On PI-controller Parameters Adjustment for Rolling Mill Drive Current Loop Using Neural Tuner

Eremenko, Y. I.; Glushchenko, Anton; Petrov, Vladislav

doi:10.1016/j.procs.2017.01.121

Cited by 5 publications

(5 citation statements)

References 11 publications

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“…Here, KP is the parameter of the PI-controller proportional part; KI is the parameter of the PI-controller integral part, ûad is an additional term to compensate for τ e ; e = r ω − ω is the tracking error, i.e., the difference between the rotor speed setpoint r ω and its actual value. The fact that u (the armature current) is bounded is taken into consideration in (5) with the help of the saturation function sat(.) and the Anti-Windup procedure sat I (.…”

Section: Problem Statementmentioning

confidence: 99%

“…Remark 1. It follows from the chosen control law (5) with the Anti-Windup procedure (6) that Assumption 2 is met for (5).…”

Section: Problem Statementmentioning

confidence: 99%

“…In [5,6], the neural network and fuzzy tuners of the speed PI-controller parameters are proposed, respectively. The advantages of these tuners include the rules of the PI-controller parameters adjustment, which are understandable by the process automation engineers.…”

Section: Introductionmentioning

confidence: 99%

“…This paper is to take all the shortcomings of the methods from [5][6][7][8] into consideration and propose an adaptive DC motor speed control system, which: (1) uses only measurable signals; (2) considers the boundedness of the control signal; and (3) adaptively compensates for the load torque.…”

Section: Introductionmentioning

confidence: 99%

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DC Drive Adaptive Speed Controller Based on Hyperstability Theory

2022

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The scope of this research is to develop a hyperstable adaptive control system of a direct current (DC) drive speed for effective load torque attenuation. The proposed speed controller is based on the model reference adaptive control framework and integrated into the conventional DC drive cascade control system. Its main features are as follows: (1) the boundedness of the control action signal, as well as the armature current control loop non-stationarities, are taken into consideration with the help of the reference model hedging technique; (2) its inputs include only measurable signals, thus there is no need to use any kind of state estimators; (3) it attenuates the disturbances, which are matched with its control action signal, particularly, the inertia moment non-stationarity and load torque. The asymptotic hyperstability of the obtained DC drive control system is proven with the help of Lyapunov’s theorems and Popov’s criterion. The numerical experiments corroborate the obtained results. They include the demonstration of disadvantages of the conventional cascade control system under conditions of the drive parameters’ non-stationarity and advantages of the proposed solution for different disturbance types and amplitudes.

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Section: Problem Statementmentioning

confidence: 99%

“…Remark 1. It follows from the chosen control law (5) with the Anti-Windup procedure (6) that Assumption 2 is met for (5).…”

Section: Problem Statementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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DC Drive Adaptive Speed Controller Based on Hyperstability Theory

2022

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“…On PI-controller, the adjustments of PI controller parameters are used for a rolling mill drive control. It shows that, the quality improvement of transient response of speed and current control loops [5]. The direct synthesis method is used and determines the parameters of PI controllers and it is used for the control of wide variety of processes, inclusion of delay time with first-order system, secondorder system, an integrator system and non-minimum phase system.…”

Section: Introductionmentioning

confidence: 99%

Control of Third Order Processes Using Optimized Synthesis PI Controller

Suganya¹,

Kumar²

2018

IJET

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In closed loop system with PI controller, the most and severe problem is peak overshoot minimization in the closed loop response and tuning the proportional plus integral (PI) controller parameters. This paper deals with the two different tuning methods for obtain the PI controller settings. These methods are used to tune the parameters of PI controller and the closed loop performances of two methods are analyzed for the control of third order processes. From the closed loop responses, the time responses are move to unstable characteristics and the process variables are oscillates due to PI parameters are tuned using Ziegler-Nichols method and direct synthesis method respectively. The control loop performance of the control of third order process is improved with optimized parameters of PI controller. In direct synthesis method, the variable parameter of PI controller is obtained with Genetic algorithm. The controller parameter of PI controller is obtained from optimized variable parameters and results are reveals that the performance of closed loop is enhanced with the elimination of peak overshoot and minimization of oscillation levels in the process variables. Simulation results are confirmation that the proposed design method is better to the Ziegler-Nichols method and direct synthesis method. Furthermore, the proposed method was applied to the control of two different categories of third order processes.

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Method of Calculation of Upper Bound of Learning Rate for Neural Tuner to Control DC Drive

Glushchenko¹

2017

Advances in Neural Computation, Machine Learning, and Cognitive Research

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On PI-controller Parameters Adjustment for Rolling Mill Drive Current Loop Using Neural Tuner

Cited by 5 publications

References 11 publications

DC Drive Adaptive Speed Controller Based on Hyperstability Theory

DC Drive Adaptive Speed Controller Based on Hyperstability Theory

Control of Third Order Processes Using Optimized Synthesis PI Controller

Method of Calculation of Upper Bound of Learning Rate for Neural Tuner to Control DC Drive

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