Model predictive control (MPC) includes a receding-horizon control techniques based on the process model for predictions of the plant output. Since late 1970’s several MPC approaches have been reported in the literature. Selection of the most appropriate MPC approach depend on the specific problem. In this paper, discrete time MPC is applied to a inverted pendulum system coupled to a cart. The ...

In this paper, a new incremental predictive guidance method based on implicit form of velocity to be gained algorithm is proposed. In this approach, the generalized incremental predictive control (GIPC) approach is applied to the linearized model for compensating the guidance error. Instead of using the present state in popular model based predictive controller (MPC), in the new method both pre...

-A novel approach for the implementation of Nonlinear Model Predictive Control (NMPC) using Particle Swarm Optimization (PSO) technique is proposed. Two different approaches are made in the PSO algorithms, Random PSO (RPSO) and knowledge based PSO (KPSO) for the determination of optimum controller gain in MPC structure In order to test the performance of the proposed PSO based MPC system a nonl...

Wiener model identification and predictive control of a pH neutralisation process is presented. Input-output data from a nonlinear, first principles simulation model of the pH neutralisation process are used for subspace-based identification of a black-box Wiener-type model. The proposed nonlinear subspace identification method has the advantage of delivering a Wiener model in a format which is...

This paper presents an explorative work about a Model Predictive Control (MPC) technique. A nonlinear model predictive controller was designed and applied to a fedbatch bioprocess. First, bioprocess and its model are described. Then, a controller based in a nonlinear MPC scheme (Dual Fuzzy Model Predictive Control DF-MPC) is proposed with the aim to test the control of substrate concentration i...

The present sought to draw a comparison between Model Predictive Control performance and two other controllers named Simple PI and Selective PI in controlling large-scale natural gas transport networks. A nonlinear dynamic model of representative gas pipeline was derived from pipeline governing rules and simulated in SIMULINK® environment of MATLAB®. Control schemes were designed to provide a s...

This paper shows the development of a Predictive Sliding Mode Controller (PSMC). The proposed controller blends the design of Sliding Mode Control (SMC) with Model Predictive Control (MPC). The combination of SMC and MPC improves the performance of these two control laws. The designed control strategy has stronger robustness and chattering reduction property to conquer within the system uncerta...

The analysis study has been done for a First Order Plus Delay Time (FOPDT) model controlled by Proportional Integral Derivative (PID), proportional integral(PI),Internal Model Controller(IMC) and Model Predictive Control (MPC) using MATLAB software. The study has been done for both MPC and conventional control methods to design the controller for the level tank system and the results has been c...