• Journal of Power Electronics
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• v.16 no.3
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• pp.1004-1011
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• 2016

The inaccurate model parameters in the predictive current control of surface-mounted permanent magnet synchronous motor (SMPMSM) affect the current dynamic response and steady-state error. This paper presents a model parameter correction algorithm based on the relationship between the errors of model parameters and the static errors of dq-axis current. In this correction algorithm, the errors of inductance and flux are corrected in two steps. Resistance is ignored. First, the proportional relations between inductance and d-axis static current errors are utilized to correct the error of model inductance. Second, the flux is corrected by utilizing the proportional relations between flux and q-axis static current errors under the condition that inductance is corrected. An experimental study with a 100 W SMPMSM is performed to validate the proposed algorithm.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.272-283
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• 2017

In this paper, an improved predictive functional control (PFC) scheme for permanent magnet synchronous motor (PMSM) control system is proposed, on account of the standard PFC method cannot provides a satisfying disturbance rejection performance in the case of strong disturbances. The PFC-based method is first introduced in the control design of speed loop, since the good tracking and robustness properties of the PFC heavily depend on the accuracy of the internal model of the plant. However, in orthodox design of prediction model based control method, disturbances are not considered in the prediction model as well as the control design. A minimum-order observer (MOO) is introduced to estimate the disturbances, which structure is simple and can be realized at a low computational load. This paper adopted the MOO to observe the load torque, and the observations are then fed back into PFC model to rebuild it when considering the influence of perturbation. Therefore, an improved PFC strategy with torque compensation, called the PFC+MOO method, is presented. The validity of the proposed method was tested via simulation and experiments. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection.

• Journal of Power Electronics
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• v.17 no.3
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• pp.674-685
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• 2017

The conventional model predictive direct torque control (MPDTC) method uses all of the voltage vectors available from a two level voltage source inverter for the prediction of the stator flux and stator current, which leads to a heavy computational burden. This paper proposes an improved model predictive direct torque control method. The stator flux predictive controller is obtained from an analysis of the relationship between the stator flux and the torque, which can be used to calculate the desired voltage vector based on the stator flux and torque reference. Then this method only needs to evaluate three voltage vectors in the sector of the desired voltage vector. As a result, the computational burden of the conventional MPDTC is effectively reduced. The time delay introduced by the computational time causes the stator current to oscillate around its reference. It also increases the current and torque ripples. To address this problem, a delay compensation method is adopted in this paper. Furthermore, the switching frequency of the inverter is significantly reduced by introducing the constraint of the power semiconductor switching number to the cost function of the MPDTC. Both simulation and experimental results are presented to verify the validity and feasibility of the proposed method.

• Journal of Power Electronics
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• v.15 no.6
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• pp.1547-1558
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• 2015

A predictive functional control (PFC) scheme for permanent magnet synchronous motor (PMSM) servo systems is proposed in this paper. The PFC-based method is first introduced in the control design of speed loop. Since the accuracy of the PFC model is influenced by external disturbances and speed detection quantization errors of the low distinguishability optical encoder in servo systems, it is noted that the standard PFC method does not achieve satisfactory results in the presence of strong disturbances. This paper adopted the Kalman filter to observe the load torque, the rotor position and the rotor angular velocity under the condition of a limited precision encoder. The observations are then fed back into PFC model to rebuild it when considering the influence of perturbation. Therefore, an improved PFC method, called the PFC+Kalman filter method, is presented, and a high performance PMSM servo system was achieved. The validity of the proposed controller was tested via experiments. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection.

• Smart Structures and Systems
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• v.25 no.5
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• pp.559-567
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• 2020

Vibration at the tip of various flexible manipulators may affect their operation accuracy and work efficiency. To suppress such vibrations, the feasibility of using MFC actuators and sensors is investigated in this paper. Considering the convergence of the famous filtered-x least mean square (FXLMS) algorithm could not be guaranteed while it is employed for vibration suppression of plants with varying secondary path, this paper proposes a new multiple model switching adaptive control algorithm to implement the real time active vibration suppression tests with a new multiple switching strategy. The new switching strategy is based on a cost function with reconstructed error signal and disturbance signal instead of the error signal from the error sensor. And from a robustness perspective, a new variable step-size sign algorithm (VSSA) based FXLMS algorithm is proposed to improve the convergence rate. A cantilever beam with varying tip mass is employed as flexible manipulator model. MFC layers are attached on both sides of it as sensors and actuators. A co-simulation platform was built using ADAMS and MATLAB to test the feasibility of the proposed algorithms. And an experimental platform was constructed to verify the effectiveness of MFC actuators and sensors and the real-time vibration control performance. Simulation and experiment results show that the proposed FXLMS algorithm based multiple model adaptive control approach has good convergence performance under varying load conditions for the flexible cantilever beam, and the proposed FX-VSSA-LMS algorithm based multiple model adaptive control algorithm has the best vibration suppression performance.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.5
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• pp.691-696
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• 2012

In this study, a rigid multi-body dynamic model has been developed for mechatronic analysis to evaluate dynamic behavior of a machine tool. The development environment was the commercialized analysis tool, ADAMS, for rigid multi-body dynamic analysis. A simplified servo control logic was implemented in the tool using its functions in order to negate any external tool of control definition. The advantage of the internal implementation includes convenience of the analysis process by saving time and efforts. Application of this development to a machine tool helps to evaluate its dynamic behavior against feeding its component, to calculate the motor torque, and to optimize parameters of the control logic.

