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This paper proposes an improvement of the finite control set model predictive control (FCS-MPC) strategy for enhancing the voltage regulation performance of a voltage source converter (VSC) used for standalone microgrid and uninterrupted power supply (UPS) applications. The modification is based on tracking the voltage reference trajectory derivative using a single step prediction horizon. The main...
A cruise and headway control strategy using distributed model predictive control, developed for a vehicle platooning application is proposed in this paper. The cruise control (i.e. driving the vehicle with a constant velocity demanded by the driver) is designed for the platoon's leading vehicle, whereas for the rest of the platoon, a headway control strategy is developed. Thus, the control objective...
Present paper demonstrates the effectiveness of the predictive deadbeat current control for Permanent Magnet (PM) Brushless (BL) DC motor drive in injection of square-wave phase current even at higher speed as compared to conventional PI controller employed for phase current control. Effectiveness has been demonstrated in terms of capability of minimizing current ripples and torque ripples ensuring...
The modified (due to ergodic hypothesis using) Poincaré transversal cutting surface method is proposed for studying control effectiveness from data of a “passive” experiment. The obtained quasi-recurrence-plots map makes it possible to identify lagging and successfully developing regions according to achieved level of the density of the population and level of human development.
The multi-agent monitoring (surveillance) problem over graphs is to find trajectories of multiple agents that travel each node as evenly as possible. This problem has several applications such as city safety management and disaster rescue. in our previously proposed method, the finite-time optimal surveillance problem was formulated, and was reduced to a mixed integer linear programming (MILP) problem...
This paper deals with dynamic collision avoidance of multiple mobile robots by model predictive control (MPC). Each robot has the same control law based on an MPC problem which has constraints on avoidance of other robots. A numerical example shows that a robot can reach to a goal point from a start point while avoiding collision with another robot that follows its start and goal points.
In many control applications, it is desired to repeat the same control task numerous times with identical reference trajectories. As long as only model inaccuracies and disturbances, which are practically identical for each new execution, appear as external uncertainty, such tasks are well suited for the implementation of learning-type strategies. The fundamental idea of such controllers is not only...
The paper presents the outline of the didactical project of a complex computer controlled system realized by the first degree students of the Automatics and Robotics on the Faculty of Electrical and Control Engineering (FoEaCE) in Gdansk University of Technology (GUT). The synthesis, implementation and analysis of a multilayer hierarchical control system for drinking water supply system (DWSS) are...
This paper presents a novel approach for timeoptimal model predictive control. In contrast to a global uniform time scaling, the underlying optimal control problem rests upon a dynamic, local temporal discretization of the shooting grid. The approach seeks for a grid partition with minimum overall transition time. Furthermore, a multi-stage optimization iteratively adapts the number of grid points...
Model-based predictive control is an effective method for control the large scale systems. Method is based on on-lin solution of control task over the control horizon using current and past measurements as well as the system model. Because model and measurement uncertainty, predicted and plant outputs might be different and plant output may exceed plant output constraints. Generated control is not...
A method based on variable horizon predictive control is proposed in the paper for nominal trajectory guidance. Firstly, a feasible reference trajectory is generated by the Gauss pseudospectral method. Then, curvature is employed to represent the smoothness of obtained trajectory and predictive horizon is selected according to the curvature. Different predictive control optimal problems are established...
The rapid improvement of computational power and performances of embedded systems, combined with development of new optimization algorithms with reduced complexity extends the application area of model predictive control. In this paper we describe a method of developing a model predictive controller which can be deployed on general purpose microcontroller without a floating-point unit and used to...
In this paper, we consider the problem of predictive control for a class of coupled linear systems. By solving a set of local optimization problems with decoupled cost functions and constraints, an event-triggered decentralized predictive control (DPC) scheme is proposed. The event-triggering conditions only involving local information of every subsystem is derived and sufficient conditions of the...
A difficulty still hindering the widespread application of Model Predictive Control (MPC) methodologies, remains the computational burden that is related to solving the associated Optimal Control (OC) problem for every control period. In contrast to numerous approximation techniques that pursue acceleration of the online optimization procedure, relatively few work has been devoted towards shifting...
This paper concerns the distributed model predictive control (DMPC) problem for nonlinear multirate networked systems subject to asynchronous communication. The asynchronization of communication between each subsystem always exists in mechanic engineering and chemical processes. The motivation of this paper is to use the asynchronous information to improve closed-loop performance for a class of networked...
In this paper, the trajectory tracking control problem with model predictive control approach is investigated for Unmanned Underwater Vehicle (UUV) control. Firstly, the kinematic tracking controller based on model predictive control (MPC) is applied to reach the tracking control in a kinematic way. Compared with conventional backstepping control, MPC can solve the speed jump control problem very...
Direct model predictive control (MPDxC) appears to be a strong candidate for high-power applications, because it can achieve very low switching frequencies and keep variables of concern, such as power, current, torque and flux, within specified bounds. The width of bounds is observed to regulate THD of a current when MPDxC is used for controlling the current. This paper describes mathematically the...
Controlling the motion of multiple miniature objects independently and simultaneously is a grand challenge in microrobotics. In this paper, we report our recent achievements in acoustic manipulation that can control the motion of multiple objects simultaneously and independently on a centrally actuated vibrating plate. By employing spatially highly nonlinear excitation fields on the plate, we can...
Mobile robots are remarkable cases of high development technology and systems. Robot community developed a complex analysis to meet the increased demands for the control challenges for the movement of Robot. A model predictive control (MPC) approach is used in combination with feedforward Controller in a context of decoupling controller. Implementation of this algorithm in the ROS system is presented...
This article proposes a control strategy based on the constrained generalized predictive control (GPC) in combination with a geometric attitude controller for trajectory tracking of the quadcopter vehicle. The generalized predictive control approach allows tracking time varying trajectories using optimal control actions to meet constraints on the desired trajectory. The geometric attitude controller...
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