predictive controller

Shoulder-fired missiles are one of the most practical tricks in the military industry and are of great importance. In this type of aerospace weapon, due to the short flight time and high maneuvers of the missile in this short duration, the high importance of the control and guidance method to achieve the goal will be determined. In these types of missiles, the speed along the longitudinal axis cannot be controlled due to the solid fuel of the missile, so directional and lateral velocities are used by flight control tools to change the direction. In this paper, first, the dynamic equations of the Shoulder-fired missiles are extracted and then the equations related to predictive control methods and PID are extracted and simulated. Finally, in order to evaluate the accuracy of the simulation results along with the control techniques, the reliability analysis was implemented on both controllers and the results of the two control models were compared. For different flight phases, the use of each controller is specified in combination or individually and the strengths and weaknesses of each controller in different phases are analyzed.

In this paper, a constrained predictive controller is designed using Laguerre functions to control the depth and steering of an autonomous underwater vehicle considering underwater disturbances. Due to under-actuated nonlinear coupled dynamics, parameters uncertainty, external underwater disturbances autonomous underwater vehicles are complicated. Moreover, the underwater autonomous vehicle investigated in this study includes constraints on actuators leading a more complex problem. In this study, first, the nonlinear dynamics of the autonomous underwater vehicle utilized for the controller design has been modeled. Then, Laguerre orthogonal functions were used in the constrained predictive controller design for reducing computational time and accelerating optimization process. Optimized, online, high precision, implementation capability, consider constraints purposefully and robust properties against disturbances can be mentioned as the most important advantages of designed controller. In addition, predictive control method is robust against disturbances. To monitor the methods’ performance, the autonomous underwater vehicle was modeled and then a comparison between the controller's calculation time with and without the Laguerre functions was also represented. At the end, the simulation results obtained from this controller, using Laguerre functions, showed the efficiency and effectiveness of the proposed solution.

To transport the natural gas from the producer sources to the consumers, gas pipelines are used. The extension of the pipelines reduces gas pressure and compression stations are considered to compensate for the loss of pressure in the transport path. At these stations, several compressor units usually work in parallel to share the gas inlet flow. The purpose of the present study is to investigate the load distribution method between parallel compressors in an optimal manner according to the capacity of each compressor. In this paper, a load sharing algorithm is proposed with the help of a model-based predictive controller (MPC) to achieve a stable and efficient operation at the compression station. In this algorithm, real-time optimization is used by an adaptive modifier method when faced with a variable demand from the consumer. The optimization is done according to the capacity of each compressor and using the approximated efficiency curve. In this way, the coordinates of the optimal working points for each compressor are obtained. The proposed algorithm is implemented in MATLAB software on the dynamics of centrifugal compressors in parallel arrangement. The results show that the load distribution using the proposed method has a much better performance than the old methods such as equal load balancing. This method results in the optimal operation of each compressor and thus storing and saving the natural gas.