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The paper proposes a multiple models based control scheme for the solution of the tracking problem for mobile robots.
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The methods are motivated by the desire to guarantee integral controllability in model based control designs such as model predictive control (MPC).
Further, the results of the RBFNMPC is compared with similar RBFN model based control strategies and also with well tuned PID/PI controller.
This controller is designed following the Parallel distributed compensation (PDC) technique, employed for Takagi Sugeno (TS) fuzzy model based control systems, and is termed as a mixed H2/LMI controller.
Then, a multiple-model based control scheme is developed to compensate for actuator failures, consisting of a kinematic controller, multiple dynamic controllers and a control switching mechanism.
Nonlinear control with feedforward neural networks is usually designed by means of model based control strategies, which make explicit use of (direct or inverse) models of the controlled system.
This is achieved with increasing utilisation of model based control.
For efficient bioprocess control it is essential to use advanced model based control strategies.
This model is then used for model based control using internal model control (IMC).
The success of model based control of chemical processes is dependent on good process models.
Advanced model based control algorithms are often used for providing improved control of complex systems.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com