• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.2
• /
• pp.308-313
• /
• 2018

In this paper, we propose a sampled-data model predictive tracking control deign for leader-following control of multi-mobile robot system. The error dynamics of leader-following robots is modeled as a Linear Parameter Varying (LPV) model. Also, the Lyapunov function is presented to guarantee stability of the networked control system. Based on the stabilization condition using a quadratic Lyapunov function approach, model predictive sampled-data controller is designed. Finally, the leader-following control of multi mobile robots is simulated to show effectiveness of the proposed method.

• Advances in robotics research
• /
• v.1 no.1
• /
• pp.41-59
• /
• 2014

This paper deals with the problem of steering a group of mobile robots along a reference path while maintaining a desired geometric formation. To solve this problem, the overall formation is decomposed into numerous geometric patterns composed of pairs of robots, and the state of the geometric patterns is defined. A control algorithm for the problem is proposed based on the Nash equilibrium strategies incorporating receding horizon control (RHC), also known as model predictive control (MPC). Each robot calculates a control input over a finite prediction horizon and transmits this control input to its neighbor. Considering the motion of the other robots in the prediction horizon, each robot calculates the optimal control strategy to achieve its goals: tracking a reference path and maintaining a desired formation. The performance of the proposed algorithm is validated using numerical simulations.

• Journal of Power Electronics
• /
• v.18 no.5
• /
• pp.1458-1469
• /
• 2018

This paper proposes a novel common-mode voltage (CMV) elimination (CMV-EL) method based on model predictive control (MPC) to eliminate CMV for three-level T-type inverters (3LT2Is). In the proposed MPC method, only six medium and one zero voltage vectors (VVs) (6MV1Z) that generate zero CMV are considered as candidates to perform the MPC. Moreover, the influence of dead-time effects on the CMV of the MPC-based 6MV1Z method is investigated, and the candidate VVs are redesigned by pre-excluding the VVs that will cause CMV fluctuations during the dead time from 6MV1Z. Only three or five VVs are included to perform optimization in every control period, which can significantly reduce the computational complexity. Thus, a small control period can be implemented in the practical applications to achieve improved grid current performance. With the proposed CMV-EL method, the CMV of the $3LT^2Is$ can be effectively eliminated. In addition, the proposed CMV-EL method can balance the neutral point potentials (NPPs) and yield satisfactory performance for grid current tracking in steady and dynamic states. Simulation and experimental results are presented to verify the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.3
• /
• pp.235-244
• /
• 2014

This article introduces recent trends in RHC (Receding Horizon Control), also known as MPC (Model Predictive Control), that has been well recognized in industry and academy as a systematic approach for optimal design and constraint management. Constrained and robust RHCs will be briefly reviewed with milestone results. Among the diverse developments and achievements of RHCs, implementation issues will be focused on, together with the latest applications. In particular, this article introduces results on how to solve a finite horizon open-loop optimal control problem in an efficient way, together with code generation for real-time execution and easy implementation. Instead of traditional applications such as refineries and petrochemical plants, this article highlights some selected emerging applications, such as energy management systems and mechatronics, that have resulted from state-of-the-art high performance computing power and advanced numerical schemes.

• Nuclear Engineering and Technology
• /
• v.44 no.4
• /
• pp.369-378
• /
• 2012

A load-following operation in APR+ nuclear plants is necessary to reduce the need to adjust the boric acid concentration and to efficiently control the control rods for flexible operation. In particular, a disproportion in the axial flux distribution, which is normally caused by a load-following operation in a reactor core, causes xenon oscillation because the absorption cross-section of xenon is extremely large and its effects in a reactor are delayed by the iodine precursor. A model predictive control (MPC) method was used to design an automatic load-following controller for the integrated thermal power level and axial shape index (ASI) control for APR+ nuclear plants. Some tracking controllers employ the current tracking command only. On the other hand, the MPC can achieve better tracking performance because it considers future commands in addition to the current tracking command. The basic concept of the MPC is to solve an optimization problem for generating finite future control inputs at the current time and to implement as the current control input only the first control input among the solutions of the finite time steps. At the next time step, the procedure to solve the optimization problem is then repeated. The support vector regression (SVR) model that is used widely for function approximation problems is used to predict the future outputs based on previous inputs and outputs. In addition, a genetic algorithm is employed to minimize the objective function of a MPC control algorithm with multiple constraints. The power level and ASI are controlled by regulating the control banks and part-strength control banks together with an automatic adjustment of the boric acid concentration. The 3-dimensional MASTER code, which models APR+ nuclear plants, is interfaced to the proposed controller to confirm the performance of the controlling reactor power level and ASI. Numerical simulations showed that the proposed controller exhibits very fast tracking responses.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.530-535
• /
• 2004

