Internal Model Control

An Internal Model Control is a Process Model in which the controller is a model-based system.

• AKA: Model-based Control, IMC.
• Example(s):
  • Forward Model Control,
  • Inverser Mocel Control.
  • …
• Counter-Example(s):
  • Classical Model Control,
  • Open Loop Control.
• See: Certainty Equivalence Principle, Control Theory, System Dynamics, Control Engineering, Feedback Control, Process with Deadtime, Dahlin Controller, Internal Model Principle, Adaptive Control Theory.

---

---

References

2018

• (Wikipedia, 2018) ⇒ https://en.wikipedia.org/wiki/Internal_model_(motor_control) Retrieved:2018-7-15.
  • In the subject area of control theory, an internal model is a process that simulates the response of the system in order to estimate the outcome of a system disturbance. The internal model principle was first articulated in 1976 by B. A. Francis and W. M. Wonham as an explicit formulation of the Conant and Ashby good regulator theorem. It stands in contrast to classical control, in that the classical feedback loop fails to explicitly model the controlled system (although the classical controller may contain an implicit model).

    The internal model theory of motor control argues that the motor system is controlled by the constant interactions of the “plant” and the “controller.” The plant is the body part being controlled, while the internal model itself is considered part of the controller. Information from the controller, such as information from the central nervous system (CNS), feedback information, and the efference copy, is sent to the plant which moves accordingly.

    Internal models can be controlled through either feed-forward or feedback control. Feed-forward control computes its input into a system using only the current state and its model of the system. It does not use feedback, so it cannot correct for errors in its control. In feedback control, some of the output of the system can be fed back into the system’s input, and the system is then able to make adjustments or compensate for errors from its desired output. Two primary types of internal models have been proposed: forward models and inverse models. In simulations, models can be combined together to solve more complex movement tasks.

2017

• (Sammut & Webb, 2017) ⇒ Claude Sammut, and Geoffrey I. Webb. (2017). "Internal Model Control". In: (Sammut & Webb, 2017). DOI:10.1007/978-1-4899-7687-1, Online ISBN: 978-1-4899-7687-1, Print ISBN: 978-1-4899-7685-7
  • QUOTE: Many advanced controllers for nonlinear systems require knowledge of the model of the dynamics of the system to be controlled. The system dynamics is often called an “internal model,” and the resulting controller is model-based. If the model is not known, it can be learned with function approximation techniques. The learned model is subsequently used as if it were correct in order to synthesize a controller – the control literature calls this assumption the “certainty equivalence principle.”

2002

• (Tham,2002) ⇒ Ming T. Tham (2002). "Internal Model Control". In: Lectures on Introduction to Robust Control.
  • QUOTE: In practice, however, process-model mismatch is common; the process model may not be invertible and the system is often affected by unknown disturbances. Thus the above open loop control arrangement will not be able to maintain output at setpoint. Nevertheless,forms the basis for the development of a control strategy that has the potential to achieve perfect control. This strategy, known as Internal Model Control (IMC) has the general structure depicted in Fig. 1.

---