A novel hysteresis current controller for active power filter with constant switching frequency

This paper present the mitigation of line current harmonics using control of shunt active power filter (SAPF). The three phase system is connected to nonlinear load which cause harmonics to affect the power system. The control of shunt active power filter is not only compensating harmonics but also compensate reactive power. Voltage source inverter(VSI) at using SAPF reference current control strategies; instantaneous real and reactive power theory (p-q theory), modified synchronous rotating reference frame theory(Modified d- q theory) with PI control and current control method at using hysteresis current control and SPWM controller. The different control technique of SAPF is based on reference current generation and current control method simulated by using MATLAB Simulink.

The traditional finite-control-set model predictive control (FCS-MPC) of three-phase active power filter (APF) has the problems of low compensation precision and long control delay. In order to address this problem, this paper proposes a multistep prediction compensation control method for the FCS-MPC of APF, it does not require modulation of PWM link. By utilizing the discrete mathematic model of three-phase parallel APF and keeping the advantages of traditional FCS-MPC, the prediction model is established based on the structural model of traditional FCS-MPC, the predictive controller is designed for predictive control of DC-side voltage. AC-side current and fixed switching frequency, and simulation study is also conducted. The simulation results show that the multi-step predictive control method can effectively track and compensate harmonic, reduce the harmonic component of power grid, and increase the compensation precision of parallel APF.

The aim of this paper is the implementation of a hysteresis current controller with constant switching frequency as a part of an active filtering system control algorithm, based on the indirect current control. The alternative in the literature to the hysteresis current controller is the PI controller that can give better overall performances and constant switching frequency but with the cost of comprehensive parameter tuning. A compromise can be achieved between the classical current controllers which is the hysteresis current controller with constant switching frequency. This can be obtained by combining the hysteresis comparators with the PWM suboptimal modulator. The obtained performances of the active filtering system based on the indirect current control are compared with the corresponding performances obtained by the same system implemented with the well documented PI current controller. The regulator implementation and performance comparative study were accomplished on a comprehensive active compensator system built in the Matlab Simulink environment.

The application of the internal model control structure for the digital current control of active power filters using voltage-source converters is discussed. Several issues including overshoot-free and fast reference-to-output response, effective cancellation of the source voltage disturbance, and the effect of the sample-and-hold operation on the system performance are addressed. Experimental results obtained from an active filter controlled by a TMS32040 DSP-based system, are reported.

This paper presents a hybrid simulation to test control strategies in active power filters using the generalized power tensor theory. The tensor theory is based on the dyadic or tensor product between voltage and current vectors. This new definition allows the estimate of reference currents for the control of active power filters “APFs” in multiphase systems. The hybrid simulation consists in a combination of computer simulation and laboratory tests. This approach is a cost effective alternative to physically testing the whole system and allows study the dynamic behaviour of complex engineering systems. Besides, it describes implementing an active power filter (APF) hybrid prototype where the source system and load are implemented as a real-time simulation and the active power filter is implemented in physical hardware. It also confirmed the hybrid simulation results by implementing the simulation in MATLAB-Simulink regarding the same system implemented during the active power filter analysis and design stage.

Nonmodel-based controllers have been explored for the control of a shunt active power filter (APF) designed for harmonic and reactive current mitigation. In this paper, three soft computing techniques viz; fuzzy logic, neural network, and genetic algorithm are used to design alternative control schemes for switching the APF. The models for these control schemes are designed and simulated in MATLAB. A comparative study of the results obtained using these artificial-intelligence-based schemes is presented.

This paper presents an improved hysteresis current control to enhance the performance of current tracking control for active power filter while reduce the number of switching. This control technique utilizes the advantages of the fast dynamic response of the conventional hysteresis current control and the reduced switching number of the SVM scheme. While the current errors go beyond the outer hysteresis band, a suitable space voltage vector is selected to obtain fast current response, which corresponding the vector of the current error differential is of the largest partial vector in reverse direction of current error vector. Otherwise, the low harmonic current control of SVM is selected to track the reference current and limit the current error within the specified hysteresis band. A set of space vectors including the zero vectors to reduce the number of switching is determined from the information of the middle current error. Then a proper space vector selected according to the inner current error for better current. Lastly, the validity and rapidity of the proposed method are confirmed by experimental tests.

Power Quality issues are becoming a major concern for today’s power system engineers. Large scale incorporation of non-linear loads has the potential to raise harmonic voltages and currents in an electrical distribution system to unacceptable high levels that can adversely affect the system. Active power filter (APF) based on power electronic technology is currently considered as the most competitive equipment for mitigation of harmonics and reactive power simultaneously. Instantaneous power theory is used for generation of reference current. This paper presents a comparative study of the performance of three current control strategies namely ramp comparison method, hysteresis current controller (HCC) and Adaptive hysteresis current controller (AHCC) is carried out and superiority of AHCC is established. Simulation results for all the method are presented using MATLAB/SIMULINK power system toolbox demonstrating the effectiveness of using adaptive hysteresis band.

