Intelligent electric drive of shut-off valves based on the ESD-VTG control unit. Intelligent control systems for electric drives: mathematical methods and some approaches for their implementation in practice Is a drill an intelligent drive?

Drawing. Electronic control unit EP shut-off and control valves ESD-VT G

Currently, there is a significant need for modernization of electric drives (ED) of shut-off valves for general industrial use. In 2007, for these purposes, the EleSy company released a series of electronic units ESD-VTG (Fig. 1), designed to control electronic shut-off and control valves of various types (slide and wedge valves, Ball Valves, butterfly valves, etc.).

The new control unit was initially developed to modernize the previously used ES shut-off valves, which had a short resource on the part of the elements of the cam mechanism for setting electromechanical travel microswitches. The technology for adjusting and setting up limit switches is also extremely inconvenient from an operational point of view, requiring opening the switch cover, as well as manually setting the cams and pointer arrow. The accuracy of setting up such electronic devices is low, and their integration into a modern process control system with digital interfaces is problematic. In a modernized electric drive new block control is installed to replace the old one. Wherein:

it becomes possible to integrate the electric drive into the process control system via the RS-485 serial interface;
when the ED is equipped with an electronic position sensor, which ensures high positioning accuracy, it is possible to quickly adjust the final positions of the valve shut-off element in various ways, including without turning on the engine and moving the valve shut-off element;
The electric drive is equipped with an electronic two-way torque limiting clutch; this coupling provides the ability to work “on the stop” with a given torque, identification of the drive torque when moving based on the values of the motor currents and network voltage, as well as setting different values for limiting the torque depending on the direction of movement of the electric drive and the position of the shut-off element;
The unit independently provides the entire necessary set of algorithms for protecting the motor and valves, eliminating the need to install complex external relay systems.

It should be noted that the electronic sensor allows you to control the position of the output link of the electric drive, including in the absence of mains voltage, and does not require a battery to operate in this mode. The ED on the valve is configured without penetrating inside the unit by setting parameters in the configuration registers from the local control station using control buttons or an infrared control panel.

A developed hierarchical menu system, an intuitive verbal description of parameters in Russian, displayed on an alphanumeric two-line display, make setup as easy as using a mobile phone. The electronic unit monitors the input parameters against exceeding the maximum limit and incorrect settings.

During the setup process, it is possible to additionally set the operating algorithm of the electric drive, the values of the torque limit values depending on the position of the valve shut-off element, block the algorithms of selected protections, configure remote input/output according to a user-specified algorithm. It is also possible to set such a mode for setting the limit switches in which you need to move the shut-off valve. It is possible to set stop modes upon reaching the limit compaction or a specified end position, as well as a “shock” torque mode when starting to open.

The unit has an event logging system that tracks and stores in non-volatile memory commands, accidents and ED states (the last 300 events) indicating the time stamp of occurrence. The information recorded by this system allows you to restore the causes of problem situations.

The unit has an RS-485 interface operating using the ModBus RTU protocol. The discrete interface allows you to send commands “Close”, “Open”, “Stop” using 220 AC or 24 DC voltage signals. The time of the response signal is set in the configuration registers of the block. The electronic device produces discrete signals about the valve position “Open”, “Closed”, etc.

As an option for electronic control units, the consumer can purchase an infrared remote control to configure the unit and read the data stored in it: the event log and settings parameters. Using a remote control with two-way exchange allows you to transfer a configuration parameter file prepared on a personal computer to electronic devices installed on site, thereby reducing setup time. By reading the unit's event log using the remote control, it can be visualized on the computer screen to assess the activities of maintenance personnel and the correct operation of the electronics, the state of the electrical network, etc. The event log file can be sent via a personal computer connected to the Internet to the EleSy service department to receive advice on problem situations.

A thyristor voltage regulator (TVR) is used as a power switch in the unit, which determines the small dimensions, high reliability and low cost of the electric power supply.

