Control Systems

Key Causes of Uncertainty in Control Systems

One of the objectives of a control system is to achieve good plant performance in the face of uncertainty. The major sources of uncertainty in control are:

  • Unmeasurable perturbations
  • Modelling errors
Key Causes of Uncertainty in Control Systems

Unmeasurable Perturbations

Unmeasurable perturbations produce output deviations. With a controller in place, the achieved deviations must be below a user-defined bound.

Modelling Errors

Modelling errors can be classified into three categories:

  • Parameter uncertainty
  • Unmodeled dynamics
  • Non-linearity

Parameter Uncertainty

Parameter uncertainty originated by uncertainty in physical parameters. Parameter uncertainty may be accommodated with high-gain regulators in some instances.

Unmodeled Dynamics

Unmodelled dynamics i.e. neglected delays and fast time constants. The order of real plants is infinite (partial differential equations) and lumped parameter models are only approximations. In most cases, these approximations are intentionally made to keep the problem traceable. For example:

  • Multi-loop control disregards the non-diagonal terms in tuning each loop. The cross-coupling is a modelling error that should be appropriately withstood.
  • Low-order models are typically used to avoid modelling cost. For instance, modelling a distillation column with experimental first-order and delay models, instead of a detailed one based on thermodynamics, etc.

Non-linearity

Linear regulators must be at least robust to smooth non-linearities on the process. As a matter of fact, practical requirements usually require appropriate behaviour in the face of non-smooth non-linearities like hysteresis or backlash that occur mostly with valves and other mechanical actuators.

Take note of the fact that, modelling errors can change with time, due to plant aging or component replacement; significant modelling errors need to be considered in time ahead irrespective of the initial effort devoted to modelling.

John Mulindi

John Mulindi is an Industrial Instrumentation and Control Professional with a wide range of experience in electrical and electronics, process measurement, control systems and automation. In free time he spends time reading, taking adventure walks and watching football.

View Comments

Recent Posts

The Problems Associated with Embedded Power Generation

Image source Pixabay The rate of the development of energy sources that are alternatives to…

7 hours ago

The Power of Automation in Construction: How It Transforms Efficiency and Safety

Image by Pixabay Automation is transforming industries worldwide, and construction is no exception. Companies are…

1 day ago

LED Beacon Lights: What Does Each Colour Lens Mean?

A closeup shot of a warning lamp in the street at night, image by Freepik…

2 days ago

Impeller Flowmeters: Features, Installation Considerations & Uses

Impeller flowmeters at times referred to as paddlewheel meters are one of the frequently utilized…

6 days ago

Sell Old Electronics: Turn Your Used Devices into Cash

Photo by Héctor Martínez on Unsplash Introduction Yes! If you have old electronic devices that you…

1 week ago

The Effects of Low Power Factor on Electrical Equipment

The cosine of the angle between voltage and current in an AC circuit is referred…

1 week ago