Abstract We propose a computationally efficient Learning Model Predictive Control (LMPC) scheme for constrained optimal control of class nonlinear systems where the state and input can be reconstructed using lifted outputs. For considered systems, we show how to use historical trajectory data collected during iterative tasks construct convex value function approximation along with safe set in s...

Fast and accurate transient response is the main requirement in electric machine position control. Conventional cascade control structure has sluggish response due to the limitation of inner control loop bandwidth. In this paper, in order to decrease the Permanent Magnet Synchronous Motor (PMSM) transient response time it can be used reference model using feed-forward signals. In this structure...

Laguerre function has many advantages such as good approximation capability for different systems, low computational complexity and the facility of on-line parameter identification. Therefore, it is widely adopted for complex industrial process control. In this work, Laguerre function based adaptive model predictive control algorithm (AMPC) was implemented to control continuous stirred tank rea...

surge is one of the two destructive factors in compressors. surge is the stream instability phenomenon in compressor that imposes severe damages to the compressors. nowadays, suppressingsurge phenomenon is one of the most important issues in oil and gas industries, especially when flow reduction or gas reflux is considered. according to moore-greitzer compressor model, this paper designs an act...

this paper presents a model predictive control (mpc) approach for production and inventory control systems. model predictive control previously has been successfully applied to supply chain problems; however most systems that have been proposed so far possess no information on future demand. the incorporation of a forecasting methodology in an mpc framework can promote the efficiency of control...