The unit as part of a thyristor asynchronous electric drive performs the following functions: y protection against short circuit currents; y limiting motor currents to the maximum permissible level; y thermal protection of the motor from overload; y formation of starting torque impulses necessary to overcome the forces of dry friction, jamming, etc.; y limiting the moment in motion, which helps prevent failure of the mechanical elements of the electric drive; y work on emphasis while maintaining a given moment.

Meeting these requirements in the TRN-AD system is complicated by the semi-controlled nature of the thyristors, the non-sinusoidal distortion of the motor stator currents and the lack of torque control methods by adjusting the opening angle of the thyristors.

EP can be used Various types gearboxes. The requirements regarding the torque limitations of the electric drive are fulfilled taking into account the properties of the gearbox, and first of all, the torque transfer coefficient Km should be taken into account. As studies have shown, the Km coefficient in gearboxes varies significantly depending on the operating mode. For example, for a gearbox with a gear ratio Kr = 220, used in valve electronics, the values change as follows: y work at stop when starting with shock application of torque: Km = 0.8 Kr.; y work on stop when starting with smooth application of torque: Km = 0.65 Kr; y work in motion: Km = 0.9 Кр× f(Мc), where Мc is the moment of resistance; y transition from the driving mode to the stop mode: Km = 0.95 Kr.

Thus, the control algorithm of the electric drive must take into account the nonlinear nature of its elements (IM, TPH, gearbox). Due to the fact that the coefficient Km for different gearboxes may have some differences (due to imperfect technologies for manufacturing its elements), it is necessary to provide for the possibility of appropriate adaptation for the control system. To solve this problem when creating an electronic control unit, the algorithm presented in Fig. 3 as a graph. The nodes of the graph show the logical modes of operation of the control system in the form of some fixed states, where there is its own logic of operation, a process model and criteria for achieving the set goal of the mode. The lines of the graph show the conditions and directions of transitions when events occur in the system that determine a regime change. Event designations on arrows:

command to move;
presence of a phase short circuit;
presence of a linear short circuit;
phase short circuit test timer;
linear short circuit test timer;
no movement timer;
completion of the impact moment procedure;
the number of attempts to apply the impact torque is zero;
exceeding the moment of movement;
engine speed is more than half the rated speed;
command to stop, reaching the target position;
no movement timer.

Fulfillment of the requirements for protection against short circuit currents is carried out by applying preliminary test pulses to the thyristors with large opening angles φ (170° for determining a phase short circuit and 120° for a linear one). At the end of the test, the stop torque specified at the start is processed; in this case, the opening angle of the thyristors is formed in accordance with the specified torque limit and the current network voltage. In the absence of movement, control is transferred to the “Impact” algorithm, which generates a torque pulse due to the zero opening angle of the thyristors with control of the number of starts of this algorithm and subsequent return to the previous opening angle of the thyristors. At the beginning of the movement, the opening angle of the thyristors tends to the minimum value (the “Motion” algorithm), and the calculation of the load torque is carried out as a tabular function of the network voltage, motor current and power factor. In this mode, the engine operates in a linear section of the mechanical characteristic and provides a speed close to the rated speed. If the torque exceeds the specified value, control is transferred to the “Stop” algorithm with a stepwise change in the opening angle of the thyristors, which leads to a decrease in speed, “relaxation” of the gearbox and the ability to control according to the table that “forms” the torque at start. If the motion of the electric motor is not resumed within a specified time, an alarm signal is generated about the load torque being exceeded and the engine is switched off.

In conclusion, it should be noted that for a more detailed study of the capabilities of such an electronic signature, it is possible to obtain it on the website www.elesy.ru software simulator of electronic shut-off valves with an electronic control unit ESDVTG. This software product is the closest possible model of a real electric drive with an ESD-VTG control unit. There are also simulators for other electronic control units produced by EleSy. This model is built on the basis of: y real software loaded into the ESD-VTG electronic unit; y systems of differential equations for modeling the operation of an asynchronous three-phase motor with a squirrel cage rotor; y principles of operation of the TRN for a three-phase load without a zero terminal; y the ability to create “virtual” control via a serial interface. Using the proposed simulator, the user has the opportunity to simulate the operation of the shut-off valve electronics (taking into account the load diagram, the state of the electrical network, the connections made to the interface and power parts of the unit, etc.).

