Modified Model Predictive Control Scheme Research Articles

A modified model predictive control method for frequency regulation of microgrids under status feedback attacks and time-delay attacks

As a promising technology to integrate renewable energy and enable decentralized energy management, microgrid (MG) offers an appealing network architecture due to its potential economic, environmental, and technical benefits. However, with the increasing deployment of intelligent devices and the growing network interconnectivity, communication channels and controllers for MGs become more vulnerable to emerging cyber threats. Two types of attacks are considered in this paper, including the data integrity attacks on the system status feedback and time-delay attacks which may disrupt the control of the MGs and lead to adverse consequences. A modified model predictive control (MPC) scheme is proposed for the secondary frequency control of MGs based on the online status switching method and generalized cross correlation (GCC) estimation to detect the real system status and time delay injected to the control system. The Euclidean metric is used in the online status switching method to obtain the real system states. Meanwhile, the GCC based delay estimation is developed to detect and track the time delay posed by attacks in the real-time operation. Case studies under different scenarios of the attacks are conducted, and the simulation results verify the effectiveness of the proposed MPC scheme under the cyberattacks.

Parameter-disturbance-robust model predictive control of input-saturated MIMO fractional systems

This paper primarily discusses the solution to multi-degree of freedom linear time invariant fractional order dynamic systems with fractional actuators in detail. This solution is of significant importance due its ease of usage and compatibility with digital systems. Subsequently, a modified model predictive control (MMPC) scheme is introduced that is an infusion of a novel discrete-time robust sliding mode control and model predictive control. The proposed modified model predictive control algorithm is proven to illustrate robustness against uncertainty in system’s parameters and external disturbance while abstaining from the undesirable characteristics of sliding mode control such as chattering. By employing the MMPC scheme, it is possible to constrain the control inputs to be less than pre-determined bounds and by this mean, take a step toward making this algorithm more suitable for practical applications. A general and illustrious plant, represented by the famous Torvik’s three parameter model, is selected and the proposed control scheme is applied to further elucidate the merits, qualities and capabilities of MMPC for fractional systems. The corresponding MATLAB code for the simulation section is also presented in the appendix of the paper. A discussion is also included that examines the effectiveness of MMPC and provides insights for future works.

Transient uniformity model predictive control in dealing with non-uniformity of multivariable systems

In this article, the model predictive control scheme is studied for a class of multiple-input multiple-output linear systems with different transient trajectories among the outputs. To eliminate the transient errors among the outputs, a modified model predictive control scheme is designed making one output track following the reference while the other outputs track following this output instead of the reference. Utilizing the specified output as the alternative reference for all the other outputs, a constructive model predictive control scheme is developed to diminish the differences of the transient-state trajectories among each output such that both the uniformity of the transient-state trajectories and the optimal steady-state trajectories are achieved. The effectiveness of the proposed transient uniformity model predictive control scheme is demonstrated in the experiment of the semiconductor wafer manufacturing baking process. The experimental results show that the transient uniformity model predictive control scheme has successfully reduced the integral square error of transient-state uniformity between any two outputs by 90% as compared to the conventional model predictive control scheme. The robustness of the proposed scheme has also been experimentally evaluated in the presence of external disturbance and plant modeling inaccuracy.

Modified Model Predictive Control for Bidirectional Four-Quadrant EV Chargers With Extended Set of Voltage Vectors

This paper presents a modified model predictive control (MMPC) for bidirectional power flow control between the electric vehicle (EV) chargers and the main grid. In contrast to the conventional finite control set MPC which selects an optimal switching state from eight possible voltage vectors, the proposed MMPC is based on the application of an optimal voltage vector chosen from an extended set of 20 modulated voltage vectors with a fixed duty ratio. To reduce the computational burden introduced by the increased number of voltage sets, a preselection algorithm is developed for the MMPC method. Six voltage vectors are preselected from the 20 sectors. Due to the increased number of the voltage space vectors, the grid currents and active and reactive power performance can be improved by using the proposed MMPC scheme. Both the conventional and proposed methods are compared through experimental test results of a two-level three-phase off-board EV charger.