This paper presents a novel architecture for a unit-delay digital deadbeat current controller for a shunt active power filter (APF). The APF is based on a fixed frequency pulsewidth modulated voltage-sourced converter (VSC). The proposed controller increases the APF current-tracking bandwidth without increasing the VSC switching frequency. Previous APF digital deadbeat controllers have a current-tracking delay of two or more sample-periods. One delay is due to current controller computation, a second sample delay represents VSC actuation time. The paper presents a new controller architecture employing both asynchronous programmable logic and a small microprocessor. Current-tracking feedback control calculations are executed in asynchronous programmable logic to effectively eliminate the controller computation delay. The microprocessor executes fundamental frequency disturbance rejection computations and all other supervisory functions. The proposed architecture retains all high-level functions in the microprocessor to minimize controller development time without compromising APF performance.

The paper presents a three-phase parallel active power filter without filter current measurement. Only supply grid voltage sensors, filter capacitor voltage sensor and supply line current sensors are used to provide filter’ proper operation, aiming to reduce reactive power and line current distortion, caused by a non-linear load. Due to filter’s inverter-like topology with known parameters in filter branch, the predictive direct current control (DCC) method has been successfully applied, thus obtaining good dynamic response, reducing the commutation frequency of the active power filter’s switches and consequently decreasing the filter branch losses.

This paper presents an active disturbance rejection control (ADRC) method based on radial basis function (RBF) neural network applied to current tracking control of active power filter (APF). It is difficult to accurately model the active power filter system, and the uncertainty of the nonlinear system brings difficulties to the system analysis and control. In this paper, under the ADRC framework, a tracking differentiator (TD) is introduced to obtain the differential information of the reference signal and a nonlinear extended state observer (ESO) is constructed to estimate the state variables and the total disturbance. The nonlinear ESO realizes the feedforward compensation of disturbance, and the state feedback adopts the PD form. Further, the RBF neural network is designed to estimate the unknown parameter b of the system. The simulation results show that the proposed control method has good steady-state and dynamic performance.

Model reference adaptive fuzzy control (MRAFC) is proposed to control the active power filter (APF) and model the APF system caused by nonlinear characteristics, variable parameters and external interferences. T-S fuzzy theory is utilized on the approximation of nonlinear model and the current tracking control. APF system based on MRAFC can be guaranteed to be asymptotical stable. Simulation results are included to confirm the effectiveness of the proposed controller and comparisons with APF system based on model reference adaptive control (MRAC) demonstrate that MRAFC method is capable of reducing the modeling error and tracking reference current signal accurately. Moreover, APF based on the proposed method shows the dynamic and static control performance of stronger robustness, better suitability and higher accuracy than the one based on MRAC modus.

A new finite time intelligent control strategy using an adaptive Chebyshev recurrent fuzzy neural network (ACRFNN) is proposed for the harmonic suppression of an active power filter (APF). Considering the nonlinear APF system encompasses the model uncertainties and the existence of lump external unknown disturbances in the controller design, a recursive terminal sliding mode controller (RTSMC) is proposed to improve the current loop tracking control accuracy and robustness for harmonic compensation of APF. And for the fast nonsingular terminal sliding mode surface and an integral mode surface integrated in the designed RTSMC, the tracking error achieves to converge in a finite time. In addition, to reduce the control burden of the RTSMC caused by the lump disturbances and mitigate chattering problem, a ACRFNN structurally combining recurrent neural network and Chebyshev neural network, is proposed as an approximator for the nonlinear dynamic model, and an adaptive node adjustment algorithm is introduced to the proposed neural network (NN) so that the NN structure can be further optimized. Hardware experiments are carried out to verify better performance of harmonic compensation property.

New digital reference current generation for shunt active power filter under distorted voltage conditions

Model reference adaptive sliding mode control (MRASMC) using radical basis function (RBF) neural network (NN) is proposed to control the single-phase active power filter (APF). The RBF NN is utilized to approximate nonlinear function and eliminate the modeling error. AC side model reference adaptive current controller not only guarantees the globally stability of the APF system but also generate the compensating current to track the harmonic current accurately. Moreover, a sliding mode controller based on exponential approach is designed to improve the tracking performance of DC side voltage. Simulation results demonstrate that MRASMC using RBF NN can improve the adaptability and robustness of the APF system and track the given instructional signal quickly.