Drawing. Electronic control unit EP shut-off and control valves ESD-VT G

The new control unit was initially developed to modernize the previously used ES shut-off valves, which had a short resource on the part of the elements of the cam mechanism for setting electromechanical travel microswitches. The technology for adjusting and setting up limit switches is also extremely inconvenient from an operational point of view, requiring opening the switch cover, as well as manually setting the cams and pointer arrow. The accuracy of setting up such electronic devices is low, and their integration into a modern process control system with digital interfaces is problematic. In a modernized electric drive, a new control unit is installed to replace the old one. Wherein:

it becomes possible to integrate the electric drive into the process control system via the RS-485 serial interface;
when the ED is equipped with an electronic position sensor, which ensures high positioning accuracy, it is possible to quickly adjust the final positions of the valve shut-off element in various ways, including without turning on the engine and moving the valve shut-off element;
The electric drive is equipped with an electronic two-way torque limiting clutch; this coupling provides the ability to work “on the stop” with a given torque, identification of the drive torque when moving based on the values of the motor currents and network voltage, as well as setting different values for limiting the torque depending on the direction of movement of the electric drive and the position of the shut-off element;
The unit independently provides the entire necessary set of algorithms for protecting the motor and valves, eliminating the need to install complex external relay systems.

A thyristor voltage regulator (TVR) is used as a power switch in the unit, which determines the small dimensions, high reliability and low cost of the electric power supply.

Various types of gearboxes can be used in EP. The requirements regarding the torque limitations of the electric drive are fulfilled taking into account the properties of the gearbox, and first of all, the torque transfer coefficient Km should be taken into account. As studies have shown, the Km coefficient in gearboxes varies significantly depending on the operating mode. For example, for a gearbox with a gear ratio Kr = 220, used in valve electronics, the values change as follows: y work at stop when starting with shock application of torque: Km = 0.8 Kr.; y work on stop when starting with smooth application of torque: Km = 0.65 Kr; y work in motion: Km = 0.9 Кр× f(Мc), where Мc is the moment of resistance; y transition from the driving mode to the stop mode: Km = 0.95 Kr.

command to move;
presence of a phase short circuit;
presence of a linear short circuit;
phase short circuit test timer;
linear short circuit test timer;
no movement timer;
completion of the impact moment procedure;
the number of attempts to apply the impact torque is zero;
exceeding the moment of movement;
engine speed is more than half the rated speed;
command to stop, reaching the target position;
no movement timer.

Basic prerequisites for the development of intelligent digital electric drives

The start to the accelerated development of digital systems that form the basis of intelligent control systems for electric drives should be considered the appearance of the first microprocessor in 1971. Since then, this industry has undergone rapid development, which continues to this day.
Thanks to advances in microprocessor technology and power electronics in last years Embedded microprocessor systems, IGBT transistors, high-performance microcontroller systems for direct digital equipment control and intelligent IPM power modules capable of real-time control of dynamic processes of electric drives have found practical application.

Modern microcontrollers include direct digital control functions, which are directly built into the microcontrollers and are characterized by a developed architecture and command system, allowing most problems to be solved at the fast code level. typical tasks control of dynamic systems. New approaches used in digital control systems for modern electric drives include:
— transition from conventional counters to sets of universal counters/timers with built-in comparison/capture channels and further to multi-channel event processors;
— availability of high-speed output channels at frequencies up to 20-50 kHz;
— precision timing processing of input multichannel pulse sequences for interfacing with a wide class of feedback sensors (pulse, inductive, Hall elements, etc.);
— availability of high-speed input function at frequencies up to 100 kHz and higher;
— creation of specialized peripheral devices such as “quadrature decoders” for processing signals from the most common feedback sensors (in particular, optical position sensors);
— availability of functions for direct control of power switches and position/speed identification;
— creation of unified multi-channel PWM generators with built-in capabilities for direct digital control of inverter switches, active rectifiers and DC-DC converters in frontal, centered and vector PWM modulation modes;
- integration of an event processor and a multi-channel PWM generator in one universal device - an event manager;
— creation of microcontrollers with dual event managers for direct digital control of drives according to the system: “Active rectifier-Inverter-Motor” and “DC-DC Converter – Inverter-Motor”, as well as for controlling dual-motor drives;
— a significant increase in the speed of analog-to-digital converters (conversion time up to 100 ns per channel), auto-synchronization of ADC startup processes with the operation of other peripheral devices, in particular, PWM generators;
auto-pipelining of conversion processes to ADC via several channels (up to 16)
— support for direct current control and direct torque control functions.
The listed features of digital control of electric drives, together with the accelerated development of microprocessor technology, create a favorable climate for the development and implementation of innovative technologies and the use of modern mathematical methods for the synthesis of electric drive control systems.

