# Elements of Systems Dynamics

The set of knowledge about the possible time processes in the world of systems and the factors that affect what kind of process will occur is the content of a special section of systemology — system dynamics.

Let us try to give an overview of the main results of studying system dynamics obtained to date, discussing each of the dynamic properties in conjunction with other system properties.

## Functionality (in Conjunction with structuring, Purposefulness, and Stimulating)

A function of the system is called a dynamic process that occurs at a certain output of the system. For example, the function of a vehicle is to move some cargo in space; the function of the lamp is to light a certain space around itself; the function of the enterprise is to produce certain products (goods or services) that satisfy a particular need of society; etc. As there are a lot of outputs (connections of this system with the environment), we’re talking about the objective multifunctionality of any system.

The connection between functions and structure is that each function of the system is the cumulative result of the actions of all parts of the system, and this result depends on the structure of the links between the parts: it can be either the result of a nonlinear, emergent interaction of parts of the system (synergetic effect), or the manifestation of a linear total set of qualities of individual parts of the system (nonemergent properties, such as the total weight or the total volume of the structure consisting of parts of different weights and volumes).

The functionality property is directly related to the purposeful property. First of all, for any artificial system, some of its function is the target process for the realization of which the system is created and used. (Recall that the subjective goal is defined as the entire trajectory of the system transition from the “problem situation” to the “ultimate purpose”; see Section 2.3 in Part I.) This process is needed by the subject; but to be realized in reality, it must be an objective function of the system. This allows us to talk about any real process at the output of the system as its objective goal.

There are different ways to realize a subjective goal. Sometimes it is possible to find a natural system, the natural functions of which perfectly corresponds to our goal, and it remains only to organize its use (e.g., cow milk production is its natural function, but it coincides with one of our many subjective subgoals, and we include dairy cattle as an element in our artificial dairy production system; the same applies to natural sources of the natural resources we need, food and industrial, material and energy). However, in many cases, there is no system in nature that has the function we need in the form necessary to achieve our goal. For example, birds fly, but they cannot be harnessed, like horses, for our flying.

Sometimes there are no natural systems with the functions we need. And then we try to create an artificial system that carries out the process we need. The main difficulty lies in the fact that you cannot implement any process that you just imagine to be wanted. Only subjective goals that do not contradict the laws of nature, that is, can become the objective goal of the system created by you, are achievable.

Another striking manifestation of the relationship of functionality, purposefulness, and stimulation is the management process. Even after creating the necessary artificial system and launching it into action, we are faced with the fact that the system works in an ever-changing environment. All the factors involved in the operation of the system change, and some of them can go out of the range of values allowed for the normal functioning of the system. Such factors become limiting and take away the real trajectory of the system from the target trajectory. This requires intervention, measures to overcome the difficulty, and returning the system to achievement of the goal; such actions are called system governance. Different limiting factors require different actions to overcome them, which results in the presence of different types of control with specific algorithms (see Section 4.3 in Part I).