Modified Model Predictive Control of Back-to-Back T-type NPC Converter Interfacing Wind Turbine-Driven PMSG and Electric Grid

In this paper, a modified model predictive control (MMPC) scheme is proposed for controlling a back-to-back (BTB) T-type neutral-point-clamped converter (TNPCC). The BTB TNPCC ties a permanent magnet synchronous generator (PMSG) to an electric grid. The PMSG is driven by a variable speed wind turbine. The aim of the proposed method is to mitigate the CMV not only on wind generator-side and but also on grid-side of BTB TNPCC and to reduce the computation effort. Classical MPC (CMPC) algorithms CMPC-I/CMPC-II and MMPC algorithms MMPC-I/MMPC-II are modeled, implemented and compared for two cases: zero CMV on GS/WGS of BTB TNPCC. The simulation results confirm that the MMPC scheme shows similar or slightly improved performance than that of CMPC scheme while accomplishing the following control goals: maximum power point tracking, reactive power control, DC-link voltage control, DC-link capacitors voltage balancing, and CMV mitigation. Moreover, the MMPC strategy shows additional advantages: It reduces a) the computational effort b) the peak CMV on the GS and keeps zero CMV on the WGS, or vice versa. Sensitivity tests are performed to analyze the performance of proposed algorithms in a complex scenario, where both GS and WGS inductance parameters are underestimated/overestimated concurrently. The MMPC strategy has been validated experimentally on an FPGA controller.

Wind turbine control based on a modified model predictive control scheme for linear parameter‐varying systems

This study presents a successful application of a model predictive control (MPC) design approach based on linear parameter-varying (LPV) models subject to input/output constraints to control a utility-scale wind turbine. The control objectives are to allow the wind turbine to extract from the wind the rated power taking into account the wind speed variation, to reduce mechanical loads and power fluctuations and to guarantee the stability of the system for the whole range of operation. A modified min-max MPC-LPV scheme is proposed to compute online the optimal control input at each sampling instant by solving an optimisation problem subject to linear matrix inequality constraints. To reduce the conservatism of the original MPC scheme due to the overbounding associated with affine parameter-dependence, the full block S-procedure with a linear fractional transformation formulation is used. The performance and the efficiency of the proposed MPC-LPV algorithm is validated via simulation and compared with the original scheme and other conventional controllers.

Path Following of Marine Surface Vessels Using Bow and Aft Rudders in Wave Fields

This paper investigates the feasibility of using both bow and aft rudders to achieve better maneuverability and path following performance of marine surface vessels in waves. A nonlinear maneuvering model for the S175 containership is first introduced to facilitate the evaluation of path following performance. The original aft rudder is then replaced by the new bow-aft rudder combination. Open-loop simulation result shows that the new design can make the ship more maneuverable with a smaller total rudder area. For the path following controller design, the model predictive control (MPC) approach is adopted to enforce the rudder actuation constraints. In order to achieve offset-free path following in waves, a modified MPC scheme is proposed where a linear quadratic regulator (LQR) is used to first stabilize the system so that the offset-free MPC scheme can be further applied. Simulations confirm the validity of the hybrid scheme and the path following performance using both bow and aft rudders appears to be better.

A modified model predictive control scheme

In implementations of MPC (Model Predictive Control) schemes, two issues need to be addressed. One is how to enlarge the stability region as much as possible. The other is how to guarantee stability when a computational time limitation exists. In this paper, a modified MPC scheme for constrained linear systems is described. An offline LMI-based iteration process is introduced to expand the stability region. At the same time, a database of feasible control sequences is generated offline so that stability can still be guaranteed in the case of computational time limitations. Simulation results illustrate the effectiveness of this new approach.