Some mathematical methods and approaches used in intelligent control systems for electric drives

One of the urgent problems in the synthesis of a modern electric drive is the construction of optimal control systems. When formulating the problem of synthesizing optimal control, in addition to the equations of the control object, an optimality criterion is selected, which must be achieved in a finite time, subject to the specified restrictions on control, phase vector and boundary conditions.
A certain objective function acts as an optimality criterion (for example, achieving maximum performance, minimum energy consumption, etc.).
Various approaches are known to solve this problem. Among the most common are the so-called gradient methods, in which the target function is presented as a functional of several state variables of a dynamic system - F(x1,x2, ... xn).
According to the gradient method algorithm, to determine the direction of movement towards the optimum, it is necessary to find partial derivatives: δF/δx1; δF/δx2;… δF/δxn, which determine the gradient vector, and take a step in the direction of its decrease. At each optimization step, the gradient calculation procedure is repeated. As a result, at the end point the value of the functional F(x1,x2, … xn) reaches an extremum, and the value of the gradient reaches its zero value.
When implementing gradient methods in practice, many questions arise related to the justification of the type of quality functional, the step length at each iteration, as well as the probability of the motion trajectory falling to a local minimum point and solving the problem of finding a global extremum.
Transition to digital systems management systems built using modern element base and microprocessor technology, made it possible to move to new technologies for controlling electric drives, which were previously unattainable due to technical limitations. Such technologies include the synthesis of electric drive systems with elements of artificial intelligence, which widely use the developments of living nature in matters of adaptation of organisms to a changing external environment.
Recently, many algorithms have been proposed to optimize the control of dynamic systems based on simulating the behavior of living organisms. Various search stochastic algorithms, which in the domestic literature are known as population algorithms, have become widespread. They belong to the class of heuristic algorithms, the convergence of which to a global solution has not been theoretically proven, but based on numerical experiments it has been shown that in most cases they give fairly good results.
The following classifications of population algorithms are presented:
— evolutionary algorithms, including genetic algorithms;
— population algorithms inspired by wildlife;
— algorithms inspired by inanimate nature;
— algorithms inspired by human society;
— other algorithms.
In turn, evolutionary algorithms include:
-genetic algorithms,
-evolution strategy,
-evolutionary programming,
-algorithms of differential evolution (differentialevolution),
-genetic programming.
Evolutionary algorithms are based on general principles biological evolution (selection, mutation and reproduction of individuals) and are part of a broader technology of so-called soft computing, which includes fuzzy logic, neural networks, probabilistic reasoning and trust networks, which independently or in various combinations are used in the synthesis of systems with artificial intelligence.
Among the optimization algorithms that are widely used for the synthesis of electric drive systems are population algorithms inspired by living nature, which do not require gradient calculations to find the extremum of the objective function (particle swarm, ant colony and bee swarm algorithms).
At their core, such algorithms imitate the collective behavior of flocks of birds and schools of fish, or the behavior of an ant colony or a swarm of bees. The algorithm for the behavior of each individual in a flock can be implemented on the following principles:
1) the desire when moving to avoid collisions with the nearest individuals of the flock;
2) choice of speed taking into account the speeds of individuals moving nearby in a flock;
3) minimizing the distance to nearest neighbors.
These principles are used in one of the most popular mathematical methods - the so-called particle swarm method, which was originally developed to simulate the choreography of a flock of birds, and later it was developed to solve problems of optimization of dynamic systems. The optimization algorithm using the particle swarm method can be presented in Fig. 1.

