Mostly the dynamics of controlled objects is often described by nonlinear equalizations. Last years themethodology of neural networks is engaged into designing the systems controlling such objects, in particular due to theinfluence of nonlinearities can be taken into account by nonlinear functions of the activation. Such methodology brings someintelligence to the designed system.Authors proposed the purposeful procedure of forming the structure of the neural controller according the desired lawof the control using the discrete transformation of the motion equation. Requirements to the mathematical model of thereference and method of network training are determined, and the control quality is estimated at traditional passing thedisagreement error in the controller input and for the proposed new configuration of its input circuit, namely with separatedinputs. Simulation results confirmed providing the better quality of the system control.DOI: http://dx.doi.org/10.5755/j01.itc.44.3.7717

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Synthesis methods of controllers based on the use of frequency characteristics or root hodographs are considered classic or traditional. Frequency methods are available in practical applications, and most control systems are designed based on various modifications to these methods. A distinctive feature of these methods is the so-called robustness, which means that the characteristics of a closed system are insensitive to the minor errors of the model of the real system. This feature is significant because of the complexity of constructing an accurate model of the real system, as well as the fact that many systems are inherent in all kinds of nonlinearities, which complicate their analysis and synthesis. In recent years, many attempts have been made to develop new methods of synthesis, commonly referred to as modern control theory. One synthesis method is like the root hodograph method, which allows positioning the poles of the closed-loop transfer function at predetermined points. In the article on the basis of information about the desired transient characteristic of the reference, which is obtained on the basis of a dynamic neural network, using the Ackerman formula, a procedure for calculating the coefficient matrix, whose introduction in the structure of the object model provides the specified dynamics of the process. On the base of the reference mathematical model is created the architecture of the corresponding dynamic neural network. During training, there is the target function as a numerical sequence that corresponds to the desired transient characteristic of the system, and the input signal is given in the form of a numerical sequence that reproduces jump function. Using the values of the weight coefficients obtained in the course of learning the neural network, the coefficients of the mathematical model of the reference and the roots of its characteristic equation are calculated, with the following calculation using the Ackerman formula of the coefficients of the matrix, whose values are entered into the structure of the model ensuring the specified dynamics of the process in it.

This paper presents the synthesis of a controller for robot arm servo drive by placing the poles of the transfer function. The problem of synthesis is determined, based on the desired duration of the transition process, the desired location of the roots of the characteristic equation of closed system and space state variables regulator factors are found that provide the desired system performance. There was used Ackerman’s formula for the synthesis of regulator that allows for the placement of all poles of the transfer function of a closed system at given points of the plane of the roots of the characteristic equation. Synthesis by placing poles is based on the use of model automatic control system state variables in space. As well as there is synthesized block diagram of the controller for robot arm servo drive and both held it modeling in MATLAB and moved it in Simulink environment. Due to the stated values of transition time and output signal displacement that provide the allowed divergence between output signal and sample, proposed control system works in automatic mode.

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