Abstract
Rolling stands are complex nonlinear objects in metallurgical industry. Their parameters can change their values over time. In order to control rolling stands, direct current electric drives and P- and PI-controllers are used with constant parameters. Such systems include two control circuits. The application of algorithms of linear control leads to the deterioration of transition processes because of a change in the operational mode of the stand. This problem can be resolved by tuning the parameters of linear controllers. Neural-network tuners were previously developed for the circuit controllers of armature current and speed, working in real time without a mathematical model of the control object. The main purpose of present research is to solve a task on their joint operation in real time as well. We designed an algorithm that allows joint work of both tuners, which establishes priorities when calling the tuners. The primary one is tuning a controller of the current circuit, and only in the case that a given tuner was not called over several transitional processes, there is the possibility to call the tuner of the speed circuit. The experiments were conducted using a mathematical model of the main electrical drive of a rolling stand under conditions of change in the parameters of armature winding and mechanical part of the drive. Control system with two neural-network tuners made it possible to improve energy efficiency of the electric drive by 1.9 % compared with the system without tuning. Such a result was achieved by compensating for a drift in the parameters of electric drive and maintaining the overshoot for speed within the required range. If the overshoot happens to exceed the permissible value, power consumption of the unit increases, which we managed to avoid
Highlights
Among the main consumers of energy resources in metallurgical industry we can distinguish rolling production, including the rolling mills
The relevance of present study is determined by a wide distribution of high- power direct current electric rivers in the rolling production, improving energy efficiency of which even by 1–2 % would bring a significant economic effect
The following tasks have been set: – to develop a rule base that would account for the specificity of joint operation of tuners for current circuit and speed circuit, and to represent its performance in the form of an algorithm; – to test effectiveness of the designed rule base within the framework of a model experiment on the system that includes a neural-network tuner of speed circuit and a neural-network tuner of current circuit for a direct current electric drive
Summary
Among the main consumers of energy resources in metallurgical industry we can distinguish rolling production, including the rolling mills. Even a slight reduction in the energy consumption by electric drives of the rolling mills would reduce the cost of production. In this case, the automation issues are crucial for solving a problem on energy saving in the control systems of an automated electric drive. The relevance of present study is determined by a wide distribution of high- power direct current electric rivers in the rolling production, improving energy efficiency of which even by 1–2 % would bring a significant economic effect
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