Search results for "model predictive control"
showing 5 items of 35 documents
A Model Modulated Predictive Current Control Algorithm for the Synchronous Reluctance Motor
2022
This paper proposes a Model Modulated Predictive Control (M2PC) specifically developed for Synchronous Reluctance Motors (SynRM) drives and based on a purposely developed magnetic model taking into account both self- and cross-saturation. The proposed M2PC exploits the discrete-time version of the dynamic model to compute the current prediction and the resulting predicted current error. The built-in PWM modulator chooses the optimal pair of voltage space-vector to be applied by the inverter to minimize the current error. The magnetic model permits obtaining good dynamic performance in every working condition.
A Fokker–Planck control framework for multidimensional stochastic processes
2013
AbstractAn efficient framework for the optimal control of probability density functions (PDFs) of multidimensional stochastic processes is presented. This framework is based on the Fokker–Planck equation that governs the time evolution of the PDF of stochastic processes and on tracking objectives of terminal configuration of the desired PDF. The corresponding optimization problems are formulated as a sequence of open-loop optimality systems in a receding-horizon control strategy. Many theoretical results concerning the forward and the optimal control problem are provided. In particular, it is shown that under appropriate assumptions the open-loop bilinear control function is unique. The res…
Predictive control of convex polyhedron LPV systems with Markov jumping parameters
2012
The problem of receding horizon predictive control of stochastic linear parameter varying systems is discussed. First, constant coefficient matrices are obtained at each vertex in the interior of linear parameter varying system, and then, by considering semi-definite programming constraints, weight coefficients between each vertex are calculated, and the equal coefficients matrices for the time variable system are obtained. Second, in the given receding horizon, for each mode sequence of the stochastic convex polyhedron linear parameter varying systems, the optimal control input sequences are designed in order to make the states into a terminal invariant set. Outside of the receding horizon…
An analysis of model predictive control with integral action applied to digital displacement cylinders
2020
This article aims to analyze Model Predictive Control (MPC) for the control of multi-chamber cylinders. MPC with and without integral action has been introduced. Three different algorithms have been used to solve the optimization problem in the MPC. The different algorithms have been compared with an industrial solver. The influence of changing mass, choosing a different middle line pressure, system delays, signal noise, velocity estimation, and changing pressure levels has been investigated. It is concluded that for the small prediction horizon used in the paper a simple algorithm such as A can produce results as good as the previously used Differential Evolution algorithm in less than hal…
Predictive control of networked systems with communication delays
2012
This paper studies the problem of predictive output feedback control for networked control systems with random communication delays. A networked predictive control scheme is employed to compensate for random communication delays, which mainly consists of the control prediction generator and network delay compensator. Furthermore, a new strategy of designing the time-varying predictive controller with mixed random delays for networked systems is proposed. Then the system can be formulated as a Markovian jump system. New techniques are presented to deal with the distributed delay in the discrete-time domain. Based on analysis of closed-loop networked predictive control systems, the designed p…