Search results

Power converters are an integral part of the energy conversion process in solar photovoltaic (PV) systems which is used to match the solar PV generation with the load requirements. The increased penetration of renewable invokes intermittency in the generated power affecting the reliability and continuous energy supply of such converters. DC-DC converters deployed in solar PV systems impose stringent restrictions on supplied power, continuous operation and fault prediction scenarios by continuously observing state variables to ensure continuous operation of the converter.

A converter deployed for a mission-critical application has to ensure continuous regulated output for which the converter has to ensure fault-free operation. The fault diagnostic algorithm relies on the measurement of a state variable to assess the type of fault. In the same line, a predictive controller depends on the measurement of a state variable to predict the control variable of a converter system to regulate the converter output around a fixed or a variable reference. Consequently, both the fault diagnosis and the predictive control algorithms depend on the measurement of a state variable. Once measured, the available data can be used for both algorithms interchangeably.

The objective of this work is to integrate the fault diagnostic and the predictive control algorithms while sharing the measurement requirements of both these control algorithms. The integrated algorithms thus proposed could be applied to any converter with a single inductor in its energy buffer stage.

laboratory prototype is created to verify the feasibility of the integrated predictive control and fault diagnosis algorithm. As the proposed method combine the fault detection algorithm along with predictive control, a load step variation and manual fault creation methods are used to verify the feasibility of the converter as with the simulation analysis. The value for the capacitors and inductors were chosen based on the charge-second and volt-second balance equations obtained from the steady-state analysis of boost converter.

The purpose of this paper is to propose a new type of predictive fuzzy controller. The desired nonlinear system behavior is described by a set of Takagi-Sugeno (T-S) model. However, due to the complexity of the real processes, obtaining a high quality control with a short settle time, a periodical step response and zero steady-state error is often a difficult task. Indeed, conventional model predictive control (MPC) attempts to minimize a quadratic cost over an extended control horizon. Then, the MPC is insufficient to adapt to changes in system dynamics which have characteristics of complex constraints. In addition, it is shown that the clustering algorithm is sensitive to random initialization and may affect the quality of obtaining predictive fuzzy controller. In order to overcome these problems, chaos particle swarm optimization (CPSO) is used to perform model predictive controller for nonlinear process with constraints. The practicality and effectiveness of the identification and control scheme is demonstrated by simulation results involving simulations of a continuous stirred-tank reactor.

A new type of predictive fuzzy controller. The proposed algorithm based on CPSO is used to perform model predictive controller for nonlinear process with constraints.

The results obtained using this the approach were comparable with other modeling approaches reported in the literature. The proposed control scheme has been show favorable results either in the absence or in the presence of disturbance compared with the other techniques. It confirms the usefulness and robustness of the proposed controller.

This paper presents an intelligent model predictive controller MPC based on CPSO (MPC-CPSO) for T-S fuzzy modeling with constraints.

The purpose of this paper is to implement a finite set model predictive control algorithm to a shunt (or parallel), multilevel (cascaded H-bridge) active power filter (APF). Specifically, the purpose is to get a controller that could compensate the mains current and, at the same time, to control the voltages of its capacitors. This strategy avoids the use of multiple PWM carriers or another type of special modulator, and requires a relatively low processing power.

This paper is focussed in the application of the predictive controller to a single-phase parallel APF composed for two H-bridges connected in series. The same methodology can be applied to a three-phase APF. In the DC buses of each H-bridge, a floating capacitor was connected, whose voltage is regulated by the predictive controller. The controller is composed by, first, a model for the charge/discharge dynamics for each floating capacitor and a model for the output current of the APF; second, a cost function; and third, an optimization algorithm that is able to control all these variables at the same time, choosing in each sample period the best combination of firing pulses.

The controller can track the voltage references, compensate the current harmonics and compensate reactive power with an algorithm that evaluates only the three nearest voltage levels to the last voltage level applied in the inverter. This strategy decreases the number of calculations required by the predictive algorithm. This controller can be applied to the general case of a single-phase multilevel APF of N-levels and extend it to the three-phase case without major problems.

The implemented controller, when the authors consider a constant sample time, gives a mains current with a Total Harmonic Distortion (THD-I) slightly greater in comparison with the base algorithm (that evaluates all the voltage levels). However, when the authors consider the processing times under the same processor, the implemented algorithm requires less time to get the optimal values, can get lower sampling times and then a best performance in terms of THD-I. To implement the controller in a three-phase APF, a faster Digital Signal Processor would be required.

The implemented solution uses a model for the charge/discharge of the capacitors and for the filter current that enable to operate the cascaded multilevel inverter with asymmetrical voltages while compensates the mains currents, with a predictive algorithm that requires a relatively low amount of calculations.