Fig.1. Particle swarm optimization algorithm
At each moment of time, particles have a certain position and velocity vector in state space, which changes at each iteration according to the following formula:
vi= ω∙ vi+a1∙ rnd()∙(pbesti - xi) + a2∙rnd(). (gbesti - xi),
Where:
a1, a2 are constant accelerations (the speed of convergence of the algorithm depends on the choice of these parameters);
pbesti t is the best point found by the particle;
gbesti is the best point traversed by all particles of the system;
xi is the current position of the particle;
rnd() is a function that returns a random number from 0 to 1 inclusive.

The coefficient ω, called the coefficient of inertia by Yuhui Shi and Russell Eberhart, balances the breadth of exploration with attention to suboptimal solutions found.
In the case of ω >1, the particle velocities increase, they fly apart and explore space more thoroughly. Otherwise, particle velocities decrease over time.
After calculating the direction of vector v, the particle moves to point x= x + v,
based on the best extremum achieved by a given particle and information about the most optimal particles in the swarm.
If necessary, the values of the best points for each particle are updated for all particles as a whole, after which the cycle is repeated.
The following can be chosen as a condition for completing the optimization algorithm using the particle swarm method: the search for an extremum ends upon reaching a certain number of iterations during which the solution has not been improved.
Currently methods intelligent control, built on the basis of the particle swarm method, represent a serious alternative to traditional optimization methods.
For example, in relation to valve electric drive control systems, a simplified algorithm based on the particle swarm method is presented, which allows optimizing the parameters of passive filters in order to suppress current harmonics and increase the efficiency of the electric drive. This algorithm is suitable for designing passive filters in synchronous electric drive systems with three types of load: with constant torque; with constant speed and variable torque; with variable speed and variable torque. As a result of applying the method, a reduction in the influence of the harmonic composition of currents and voltages on the alternating current network was achieved, as well as an increase in the efficiency of the electric drive
In solving the problem of optimizing the control of active magnetic bearings (AMP), two modifications of the classical particle swarm optimization (PSO) algorithm were compared: an algorithm with linearly decreasing inertia weight (LDW-PSO); Algorithm with constriction factor approach (CFA-PSO) Based on the results of computer simulation of both versions of the algorithm, an assessment of the convergence of procedures for minimizing the objective function, defined as an integral of the absolute value of the error, is given. It is shown that these PSO algorithms provide the necessary convergence and high computational efficiency when optimizing various structures of PID controllers used in rotor stabilization systems in the radial and axial directions.
Currently, the particle swarm method is also used in problems of optimizing the design parameters of electrical machines.
Thus, in order to increase the accuracy of flux linkage calculations, as well as to optimize the main design and operating parameters of a synchronous motor with permanent magnets and a magnetically suspended rotor, a new method for its modeling has been developed based on methods for optimizing a swarm of particles and least squares support vectors. During the simulation, the rotor angle, working winding current and suspension force are specified and the flux linkage is determined. The relationships between the initial and determined parameters are derived. The advantages of the new method in terms of accuracy and speed of calculations compared to the previously used traditional approach have been confirmed.
One of the areas in which the particle swarm method has become quite widely used is the optimization of the designs of switch-type electric motors used in modern electric drive systems. For example, it is known that magnetic pole segmentation is effective and in a simple way to reduce the torque from harmonic field interference arising in powerful synchronous machines with permanent magnets. To solve this problem, it is necessary to apply multicriteria optimization methods. One possible and time-consuming approach is to select the optimal width and offset of the magnetic segments using the finite element method. The work proposes a new, more economical strategy based on the use of a semi-analytical model of the electromagnetic torque arising due to the action of harmonic field interference, together with multi-criteria optimization of the machine design using the particle swarm method. The effectiveness of the proposed method is shown by comparison technical characteristics two prototypes of segmented pole synchronous machines with two and three blocks of permanent magnets per pole, optimized by the particle swarm method, with the characteristics of permanent magnet permanent magnet motors with uniform poles, optimized by the finite element method.
When looking for new approaches to optimizing the control of electric drives, we are not limited to imitating flocks of birds and swarms of insects. Effective population optimization algorithms also include algorithms that imitate the behavior of certain bacteria. Thus, the innovative technology of smart control of a switched reluctance motor using the so-called is considered. Smart Bacterial Foraging Algorithm (SBFA), which simulates the chemotactic behavior of bacteria - their movement along a nutrient concentration gradient. The possibilities of using the SBFA algorithm for optimizing adaptive control systems are discussed. The effectiveness of the proposed methodology is illustrated by the example of optimization of the proportional-integral speed controller of a switched reluctance electric drive with a 4 kW motor and an 8/6 configuration. Minimum speed errors and torque ripple are used as a multi-objective optimization function, and a TMS320F2812 digital signal processor is used as a platform for implementing the control algorithm.
In general, the bibliography of scientific articles devoted to the optimization of electric drive control systems using population algorithms that imitate the behavior of living beings amounts to hundreds of publications in recent years alone. Inspiring results have been obtained, which give reason to hope that in the near future the considered theoretical principles will become everyday practice and will make it possible to reach a new, previously unattainable stage in the development of industrial and transport automation.