This paper considers a state set estimation (SSE) based model predictive control (MPC) for linear parameter- varying (LPV) systems with input constraint. We estimate, at each time instant, a feasible set of all states which are consistent with system model, measurements and a priori information, rather than the state itself. By combining a state-feedback MPC and an SSE, we design an SSE-based MPC algorithm that stabilizes the closed-loop system. The proposed algorithm is solved by semi-de�nite program involving linear matrix inequalities. A numerical example is included to illustrate the performance of the proposed algorithm.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.22 no.6
• /
• pp.476-483
• /
• 2017

In this paper, a voltage-based model predictive control (MPC) scheme for a modular multilevel converter is used to reduce switching loss. The proposed method calculates an offset voltage that clamps the switching operation of submodules in which the current greatly flows at every sampling period by using the reference phase voltage and the reference phase current. To use the offset voltage, the proposed method converts the current-based MPC to the voltage-based MPC. The proposed voltage-based MPC then generates a new reference pole voltage that clamps the switching of submodules by applying the calculated offset voltage to the phase voltage. Therefore, the proposed method can reduce the switching loss by stopping the switching operation of submodules in which the current greatly flows. The switching loss reduction effect of the proposed method is verified by comparing its loss data with those of the conventional MPC method.

• Proceedings of the KIPE Conference
• /
• 2017.07a
• /
• pp.268-269
• /
• 2017

This paper presents an improved current control strategy for a three-phase grid-connected inverter under distorted grid conditions. Distorted grid condition is undesirable due to negative effects such as power losses and heating problem in electrical equipments. To enhance the power quality of distributed generation systems under such a condition, a modulated finite control set - model predictive control (MFCS-MPC) scheme will be proposed, in which the optimal switching signals of inverter are chosen by online basis using the principle of current error minimization. In addition, the moving average filter (MAF) is used to improve the phase-lock loop in order to obtain the harmonic-free reference currents on the stationary frame. The usefulness of the proposed MFCS-MPC method is proved by the comparative simulation results under different operating conditions.

• Journal of Navigation and Port Research
• /
• v.47 no.2
• /
• pp.66-74
• /
• 2023

With the increase of interest in developing Maritime Autonomous Surface Ships (MASS), an optimal ship route planning is gradually gaining popularity as one of the important subsystems for autonomy of modern marine vessels. In the present paper, an optimal ship route planning model for MASS is proposed using a nonlinear MPC approach together with a nonlinear MMG model. Results drawn from this study demonstrated that the optimization problem for the ship route was successfully solved with satisfaction of the nonlinear dynamics of the ship and all constraints for the state and manipulated variables using the nonlinear MPC approach. Given that a route generation system capable of accounting for nonlinear dynamics of the ship and equality/inequality constraints is essential for achieving fully autonomous navigation at sea, it is expected that this paper will contribute to the field of autonomous vehicles by demonstrating the performance of the proposed optimal ship route planning model.

• Journal of Power Electronics
• /
• v.17 no.4
• /
• pp.983-990
• /
• 2017

This paper proposes a model predictive control based on the discrete Lyapunov function to improve the performance of power electronic converters. The proposed control technique, based on the finite control set model predictive control (FCS-MPC), defines a cost function for the control law which is determined under the Lyapunov stability theorem with a control error compensation. The steady state and dynamic performance of the proposed control strategy has been tested under a single phase AC/DC voltage source rectifier (S-VSR). Experimental results demonstrate that the proposed control strategy not only offers global stability and good robustness but also leads to a high quality sinusoidal current with a reasonably low total harmonic distortion (THD) and a fast dynamic response under linear loads.