This paper investigates State Space Model Predictive Control (SSMPC) of an aerothermic process. It is a pilot scale heating and ventilation system equipped with a heater grid and a centrifugal blower, fully connected ...This paper investigates State Space Model Predictive Control (SSMPC) of an aerothermic process. It is a pilot scale heating and ventilation system equipped with a heater grid and a centrifugal blower, fully connected through a data acquisition system for real time control. The interaction between the process variables is shown to be challenging for single variable controllers, therefore multi-variable control is worth considering. A multi-variable state space model is obtained from on-line experimental data. The controller design is translated into a Quadratic Programming (QP) problem, in which a cost function subject to actuators linear inequality constraints is minimized. The outcome of the experimental results is that the main control objectives, such as set-point tracking and perturbations rejection under actuators constraints, are well achieved for both controlled variables simultaneously.展开更多
This paper investigates a fixed-time distributed voltage and reactive power compensation of islanded microgrids using sliding-mode and multi-agent consensus design.A distributed sliding-mode control protocol is propos...This paper investigates a fixed-time distributed voltage and reactive power compensation of islanded microgrids using sliding-mode and multi-agent consensus design.A distributed sliding-mode control protocol is proposed to ensure voltage regulation and reference tracking before the desired preset fixed-time despite the unknown disturbances.Accurate reactive power sharings among distributed generators are maintained.The secondary controller is synthesized without the knowledge of any parameter of the microgrid.It is implemented using a sparse one-way communication network modeled as a directed graph.A comparative simulation study is conducted to highlight the performance of the proposed control strategy in comparison with finite-time and asymptotic control systems with load power variations.展开更多
文摘This paper investigates State Space Model Predictive Control (SSMPC) of an aerothermic process. It is a pilot scale heating and ventilation system equipped with a heater grid and a centrifugal blower, fully connected through a data acquisition system for real time control. The interaction between the process variables is shown to be challenging for single variable controllers, therefore multi-variable control is worth considering. A multi-variable state space model is obtained from on-line experimental data. The controller design is translated into a Quadratic Programming (QP) problem, in which a cost function subject to actuators linear inequality constraints is minimized. The outcome of the experimental results is that the main control objectives, such as set-point tracking and perturbations rejection under actuators constraints, are well achieved for both controlled variables simultaneously.
基金This work was supported by Morocco’s National Center for Scientific and Technical Research within the Research Excellence Scholarships Program.
文摘This paper investigates a fixed-time distributed voltage and reactive power compensation of islanded microgrids using sliding-mode and multi-agent consensus design.A distributed sliding-mode control protocol is proposed to ensure voltage regulation and reference tracking before the desired preset fixed-time despite the unknown disturbances.Accurate reactive power sharings among distributed generators are maintained.The secondary controller is synthesized without the knowledge of any parameter of the microgrid.It is implemented using a sparse one-way communication network modeled as a directed graph.A comparative simulation study is conducted to highlight the performance of the proposed control strategy in comparison with finite-time and asymptotic control systems with load power variations.