LITERATURE
1. N.N. Shchelkunov, A.P. Dianov “Microprocessor tools and systems”, Moscow, Radio and Communications, 1989, 288p.
2. Kozachenko V.F. Microcontroller control systems for electric drives:
current state and development prospects, http://www.motorcontrol.ru/publications/controllers.pdf
Department of Automated Electric Drive MPEI, Moscow, 2014.
3. Voronov A.A. Theory automatic control. In 2 parts. Part II Theory of nonlinear and special automatic control systems. –M.: graduate School, 1986. 504 p.
4. Algorithms inspired by nature: textbook / A. P. Karpenko. - Moscow: Publishing house of MSTU im. N. E. Bauman, 2014.
6. Singh S., Singh B.. Optimized passive filter design using modified particle swarm optimization algorithm for a 12-pulse converter-fed LCI-synchronous motor drive. IEEE Trans. Ind. Appl.. 2014. 50, N 4, p. 2681-2689. English
7. Stimac Goranka, Braut Sanjin, Zigulic Roberto. Comparative analysis of PSO algorithms for PID controller tuning. Chin. J. Mech. Eng.. 2014. 27, N 5, p. 928-936. Bible 21. English
Sun Xiaodong, Zhu Huangqiu, Yang Zebin. Nonlinear modeling of flux linkage for a bearingless permanent magnet synchronous motor with modified particle swarm optimization and least squares support vector machines. J. Comput. and Theor. Nanosci.. 2013. 10, N 2, p. 412-418, 3 ill.. Bible. 29. English
Multiobjective shape optimization of segmented pole permanent-magnet synchronous machines with improved torque characteristics. Ashabani Mahdi, Mohamed Yasser Abdel-Rady I. IEEE Trans. Magn. 2011. 47, no. 4, p. 795-804, 11 ill. BIBL. 47. English
Daryabeigi Ehsan, Dehkordi Behzad Mirzaeian
Smart bacterial foraging algorithm based controller for speed control of switched reluctance motor drives. - P. 364 - 373. - English. // International Journal of Electrical Power and Energy Systems, 2014, Volume 62.

Features of Intelligent Electric NA Drive

The drives are designed taking into account the latest advances in intelligent protection of the drive and its individual components, as well as their remote and local diagnostics. Today, they fully comply with all modern requirements for such equipment from most sectors of the national economy.

