Skip to content
Hub Nexus

No author yetClaim it

Version 1Updated 1 min read

Support

Adaptive Controllers

What we've been studying up till this point are fixed systems, that is systems that do not change over time. However, real-world applications and experience tells us that the environment can change over time: New noise can be added to a signal, the signal quality can be degraded, or the specifications of the signals can be changed at the source.

There is a distinct need then for controllers which can modify themselves to produce the same output regardless of changes to the input. Herein lies the problem of adaptive control. We will introduce some of the concepts in this chapter, and discuss them in greater detail in future chapters.

This page of the Control Systems book is a stub. You can help by expanding this page, but make sure to follow the local manual of style. If you would like to help, but you don't know how, you can ask on the main discussion page. (All Stubs)

Where this page came from

This page was imported from Wikibooks. From “Control Systems” on Wikibooks, by its contributors, under CC BY-SA 4.0. Changed here: set as a page; navigation and edit links left out; each image under its own licence, credited in its caption.

Nobody has written it yet — it is the source material at a new address, which is why search engines are asked to skip it and why no one earns from it. It is up for grabs: take it on, and it is yours to rewrite and to earn from.

Comments

Spinner Logo

Next in Control Systems

CC BY-SA 4.0
Control Systems, State Machines
CC BY-SA 4.0
We can define them recursively as such: ${x}_{n} ( t ) = {x}_{0} + {∫}_{{t}_{0}}^{t} f ( τ , {x}_{n − 1} ( τ ) ) d τ$ ${x}_{1} ( t ) = {x}_{0}$ We can show that the following relationship is true: $x ( t ) = {lim}_{n → ∞} {x}_{n} ( t )$ The xn series of equations will converge on the solution to the
CC BY-SA 4.0
There are some nonlinearities that happen so frequently in physical systems that they are called "Common nonlinearities". These common nonlinearities include Hysteresis, Backlash, and Dead-zone. ## Hysteresis Continuing with the example of a household thermostat, let's say that your thermostat is se
CC BY-SA 4.0
- The two inputs may act on the system in completely different ways. As we will show in the next example, it is frequently a good idea to consider the noise and the control inputs separately: **Example:** Consider a moving automobile. The control signals for the automobile consist of acceleration (g
CC BY-SA 4.0
Notice that we set our start time t0 = kT, because we are only interested in the behavior of our system during a single sample period: $u ( t ) = u ( k T ) , k T ≤ t ≤ ( k + 1 ) T$ $x ( t ) = Φ ( t , k T ) x ( k T ) + {∫}_{k T}^{t} Φ ( t , τ ) B d τ u ( k T )$ We were able to remove u(kT) from the i
CC BY-SA 4.0
Other delays however, such as synchronization delays, are an integral part of a system. This chapter will talk about how delays are utilized and represented in the Laplace Domain. Once we represent a delay in the Laplace domain, it is an easy matter, through change of variables, to express delays in