A New High Gain DC-DC Converter With Model-Predictive-Control Based MPPT Technique for Photovoltaic Systems

Abstract Control design for a helicopter is a challenging problem because of its non-affine inputs, complicated dynamics and it is an under-actuated system. To solve a control problem of the helicopter under model uncertainties and disturbance present environments, an Explicit Nonlinear Model Predictive Control (ENMPC), a dynamic inversion and an Extended High-Gain Observers (EHGO) are combined in a multi-time-scale fashion. The multi-time scaled structrue and the ENMPC provides the framework of the control design, the dynamic inversion deals with non-affine control inputs, and the EHGO estimates the unmeasured states and uncertainties. In addition, a discretization scheme using the saturation and adding low pass filters to the control inputs is presented. Finally, the numerical simulation of a fixed sampling period has been carried out to demonstrate the validity of the proposed multi-time-scale control design and the discretization scheme.

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MPPT of Photovoltaic Systems Using Sensorless Current-Based Model Predictive Control

IEEE Transactions on Industry Applications ◽

10.1109/tia.2016.2623283 ◽

2017 ◽

Vol 53 (2) ◽

pp. 1157-1167 ◽

Cited By ~ 71

Author(s):

Morcos Metry ◽

Mohammad B. Shadmand ◽

Robert S. Balog ◽

Haitham Abu-Rub

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Photovoltaic Systems

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Model predictive control for three-level boost converter in photovoltaic systems

2017 North American Power Symposium (NAPS) ◽

10.1109/naps.2017.8107188 ◽

2017 ◽

Cited By ~ 3

Author(s):

Zhicheng Guo ◽

Mahyar Zarghami ◽

Shiying Hou ◽

Jianfei Chen

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Boost Converter ◽

Photovoltaic Systems

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Finite control set model predictive control to balance DC-link capacitor voltage for TType NPC inverter of grid-connected photovoltaic systems

Science and Technology Development Journal ◽

10.32508/stdj.v18i3.880 ◽

2015 ◽

Vol 18 (3) ◽

pp. 5-17

Author(s):

Dzung Quoc Phan ◽

Tuyen Dinh Nguyen ◽

Nhat Minh Nguyen

Keyword(s):

Model Predictive Control ◽

Cost Function ◽

Predictive Control ◽

Switching Frequency ◽

Photovoltaic Systems ◽

Delay Compensation ◽

Capacitor Voltage ◽

Finite Control ◽

Control Set ◽

The Cost

This paper proposes the Finite control set Model Predictive Control (FCS-MPC) with delay compensation for three-phase threelevel T-Type NPC inverter (T-Type NPC) of grid-connected photovoltaic systems (PV). The proposed FCS-MPC controls the objectives: current tracking control, DC-link capacitor voltage balance, the reduction of switching frequency to ensure issues of the power quality and improve the efficiency of grid-connected of PV system. The cost function of the proposed FCS-MPC uses the 27 possible switching states generated by TType NPC, the optimal switching state is selected in each sampling time that minimizes the cost function. The proposed FCS-MPC has also proposed the delay compensation with two-step prediction horizon at time k+2 to reduce the total harmonic distortion (THD) of the grid current. The proposed FCS-MPC is verified by using Matlab/Simulink.

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Explicit nonlinear model predictive control tracking control based on a sliding mode observer for a quadrotor subject to disturbances

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331219865816 ◽

2019 ◽

Vol 42 (2) ◽

pp. 214-227 ◽

Cited By ~ 2

Author(s):

Nadia Miladi ◽

Habib Dimassi ◽

Salim Hadj Said ◽

Faouzi M’Sahli

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Nonlinear Model ◽

Trajectory Tracking ◽

Tracking Control ◽

Sliding Mode ◽

High Gain ◽

Sliding Mode Observer ◽

Nonlinear Model Predictive Control ◽

Control Approach

In this paper, we propose an explicit nonlinear model predictive control (ENMPC) method based on a robust observer to solve the trajectory tracking problem for outdoor quadrotors. We take into consideration the external aerodynamic disturbances present in the dynamics of the Newton-Euler quadrotor model. To overcome the effects of these disturbances, a high gain observer combined with a first order sliding mode observer are proposed to estimate both the states and the unknown disturbances using the only positions and angular measurements of the quadrotor. The estimated signals are then used by the predictive controller in order to ensure the trajectory tracking objective. Despite the presence of bounded disturbances, the convergence of the composite controller (ENMPC technique with the latter observers) is guaranteed through a stability analysis. Theoretical results are validated with some numerical simulations showing the good performances of the proposed tracking control approach.

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Model Predictive Control for Compliant Pneumatic Systems

Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing ◽

10.1115/dscc2014-6206 ◽

2014 ◽

Author(s):

Hannes G. Daepp ◽

Wayne J. Book

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Sliding Mode ◽

Good Control ◽

Variable Stiffness ◽

High Gain ◽

Peak Performance ◽

Compliant Systems ◽

Precision Tracking ◽

Performance Capability

Pneumatic systems possess inherent compliance and potentially variable stiffness that make them an appealing actuator choice for tracking applications where contact and interaction are likely. However, good control of pneumatic systems is impeded by discontinuous and nonlinear dynamics, especially compliance and friction. The most successful previous solutions have either applied high-gain PD or sliding mode control. These achieve tracking control for compliant systems by transforming them into stiffer ones. Model predictive control can better balance precision tracking with compliance (low output impedance), so that the system is safer in case of collision disturbance. It can be coupled with a predictive observer that estimates friction as a known disturbance. The estimate is incorporated into the optimization, improving friction compensation for pneumatics, which has slow dynamics that do not react quickly enough with traditional feedforward compensation. Finally, predictive control enables constrained finite-time optimization, driving the system closer to its peak performance capability.

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