The study divides the analysis of monitoring and diagnostic information, leaving for monitoring the parameters of the stationary process, and for diagnostics -various transient regimes in the technological process. This, in turn, divides the algorithms of information processing into control of the output from the given boundaries for stationary parameters and the classification and prediction for dynamically changing parameters in a multidimensional space. In view of the large number of monitoring and diagnostic information, as well as due to different algorithms for processing it in an appropriate information system, it is necessary to apply multi-dimensional analysis methods. As diagnostic influences, various jumplike changes of a "natural character" are used, and the state of the equipment allows judging the apparatus of the influence functions. The abrupt changes in the technological process are reflected in the change in its parameters. The reaction to them is weakened as they are removed in accordance with the influence functions. The values of the parameters at the moment of the reaction define a point in the multidimensional parameter space and allow one to relate the state to one or another standard, and to relate the corresponding management algorithm to the standard. The experimental model includes five links simulating the operations of the technological process, a pulsed signal source simulating a step change and five links of propagation delay simulating the duration of operations. The results confirmed theoretical conclusions about the influence functions.

The study is devoted to the theoretical justification of procedures and algorithms for managing the quality of products. The methods to control the abstract object are used. Since the object itself, for example, quality is a reflection from the material carrier: products and the production process, control and disturbing influences are attached to them. Control actions are divided into three types: parametric, structural and organizational. The first two types are associated with the flow of technological processes, and due to the application of managing organizational influences, the necessary external and internal conditions are achieved that increase the quality of products. It is shown that even a simple linear formulation allows us to pose and solve the optimal control problem and obtain practically important results.

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The paper investigates the integration problems neural networks sections allocated in accordance with the functions performed. As an initial example, we study two trained neural matrices, one of which performs the function of recognizing the position of the manipulator and its speed, and the second generates responses using the corresponding robot drives. In addition to training mechanisms based on the adjustment of transfer weights, the mechanisms based on the supply of excitation / inhibition waves from the edges of the neural network are also affected. At the same time, training is reduced to multiple forced guiding of the robot manipulator along the target path, during which the desired paths of beatings are automatically found using comparators. The matrices are trained separately and then joined using a standard signal generated by a special unit. The division of the neural network into two sections allows building the necessary logic between them. This hybridization significantly expands the range of tasks. As a test problem, the task of searching for a given part from a jointly located set of parts in general position was selected. At the same time, the control system finds a given part, rotates its predetermined model until a matching image is obtained, and thereby understanding how the part is located and how best to capture it occurs.