• Journal of Energy Engineering
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• v.6 no.1
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• pp.41-51
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• 1997

A dynamic mathematical model of a thermal power plant with a single drum-type boiler is described with the base on modular concept. The present process model, which is including full scope of the components and high load changes, is based on physical approach through lumped parameters. The module, which means a component of the power plant and must essentially depict the characteristics of the component well, might be interconnected using pressure nodal method in a arrangement determined by users. With the results of the load changes of 75 MW to 95 MW and 95MW to 75 MW with the rate of 3 MW/min, the applicability of the process model is examined connecting to DCS(Dispersion Control System), which has a real running logic of 100 MW real power plant.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.533-541
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• 2005

In this paper, a wind turbine with power splitting transmission, which is realized through a novel three-shaft planetary, is presented. The input shaft of the transmission is driven by the rotor of the wind turbine, the output shaft is connected to the grid via the main generator (asynchronous generator), and the third shaft is driven by a control motor with variable speed. The dynamic models of the sub systems of this wind turbine, e.g. the rotor aerodynamics, the drive train dynamics and the power generation unit dynamics, were given and linearized at an operating point. These sub models were integrated in a multidisciplinary dynamic model, which is suitable for control syntheses to optimize the utilization of wind energy and to reduce the excessive dynamic loads. The important dynamic behaviours were investigated and a wind turbine with a soft main shaft was recommend.

• Earthquakes and Structures
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• v.11 no.6
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• pp.943-966
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• 2016

Recently, magnetorheological elastomer (MRE) material and its devices have been developed and attracted a good deal of attention for their potentials in vibration control. Among them, a highly adaptive base isolator based on MRE was designed, fabricated and tested for real-time adaptive control of base isolated structures against a suite of earthquakes. To perfectly take advantage of this new device, an accurate and robust model should be built to characterize its nonlinearity and hysteresis for its application in structural control. This paper first proposes a novel hysteresis model, in which a nonlinear hyperbolic sine function spring is used to portray the strain stiffening phenomenon and a Voigt component is incorporated in parallel to describe the solid-material behaviours. Then the fruit fly optimization algorithm (FFOA) is employed for model parameter identification using testing data of shear force, displacement and velocity obtained from different loading conditions. The relationships between model parameters and applied current are also explored to obtain a current-dependent generalized model for the control application. Based on the proposed model of MRE base isolator, a second-order sliding mode controller is designed and applied to the device to provide a real-time feedback control of smart structures. The performance of the proposed technique is evaluated in simulation through utilizing a three-storey benchmark building model under four benchmark earthquake excitations. The results verify the effectiveness of the proposed current-dependent model and corresponding controller for semi-active control of MRE base isolator incorporated smart structures.

• Horticultural Science & Technology
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• v.30 no.3
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• pp.270-277
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• 2012

Greenhouse industry has been growing in many countries due to both the advantage of stable year-round crop production and increased demand for fresh vegetables. In greenhouse cultivation, $CO_2$ concentration plays an essential role in the photosynthesis process of crops. Continuous and accurate monitoring of $CO_2$ level in the greenhouse would improve profitability and reduce environmental impact, through optimum control of greenhouse $CO_2$ enrichment and efficient crop production, as compared with the conventional management practices without monitoring and control of $CO_2$ level. In this study, a mathematical model was developed to estimate the $CO_2$ emission from soil as affected by environmental factors in greenhouses. Among various model types evaluated, a linear regression model provided the best coefficient of determination. Selected predictor variables were solar radiation and relative humidity and exponential transformation of both. As a response variable in the model, the difference between $CO_2$ concentrations at the soil surface and 5-cm depth showed are latively strong relationship with the predictor variables. Segmented regression analysis showed that better models were obtained when the entire daily dataset was divided into segments of shorter time ranges, and best models were obtained for segmented data where more variability in solar radiation and humidity were present (i.e., after sun-rise, before sun-set) than other segments. To consider time delay in the response of $CO_2$ concentration, concept of time lag was implemented in the regression analysis. As a result, there was an improvement in the performance of the models as the coefficients of determination were 0.93 and 0.87 with segmented time frames for sun-rise and sun-set periods, respectively. Validation tests of the models to predict $CO_2$ emission from soil showed that the developed empirical model would be applicable to real-time monitoring and diagnosis of significant factors for $CO_2$ enrichment in a soil-based greenhouse.