with an adaptive gain based on a static gain model, and (4) state feedback with state estimation by a nonlinear high-gain observer.
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The IMC (Internal Model Control) controller based on robust tuning can improve the robustness and dynamic performance of the system.
This paper presents the modeling and model predictive control based on state-space model of the air jet texturing and twisting machine.
Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system.
Two control architectures, model predictive control based on ULN model and single neuron PID (SN-PID) controller based on ULN predictor, are designed to control pH neutralization process, respectively.
An approach to reconfigurable distributed model predictive control based on reconfigurable controller dissipativity properties is developed.
The comparable perturbation to a model applying control based, for example, upon a specific target copy number would be to vary the value of this target.
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