Self-Tuning Predictive Control of Nonlinear Servo-Motor

Bobál, Vladimír; Chalupa, Petr; Kubalcik, Marek; Dostál, Petr

doi:10.2478/v10187-010-0056-x

Cited by 10 publications

(6 citation statements)

References 12 publications

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“…In [12] matrix methods are used to compute predictions. We derived a method for recursive computation of both the free response and the matrix of the dynamics [1,16].…”

Section: Computation Of Predictormentioning

confidence: 99%

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Identification and self-tuning predictive control of heat exchanger

Bobál

Kubalcik

Dostál

2013

2013 International Conference on Process Control (PC)

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Heat exchange belongs to the class of basic thermal processes which occur in a range of industrial technologies, particularly in the energetic, chemical, polymer and rubber industry. The process of heat exchange is often implemented by through-flow heat exchangers. It is apparent that for an exact theoretical description of dynamics of heat exchange processes it is necessary to use partial differential equations. Heat exchange is namely a process with distributed parameters. It is also necessary to take into account its nonlinear and stochastic character. In spite of these facts, most of thermal equipment is controlled by digital modifications of PID controllers at present. This paper deals with identification of a dynamic behavior of a through-flow heat exchanger and a design of an self-tuning predictive controller for its control. The designed controller was verified by a real-time control of experimental laboratory heat exchanger.

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“…In [12] matrix methods are used to compute predictions. We derived a method for recursive computation of both the free response and the matrix of the dynamics [1,16].…”

Section: Computation Of Predictormentioning

confidence: 99%

“…One of the possible approaches to control processes with time-delay is Model Predictive Control [9][10][11][12][13][14][15][16]. The aim of the paper is design of a self-tuning predictive controller for control of a laboratory heat exchanger.…”

Section: Introductionmentioning

confidence: 99%

Identification and self-tuning predictive control of heat exchanger

Bobál

Kubalcik

Dostál

2013

2013 International Conference on Process Control (PC)

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“…Another sensorless control application for PMSM driver systems has been demonstrated in [12], where sensorless direct current control is achieved by a MPC with a novel second-order PLL observer. In [13] a self-tuning based MPC has been applied to a higher-order nonlinear proportional servo motor.…”

Section: Introductionmentioning

confidence: 99%

Runge-Kutta Model Predictive Speed Control for Permanent Magnet Synchronous Motors

Akpunar

İplikçi

2020

Energies

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Permanent magnet synchronous motors (PMSMs) have commonly been used in a wide spectrum ranging from industry to home appliances because of their advantages over their conventional counterparts. However, PMSMs are multiple-input multiple-output (MIMO) systems with nonlinear dynamics, which makes their control relatively difficult. In this study, a novel model predictive control mechanism, which is referred to as the Runge-Kutta model predictive control (RKMPC), has been applied for speed control of a commercial permanent magnet synchronous motor. Furthermore, the RKMPC method has been utilized for the adaptation of the speed of the motor under load variations via RKMPC-based online parameter estimation. The superiority of RKMPC is that it can take the constraints on the inputs and outputs of the system into consideration, thereby handling the speed and current control in a single loop. It has been shown in the study that the RKMPC mechanism can also estimate the load changes and unknown load disturbances to eliminate their undesired effects for a desirable control accuracy. The performance of the employed mechanism has been tested on a 0.4 kW PMSM motor experimentally for different conditions and compared to the conventional Proportional Integral (PI) method. The tests have shown the efficiency of RKMPC for PMSMs.

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“…The adaptive laws are derived in the Lyapunov sense, thus, the asymptotic stability of the controlled system is guaranteed. For comparison purposes, the implementation of designed robust adaptive fuzzy control scheme on a strongly nonlinear plant and high level of amplitude of excitation has been compared with self-tuning Ziegler-Nichols PID controller which has been developed by Bobal et al [33][34][35]. MFC actuators are used for the real implementation of the control strategy, which allows achieving the required vibration level.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Vibration Control of a Nonlinear Smart Beam: A Comparison with Self-Tuning Ziegler-Nichols PID Controller

Oveisi

Gudarzi

2013

Journal of Low Frequency Noise, Vibration and Active Control

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This paper investigates the vibration control of geometrically nonlinear beam with Macro Fiber Composite (MFC) actuators using two different adaptive control algorithms. A complete mathematical modeling is presented in order to find the dynamic equation of motion. Then, a robust adaptive fuzzy control algorithm for controlling the proposed mechanical structure is introduced. This controller includes a fuzzy scheme and a robust controller. Based on sliding mode controller a fuzzy system is introduced to mimic an ideal controller. The robust controller is designed based on compensation of the difference between the fuzzy controller and the ideal controller. The parameters of the fuzzy system and uncertainty bound of the robust controller are adjusted adaptively. The adaptive laws are designed based on the Lyapunov stability theorem to reach the stability of the closed-loop system. Meanwhile, for comparison purposes the presented controller is compared with self tuning Ziegler-Nichols PID controller for both robustness and vibration suppression performance aspects. Effectiveness of these two control strategies is evaluated by numerical simulations. Detailed analysis for the closed-loop system is carried out to evaluate the vibration controlling performance under different output excitation, robustness of the closed-loop system under sudden loading and the effect of initial condition on vibration characteristic.

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Self-Tuning Predictive Control of Nonlinear Servo-Motor

Cited by 10 publications

References 12 publications

Identification and self-tuning predictive control of heat exchanger

Identification and self-tuning predictive control of heat exchanger

Runge-Kutta Model Predictive Speed Control for Permanent Magnet Synchronous Motors

Adaptive Sliding Mode Vibration Control of a Nonlinear Smart Beam: A Comparison with Self-Tuning Ziegler-Nichols PID Controller

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