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This paper addresses the problem of designing a control that maximizes the harvested energy of a wave energy converter, in the presence of displacement constraints. The feasible displacement range is split into two segments. In the first segment (the inner segment), an unconstrained optimal control is used. In the outer segment, a constraint control is used. For the unconstraint control in the inner...
Model mismatch from parameter uncertainties and disturbance is a challenge of controller design for DC-DC boost converters. To deal with this problem, a composite cascade adaptive controller is proposed in this paper. The outer loop is a PI controller combined with a feedforward compensator to generate the current signal from the output voltage reference and the inner loop is a finite horizon Model...
The modular multilevel converter (MMC) is considered among the top choices for very high-power applications due to its superior features. To operate with good performance, effective control and modulation techniques are required to suppress the detrimental effects, including the circulating current and the capacitor voltage ripples. This paper proposes an efficient variable nearest level control-model...
This paper describes the application of a simplified indirect model predictive current control strategy for a direct Matrix Converter. The direct matrix converter has a large number of available switching states which implies that the implementation of predictive control high computational cost. In this paper, a predictive current control strategy is proposed in order to simplify the computational...
The direct matrix converter has twenty-seven available switching states which implies that the implementation of predictive control techniques in this converter requires high computational cost while an adequate selection of weighting factors in order to control both input and output sides of the converter. In this paper, two indirect model predictive current control strategies are proposed in order...
In this paper, predictive speed control (PSC) of interior permanent magnet sychonous motor (IPMSM) which is based on finite control set model predictive control (FCS-MPC) is investigated. The predictive speed controller with a cascade-free structure has a excellent dynamic performance. A prediction model with speed compensation is used to predict the future states of IPMSM. Then a cost function with...
Stochastic dynamic behavior of solar energy necessitates the use of robust controllers for photovoltaic (PV) power electronics interfaces. Such robust controller maximizes the energy harvest through continuous operation using a maximum power point tracker (MPPT). A model predictive control MPPT (MPC-MPPT) is proposed in this paper for a quasi-Z-source inverter (qZSI) based grid-connected PV power...
This paper investigated and compared two types of modified model predictive control methods with finite set for six-phase PMSM MTPA control. The first one has conventional cascaded speed and current controller loops where the PI current loop is replaced with a MPC control loop. The second method uses one MPC controller in place of conventional cascaded loops for both speed and current control. The...
Finite control set model predictive control techniques are mainly distinguished by a variable switching frequency which causes noise, large voltage and current ripples at low sampling frequency. This paper presents a comparative study of two enhanced predictive current control techniques with fixed switching frequency applied to an asymmetrical six-phase induction motor drive. Simulation results are...
This paper presents an investigative work about the direct speed control (DSC) of interior permanent magnet synchronous motor (IPMSM) based on finite control set model predictive control (FCS-MPC). A compensation is applied to the speed prediction model because of the unknown load torque and varied rotary inertia. And a multi-constrained cost function with dynamically adjustable weight factors is...
Model Predictive Control (MPC) method is proposed in this paper applied to a single phase grid-connected inverter. This method uses a state-space equation of the system to predict the next time value of current from the grid side by adjusting the duty ratio of inverter in each sampling period. The duty ratio which minimizes a cost function is selected. Then, taking advantage of the duty ratio to control...
In this paper, we consider a two-players stochastic linear quadratic game framework. The game is partially observed and each player has their own private observation. The challenge is that none of the players has access to the continuum observations, rather they can access their respective observations at discrete time instances by operating a switch unanimously. The operation of the switch is costly...
This paper presents an advanced finite control set model predictive control (FCS-MPC) method, to reduce current ripple of the single-phase grid-tied inverters. Compared with the conventional FS-MPC method, the developed control method not only improves the steady-state performance of MPC but also keeps the characteristic of variable switching frequency, thus having a good EMI performance. First, it...
This paper proposes a direct model predictive current control (MPC) strategy for matrix converters (MCs). The proposed method aims to regulate the output current of the MC while minimizing the input reactive power at the same time. In addition, in order to reduce the switching losses, the MPC adjusts the average switching frequency of the converter. The MPC scheme uses the discrete-time model of the...
A model predictive current control (MPCC) of shunt active power filter (SAPF) requires tracking of distorted reference current based on the discrete mathematical model of the system. But the approximations considered in the development of mathematical model for the nonlinear system and also the uncertainty in the parameter values will deteriorate the performance of control algorithm. To enhance the...
Boost converters are widely used in several applications such as solar PV systems, energy storage systems, etc. In order to improve its dynamic performance, several model predictive control (MPC) strategies have been proposed to govern this DC-DC converter. However, in general, they require long prediction horizons to achieve a stable closed-loop due to its well-known non-minimum phase behavior. A...
A novel approach for reconfigurable control systems design against sensor and actuator faults is proposed. The scheme is based on an estimation of the state and of the fault parameters, and on a Partially Observable Markov Decision Process (POMDP), used for the decision task of the feedback controller. The following fault types are considered: locking and loss of effectiveness of the device. The modelling...
Uninterruptable power supply (UPS) applications require شa well regulated sinusoidal output voltage with low total harmonic distortion (THD). These requirements are achieved by model predictive control (MPC) of UPS inverter with LC filter on the output. The controller uses the model of the system to predict the future behavior of the controlled variables for all possible voltage vectors, and uses...
Classic finite-set model predictive control techniques are distinguished by a variable switching frequency which causes noise, large voltage and current ripple. This paper presents an enhanced predictive current control technique with fixed switching frequency applied to the six-phase drives and a Kalman Filter estimator. Simulation results are provided to show the efficiency of the current control...
Direct optimal control methods are used to obtain the time minimal trajectory for a race circuit. All states, controls, and the 5 gear switching structure of the dynamic model are completely subject to optimization. The race circuit (Nürburgring) is modeled with two cubic splines for the center line as well as the width of the track. The discrete gear choices are modeled using the outer convexification...
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