Five-level rectifiers have received widespread attention because of their excellent performance in high-voltage and high-power applications. Taking a five-level rectifier with only four-IGBT for this study, a sliding mode predictive control (SMPC) algorithm is proposed to solve the problem of poor dynamic performance and poor anti-disturbance ability under the traditional model predictive control with the PI outer loop.

First, mathematical models under the two-phase stationary coordinate system and two-phase synchronous rotating coordinate system are established. Then, the design of the outer-loop sliding mode controller is completed by establishing the sliding mode surface and design approach rate. The design of the inner-loop model predictive controller was completed by discretizing the mathematical model equations. The modulation part uses a space vector modulation technique to generate the PWM wave.

The sliding mode predictive control strategy is compared with the control strategy with a PI outer loop and a model predictive inner loop. The proposed control strategy has a faster dynamic response and stronger anti-interference ability.

For the five-level rectifier, the advantages of fast dynamic influence and parameter insensitivity of sliding mode control are used in the voltage outer loop to replace the traditional PI control, and which is integrated with the model predictive control used in the current inner loop to form a novel control strategy with a faster dynamic response and stronger immunity to disturbances. This novel strategy is called sliding mode predictive control (SMC).

Flying‐capacitor multilevel converters (FCC) need a passive or active regulation of the capacitor voltages. Recently the trend is towards active control, often implemented separately from the current control. The advantages of a true multi‐variable control sparked the interest to apply Model Based Predictive Control (MBPC) for FCC. In this paper an objective analysis method to evaluate the effects of several design choices is presented. The effects of the weight factor selection, model simplification, and prediction horizon expansion for MBPC of a 3‐level FCC are analyzed in a systematical way.

The analysis is mainly based on the mean square error (MSE) of current and capacitor voltage. The results are analysed for different lengths of the prediction horizon and for a wide range of weight factor values. Similarly the effect of a model simplification, neglecting the neutral point voltage, is studied when implementing MBPC for FCCs while considering the computational aspects. Validation of the simulation results is done by experiments on an FPGA‐based setup.

Including the effect of the neutral point voltage considerably increases the current control quality and a much wider range of good values for the weight factor exists. As this good range is not critically dependent on the current amplitude it is possible to select one weight factor value for all operating points. Furthermore, it is concluded that increasing the prediction horizon increases the computational load without improving the control quality.

The effects of increasing the prediction horizon when including other controlled variables is to be investigated, as well as the robustness to modeling errors. The MSE analysis methodology is very suitable for this further research.

For practitioners of MBPC in power electronics the paper proves that by means of simulations and the MSE one value for weight factor can be chosen for all operating points. The paper clearly shows that a practical implementation is feasible and demonstrates that neglecting the neutral point voltage is not good practice.

The MSE‐based analysis is shown to be a systematical and unbiased methodology to evaluate the effects of design choices. The results from this analysis can be directly applied in practical setups.

Maintaining a balanced neutral point, reducing power loss, execution time are important criteria for the controlling of neutral point clamped (NPC) inverter. However, it is tough to meet all the challenges and also supplying the load current within the harmonic limit. This paper aims to maintain load current quality within the Institute of Electrical and Electronics Engineers 519 standard and meet the above-mentioned challenges.

The output load current of a three-level simplified neutral point clamped (3 L-SNPC) inverter is controlled in this paper using model predictive control (MPC). The 3 L-SNPC inverters is considered because fewer semiconductor devices are used in this topology; this will enhance the reliability of the system. MPC is used as a controller because it can handle the direct current-link capacitors’ voltage balancing problem in a very intuitive way. The proposed 3 L-SNPC yields similar current total harmonic distortion (THD), transient and steady-state responses, voltage stress and over current protection capability as the conventional NPC inverter. To reduce the computational burden of the proposed SNPC system, two simplified MPC strategies are proposed, namely, single voltage vector prediction-based MPC and selective voltage vector prediction-based MPC.

The system shows a current THD of 2.33% at 8.96 kHz. The overall loss of the system is reduced significantly to be useful in medium power applications. The required execution times for the simplified MPC strategies are tested on the hardware dSPACE 1104 platform. It is found that the single voltage vector prediction-based MPC and the selective voltage vector prediction-based MPC are computationally efficient by 8.28% and 62.9%, respectively, in comparison with the conventional MPC-based conventional NPC system.

Multiple system constraints are considered throughout the paper and also compare the SNPC to the conventional NPC inverter. Proper current tracking, over-current protection, overall power loss reduction especially switching loss and maintaining capacitor voltages balance at a neutral point are achieved. The improvement of execution time has also been verified and calculated using hardware-in-loop of the dSPACE DS1104 platform.

