Process modeling is one of the main directions in science and engineering. When there is a model of simple system it is possible to obtain the parameters of its state vector before a process starts. However, the modeling of complex processes (systems) applying standard methods of computing and simulation software is confronted with difficulties of chaotic dynamics of such systems. A number of models that allow to describing the dynamics of complex biological dynamic systems is extremely small, as to repeat the same results of experiments it is impossible on the basis of deterministic or stochastic models. In additional, the authors propose a model for description of human state vector through three-compartment two-cluster control system. This model may be implemented using an application package exhibiting an operation of each cluster separately. The output signals of the model seen can be compared with the actual experimental data observed as output signals. The signals obtained at the output of the simulation model show different states of the system under external control actions which cause the change in the internal properties and states due to external (disturbance) signal. Control external signal from the first cluster and accordingly the output signal from the second cluster were divided into four main components that had the same analogues in the dynamics of complex biological behavior of dynamical systems [2,4].

In the framework of the compartmentae-cluster approach there is possibility of constructing adequate mathematical models that may be of several types supposedly stationary modes of biomechanical systems: in the traditional deterministic approach, when the state vector оf the biomechanical system have equal value and in the framework of the new theory of chaos and self-organization, when system state vector x=x(t)=const. The vector can occur within a bounded volume of the phase space of states. The message signals presented arbitrary human motion under the influence of an alcoholic beverage and the simulated signals for a given external exposure control (Ud=60 у.е.) was compared. Different values ​​of the damping coefficient (b=1,1; b ´= 3,4) present the normal and unnormal state of human body. A comparison was made, the resulting figures and draw conclusions about the impact of damping coefficient on the size of the area of ​​quasi-attractor. Present the state of the biological dynamical system (the human body) under alcohol effect and in normal state.

Transition from determinism to stochastic sand further to chaos (self-organization) in the study of biomechanical systems leads to the problem of chaotic dynamics modeling of a post- ural tremor. In general, there is a problem of identifying the voluntary human movements. In other words biophysics of complex systems has approached the global challenges of voluntary and involuntary performance of any motor functions. The possibility of modeling these processes qualitatively and quantitativelyisdiscussed. Specific models demonstrate the effectiveness of the compartment-cluster modeling of biosystems and possibilities of controlof such models from the neural networks of the brain. Comparative analysis of the simulated and real recorded signals has shown a high consistent dynamics of simulated and real signals of complex biological systems. In particular, changes in tremor parameters can be described by the change in quasi-attractors which essentially depend on the mental state of a person. In experiments it is shown in the form of sight effects, which are considered in the report as a test model on experimental data.

In medicine, there are very large numbers of models of different pathological processes. Thus, models of the evolution of pathologies, in particular, in the clinic of nervous diseases absent altogether. This work presents an example of mathematical modeling the development of pathology in the human body in the form of transition from postural tremor to periodic tremor Parkinson´s and further to a rigid form. The appearance of periodicity in the characteristics of the neuromuscular system corresponds to the pathological phenomenon, for example, Parkinson´s disease. The authors note the similarity of tapping in relatively healthy person with a tremor of a patient with Parkinson´s disease from the position of the phase portraits. At high excitations from the striatum in patients with Parkinson´s disease (in models is Ш=410 u.e.) in the cluster of the neuromuscular system comes rigid phase and in the effector system there is a severe form of parkinsonism, the muscles can no longer perform any movements. In this case the timebase activity of effector organs moves in a steady mode and takes some constant value. The simulation results suggest the high consistency of the obtained results with real signals recorded by the subjects in different conditions. For various indicators of the functional systems of the human body, it is necessary to find the coefficients b and ud directionally.

Processes simulation is one of the main directions in science and technology. In the presence of a simple model of the process, the results of the process before it starts can be obtained. The simulation of complex processes (systems) within the standard methods of computing and simulation software runs into difficulties because of the chaotic dynamics of such systems. The number of models that allow to describe the complex biological processes of dynamic systems is extremely small, because it is impossible to repeat the same results of experiments based on deterministic or stochastic models. The authors propose a model that allows the description of the state vector of a person within tree compartmental two-cluster systems management. The model is implemented using the package of applied programs that demonstrate the performance of each cluster separately. On the model output signals are obtained, they are compared with real experiments and the resulting signals. Signals obtained at the output of the simulation model signals show different values of external control actions in which the change in the properties of the output signal. Control signal and the output signals respectively were divided into four main components that have the same name counterparts with complex biological dynamical systems.