Model predictive controller is widely used in industrial plants. Uncertainty is one of the critical issues in real systems. In this paper, the direct adaptive Simplified Model Predictive Control (SMPC) is proposed for unknown or time varying plants with uncertainties. By estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly calculated. The proposed method is validated via simulations for both slow and fast time varying systems. Simulation results indicate the controller ability for tracking references in the presence of plant’s time varying parameters. In addition, an analytical tuning method for adjusting prediction horizon is proposed based on optimization of the objective function. It leads to a simple formula including the model parameters, and an indirect adaptive controller can be designed based on the analytical formula. Simulation results indicate a better performance for the tuned controller. Finally, experimental tests are performed to show the effectiveness of the proposed methodologies.

Drum boilers consume is one of the most important equipment of the thermal power plants in many countries and are widely used in industrial process applications. A boiler-turbine unit is a typical multivariable industrial control system in power plant. The boiler is so manufactured that the drum level must be in the specified range. Output constraints are an important challenge in boiler drum systems to have safety and efficient operation. In this paper, the problem of state space model predictive control for a constrained nonlinear boiler drum systems is investigated. Predictive control is a highly efficient and strong method since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. Simulation results demonstrate the satisfactory performance and effectiveness of this method and compatibility with practical implementation in boiler.

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, feed-forward signals generated by simplified model of permanent magnet synchronous motor. In this paper, feed-forward signals generated are emplyed in model predictive control; which are combined with conventional cascade control structure. Using this approach, a fast transient response and satisfactory tracking ability will be guaranteed. The proposed method is compared with the model reference method and conventional cascade structure. Simulation results showed a good performance of proposed method related to both methods. Verification of simulation results were carried out by experimental results.

Nowadays Autonomous Underwater Vehicles (AUVs) are an unavoidable part of marine industries. One of the most important parts of any autonomous vehicle is the control issue to achieve the desired performance. This paper is concerned with speed control of an AUV model respecting the state and control constraints. According to the Newton-Euler method, the 6 DOF kinematic and dynamic models of the AUV are established. A well-defined performance index and constrained finite horizon optimization program in the form of Model Predictive Control (MPC) strategy is proposed to regulate the horizontal speed of AUV to its desired value while the constraints on the states like depth and control signals are considered in finite time horizon optimization program to be satisfied. The main problem for such a situation is the interaction between speed control and depth deviation then quadratic programing technique managed responses to avoid state and control signal constraints. Simulation results show a reliable performance of proposed MPC strategy to control the horizontal speed of AUV while all the constraints on state, control signal and also the variation of the control signal are satisfied.

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, suppressing surge 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 active controller for surge control in constant speed centrifugal compressors. As such, the applied operator considered for surge control is Close Couple Valve (CCV) and it is designed to stabilize a centrifugal compressor system with disturbaces using nonlinear predictive controller. The proposed controller, without any information about the amount of Throttle Valve variations, could control the surge instability and reduce the distance between compressor operation point and the surge line. Finally, the compressor system with controller is simulated and the obtained results will show the efficiency of the designed nonlinear predictive controller.