The power part of the electric drive is made on the basis of the NA electric drive. Additional intelligent functions are provided in the intelligent block, which is attached to the drive as a separate function block.

a. drive mode readings:

Remote - remote control of the drive
Local - local drive control
Off - drive stop
Auto - drive autoscan mode (optional in PCU - drive positioner)
Set - setting drive parameters

b. drive status indications:

Open - drive is completely open
Close - actuator is completely closed
Run - the drive is in motion
Fault - drive error

With. indications of operating position of the drive 0 - 100%

d. drive error number

Smart drive functions

Diagnostics of the correct phase rotation and elimination of their mismatch;
Controlling the direction of movement of the drive without throwing installation wires;
Possibility of setting operating modes of the drive - jolting and holding;
Setting the direction of movement of the drive in case of loss of the control signal;
Selecting the method of stopping the drive when reaching the final positions - upon reaching the final position or upon exceeding the torque;
Checking the operating time of the drive according to the “open-close” resource;
Checking the condition of the measuring potentiometer;
Automatic calibration mode of the drive stroke;
Selecting outgoing signals from the presented types or setting your own values;
Installation and adjustment of “dead zones” of the drive stroke - protection against the “hammer effect”;
Setting and adjusting the time for passing the “dead zone” - postponing some signals for this time;
Providing a signal about the position of the drive after the “fault” signal has been processed;
Setting and adjusting the starting and ending points of the analog signal;

Smart unit options available in menu (when using PMU)

	On-off mode	CPT (current sensor)	PCU (positioner)
PH-check (phase check)
Direct (direction of movement)
Inch/hold
Esd dir (movement in case of absence of control signal)
TQ check (stop method when reaching extreme positions)
Cycle (check the number of cycles)
PIU check (potentiometer check)
Auto scan (auto calibration mode)
Input sel (setting output signals)
Input set (setting outgoing signals not from the menu)
Dead band (dead zone setting)
Time delay (setting the signal delay time)
Input F/A (providing a signal about the position of the actuator after a fault signal)
Cl out Set (setting the outgoing signal to “0”)
Op out set (setting “100” of the outgoing signal)

The design of electrical connections, separated into a separate unit, with electrical connection diagrams installed at the factory, does not allow atmospheric moisture and dust to get inside the drive. This increases the life cycle of the drive and the performance of each of its components throughout the entire service life of the drive.

Electrical diagram of the terminal block

	Description

Supply voltage U, V, W	Voltage 3-phase 380 V 50 Hz.



Input terminals	Remote control - Closed
	Remote control - Open
	Remote control - Stop
	Remote control - ESD
	Remote control - Auto
	Remote control AC COM
	Remote control DC COM
	Remote input 4-20 mA(+)
	Remote input 2-20 mA(-)
Output terminals	Integral voltage 24VDC(+)
	Integral voltage 24VDC(-)
	COM Monitor	Max. Eg. 250VAC 5A
	Monitor On/Off
	Monitor Remotely
	COM defect	Max. Eg. 250VAC 5A


	Working stroke of the COM	Max. Eg. 250VAC 5A
	Working stroke to Closed
	Work progress to Open
	Complete closure of COM	Max. Eg. 250VAC 5A
	Full NC closure
	Full closure NO
	Full opening of COM	Max. Eg. 250VAC 5A
	Full opening NC
	Full opening NO
	Remote output 4-20 mA (+)
	Remote output 4-20 mA (-)

Electrical connection diagrams

NA 301 (On-Off Type)
NA 302 (CPT Type)
NA 303 (PCU Type)

The high-speed Profibus protocol operates via the RS485 port using a 2-wire electrical circuit. Up to 126 drives inclusive can be connected via a network with a suitable repeater. In the absence of a repeater (repeater), only 32 devices can be connected.

Transmission speed and cable length.

GSD-FAIL master: program installation

Profibus DP card interface specification

Command and feedback signals:

command signals: position value (00-FF, 256 steps)
feedback signal: position value (00-FF, 256 steps)

Profibus DP general specification:

Communication protocols: Profibus DP compliant with IEC 61158 and 617
transmission medium: twisted pair, shielded copper cable, EN50170 compliant.

Profibus DP interface: EIA-485 (RS485).

Device number: 32 devices without repeater, 126 devices with repeater. Operating temperature (-10 +70 o C).

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