Model predictive control (MPC) has been successfully applied to many transportation systems. For the control of overhead cranes, existing MPC approaches mainly focus on improving the regulation performance, such as tracking error or steady-state error. In this paper, energy efficiency as well as safety is newly considered in our proposed MPC approach. Based on the system model designed, the MPC...

A scheme for temperature control of a greenhouse is proposed. The present work proposes an approach based on a combination of two different control schemes: Feedback Linearization (FL) and standard linear Model Predictive Control (MPC), using their advantages. The treated greenhouse is considered a nonlinear Single-Input Single-Output process and subjected to strong external disturbances. Since...

this paper develops new results on the use of model predictive control to regulate the attitude of a ground station antenna. two degree of freedom az-el pedestal is considered as ground station antenna. permanent magnet synchronous motors are taken into consideration as the best choice for satisfaction of control objectives as actuators. the design is based on a two cascade controller consist o...

With development of fast modern computers, it has become possible to extend model predictive control (MPC) method to automotive engine control systems, which is traditionally applied to plants with dynamics slow enough to allow computations between samples. In this paper MPC based on an adaptive neural network model is attempted for air fuel ratio (AFR), in which the model is adapted on-line to...

This paper presents a Particle Swarm Optimization (PSO) based Model Predictive Control (MPC) scheme applied to Automatic Generation Control (AGC) systems. The proposed scheme formulates the MPC as an optimization problem and PSO is used to find its solution. Single area AGC model is taken incorporating Generation Rate Constraint (GRC) nonlinearities and constraints on the control input. Two int...

The purpose of this paper is to describe the importance of the underlying relationship between control strategy design and model predictive control. Successes and problems encountered when implementing model predictive control (MPC) on chemical processes have revealed that understanding this relationship provides insight into the nature of the process control problem. Model predictive control (...

Battery energy storage systems (BESSs) have been widely used for microgrid control. Generally, BESS control systems are based on proportional-integral (PI) control techniques with the outer and inner control loops based on PI regulators. Recently, model predictive control (MPC) has attracted attention for application to future energy processing and control systems because it can easily deal wit...

Model uncertainty limits the utilization of Model Predictive Controllers (MPC) to minimize building energy consumption. We propose a new Robust Model Predictive Control (RMPC) structure to make a building controller robust to model uncertainty. The results from RMPC are compared with those from a nominal MPC and a common building Rule Based Control (RBC). The results are then used to develop a ...

Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) describes systems with nonlinear models and/or constraints. Continuation MPC, suggested by T. Ohtsuka in 2004, uses Krylov-Newton iterations. Continuation MPC is suitable for nonlinear problems and has been recently adopted for minimum time problems. We extend the continuation MPC ...