Stability is something we all need in our lives .You may
have a different perspectives about what exactly meant by being in a stable
state but we all have some common aspects about it. In control systems
engineering it’s essential to have a stable system otherwise the system will be
impractical to setup in real world no matter how elegant is your design. When
we are talking about the stability of a control system it corresponds the
ability of a system to produce bounded output signals to bounded input signals.
When we are talking about bounded signal I would think it as a signal with a
finite energy (magnitude).When I first learn about BIBO systems (Bounded Input
Bounded Output) I always had a confusion what is actually meant by bounded in
real case, especially with the impulse signal .The definition tells us that it
has an infinite magnitude at t=0 (when the duration is close to zero) so I
wondered how could be the impulse signal is bounded signal but if we relate it
to real world cases we can see this concept can model lots of forces like
impulse force which acts on a body for a very short time and has a very high
magnitude compared to a conventional force . Impulse signals always have a
finite energy therefore I consider a bounded signal means the signal has a
finite amount of energy, It can’t be infinite. So if a system is a BIBO system
it will not produce an unbounded signal to a bounded signal. we only consider
about BIBO systems. As well as that, all the systems we consider are LTI system
(Linear Time invariant signals) which means that there is only single output to
a single input(one to one relation) for all t and if a system has an output
value other than zero at t=0 the system is not considered as a linear in
control system. Time invariant means the system will produce the same output
regardless of the time difference if the inputs and the initial conditions are
identical in two instances. I mentioned those concepts here although they are
not relevant here since we talk about LTI, BIBO system only.
Before I proceed to talk about the stability of a system it
may be good to explain few things about a typical control system. Most of the
time all the analysis of control systems are done using transfer functions of
real system. Laplace transformation converts all the time varying functions to
frequency varying functions in complex domain(s domain) and this transformation
make the analysis very easy to carry out. The following diagram shows a typical
block diagram of a control system.
Plant: Plant is the system we need to control described as a
transfer function(s domain). It would be any physical system and several very
different physical systems can be modelled using the same transfer function.
Sensor: The sensor component measures the value of an output
specified by the design and sends it as a feedback to the controller.
Controller: Controller
is a computing device (A computer) that compares the sensor output and
reference provided as the input to the system and generates control signals to
Actuator using PLCs.
Actuator: A device or a mechanism that controls the plant in
a desired manner.
Now back to stability,
having a stable system is a good and
essential thing in control engineering but finding the perfect stable state for
a given system will be impossible since we can’t predict how the system will be
behaving in future. Any physical system change it’s qualities with time and
these changes might cause the system to behave in an unpredictable manner. For
example, a motor will not output it desired torque after some years due to
mechanical ware and a motor control system might behave unexpectedly if this
doesn’t take into account. Therefore rather than using just one stable state
engineers design the system with stability margins. So system will be able to
handle small parameter changes to input.
This helps to tackle any unpredictability in system and makes it more
robust.
How do we determine the stability of a system? The method is
easy to understand but very hard to do it without using a computer most of the time. It’s not that difficult to
determine the stability nowadays with the help of advanced computer softwares like
MATLAB. But before the arrival of computers people had to find methods to
determine the stability of a system by hand. Few methods are listed below. I’m
hoping to discuss these topics in future. Each of this method has it’s own pros
and cons and becomes handy according the problem you are dealing with. Although using computer programs are the
wildly used method in control engineering, an engineer should have an in depth
knowledge about those methods in order to understand and interpret the results.
- · Root locus method.
- · Bode Plots.
- · Nyquist plots.
- · Routh-Hurwitz criterion.
Determining the stability
As I mentioned above in order to assess the stability of a
system all we have to know is whether the poles of the system (closed loop) is
located at the right or left side of s plane. If all the poles are located in left half
plane then the system will be stable.
If a single pole is located on right half s plane then the system will be unstable.
Furthermore if there is at least single multipole on the imaginary axis the system will be unstable.
If there is at least single pole on the imaginary axis then the system is said to be critically stable. It’s on the verge of being unstable.
If a single pole is located on right half s plane then the system will be unstable.
Furthermore if there is at least single multipole on the imaginary axis the system will be unstable.
If there is at least single pole on the imaginary axis then the system is said to be critically stable. It’s on the verge of being unstable.
Let’s take a simple example .Let G(s) = N(s)/P(s) =
1/(s+2)(s+3) . G(s) is the open loop transfer function . So the poles of the
system are -2 and -3. And these values(poles ) are negative and therefore they
are located on left half plane of s plane. Therefore the system will be stable.
If we convert into time domain this result will be obvious.
By taking partial fractions of G(s), G(s) = 1/(s+2)- 1/(s+3)
And By taking Laplace inverse of G(s) , g(t)= exp(-2t)-exp(-3t).
So it is obvious
when t goes to infinity g(t) will decay in an exponential manner. Therefore
this system will be a stable system. But instead of the system poles were +2
and +3 then g(t) = exp(2t)-exp(3t) and when t goes to infinity t this system
will produce unbounded (infinite)results, which cause malfunctions in a
realistic system.
If above system (g(t)) was connected to a unity feedback
system , the system’s new transfer function will be H(s)=G(s)/1+G(s) and all we
have to do is to solve the denominator for roots and the roots will be new
poles of the system. This 1+G(s) =0 Is called the characteristic equation of
the system since it will determine the stability of the system.
In conclusion it is very important to know whether a system
will be able to stabilize itself and fortunately there are many tools we can
use to verify the stability and the stability margins of the systems. It is an essential
aspect in Control engineering .