A new control method is proposed for grid integration of improved hybrid three quasi z source converter (IHTQZSC). The proposed controller provides a constant switching frequency with an improved dynamic response with fewer computations. The proposed constant switching frequency predictive controller (CSF-PC) does not need weighting factors and reduces the complexity of the control circuit.

A single PI controller is intended to control voltage across dc-link by generating the necessary shoot-through duty ratio. The predictive controller produces the modulating signals required to inject the desired grid current. The performance of the proposed controller is validated with MATLAB/Simulink software.

The discrete-time instantaneous model on the grid side in the proposed controller influences the inductor current with minimum ripples. Dynamic response and computational complexity of the converter with the PI controller, finite set model predictive controller (FS-MPC) and the proposed controller are discussed.

The converter belongs to impedance source converters (ISC) family, delivers higher voltage gain in a single-stage power conversion process, extract the energy from the intermittent nature of renewable energy conversion systems. Implementing CSF-PC for ISC is simple, as it has a single PI controller.

Grid integration of high voltage gain IHTQZSC is accomplished with PI, FS-MPC and CSF-PC. Though the FS-MPC exhibits superior dynamic response under input voltage disturbance and grid current variation, total harmonic distortion (THD) in the grid current is high. CSF-PC provides better THD with a good dynamic response with reduced inductor current ripples.

The purpose of this paper is to present a complete solution for speed sensorless AC drive with voltage source inverter, induction machine, and motor choke. Major problems with adjustable speed drives are underlined and the use of motor choke is justified. An AC drive with motor choke can work only if specific modifications in the control algorithms are done.

The goal of the paper is to present new nonlinear vector control method for induction motor drive. In the control system, the presence of motor choke is taken into account. The choke changes the structure of the predictive controller and state observer. The new concept of integrating the predictive controller with electromagnetic forces observer is presented. The paper presents theoretical description of the system as well the simulation and experimental verification.

The paper shows that the suggested decoupled AC drive control system is operating better than a system without decoupling. The system with motor choke requires modifications in the current controller and observer system. With omitting the motor choke a speed sensorless drive cannot work properly.

The solution is oriented for industrial applications because in numerous industrial dives the motor choke is utilized. However, with motor choke many sophisticated control algorithms cannot work properly. The concept presented in the paper solves such practical problems.

The paper presents a completely new decoupled field‐oriented control system with load angle controller, predictive current controller and state observer for AC drive with motor choke.

Predictive current control (PCC) of three-to-five-phase direct matrix converters (DMCs) is computationally expensive. For this reason, this study aims to consider a reduced number of switching states of DMC in PCC algorithm to predict the control objectives, such as output current control and input reactive power control.

The switching sequences which yield the voltage vectors of variable amplitude at a constant frequency in space are considered for the prediction and optimization step of PCC algorithm. For the selected voltage vectors, the phase angles of the output vectors are independent on the phase angles of the input vectors. In a three-to-five-phase DMC, there are 243 valid switching states. Among the switching states, only 91 states are considered using the aforementioned concept of variable amplitude output at a constant frequency. This reduced number of switching states simplifies the computational complexity of MPC based current control of three-to-five-phase DMC.

The computational complexity of the proposed PCC based DMC is lower than the all 243 vectors based PCC. The current total harmonic distortion, transient current response and input reactive power control for the simplified 91 vector based PCC are similar to the all 243 vectors based PCC.

A reduced number of switching sequence is considered for the prediction and optimization step of PCC algorithm. Hence, PCC algorithm can be sampled at a high frequency in real-time applications. Then, the performance of the PCC will be improved.

The purpose of this paper is to propose an efficient current control technique based on model predictive control (MPC) for grid-connected wind conversion system. This nonlinear strategy is applied for the chopper circuit and grid-tied inverter and compared with other two conventional schemes; a traditional proportional-integral (PI) and sliding mode controller (SMC) using the same switching frequency.

Firstly, the MPC scheme uses the mathematical model to predict future behaviors of the controlled converter outputs for possible switching states. After that, the optimal voltage vector is selected by minimizing a cost function, which is defined as a sum of the absolute values of the controlled current errors. Then, the corresponding switching signals are applied to the converter switches in the next sampling period to track correctly the reference current. Thus, the MPC scheme ensures a minimal error between the predicted and reference trajectories of the considered variables.

The MPC-based algorithm presents several benefits in terms of high accuracy control, reduced DC-link voltage ripples during steady-state operation, faster transient response, lower overshoots and disturbance rejection and acceptable total harmonic distortion.

The authors introduce several simulation case studies, using PSIM software package, which prove the reliability and effectiveness of the proposed MPC scheme. Therefore, the MPC performances, during dynamic and steady-state condition, are compared with those obtained by a PI regulator and SMC to highlight the improvements, specifically the transfer of smooth power to the grid.