Implement Of Model Predictive Control Based On FPGA

Model Predictive Control (MPC) has received increased industrial acceptance during recent years, mainly because of its ability to handle constraints explicitly and the natural way in which it can be applied to multi-variable processes. The computational requirements of MPC, which is typically a quadratic optimization problem solved on-line in every sample time, has previously prohibited its application in the areas where fast sampling is required. Therefore, MPC has mostly been applied to slow processes, for example in the chemical industry. How to find out the global optimum solution quickly is the most difficult aspect of the predictive control algorithms.Lots of researchers have designed many efficient optimization algorithms, which have improved the speed of the algorithm's performing. Among these people, some premote the method of FPGA inplement. This thesis presents a method which use the FPGA chip to implement the MPC controller. Compared to the traditional method, the FPGA can not only improve the speed of MPC, but also strengthen the stabilization of the controller. Furthermore, the method can reduce the area of the controller, so it can improve the embedded performance.Refer to the hardware realization, there are two methods recently, one is to use the FPGA to achieve the MPC controller totally, the other is treating the FPGA as a co- processor. Between the two methods, because of the first is more simple the the second, I choose the first method to achieve the MPC algorithm. Otherwise, my thesis is to implement the linear MPC, it is simple so I decide to use the first method.My thesis have done the following job.First, based on the three tank object, build up the state space model of the system, and then linearize and disperse the model.Second, using the VHDL language to achieve the models of the MPC controller. Including the matrix subtracter, the matrix adder, the Delta model, the Ep model and so on. Then, simulate the programs and change it to achieve the better performance.Third, using the Link For ModelSim toolbox in simulink to link the Simulink and the ModelSim. Then control the three tank model by encapsulate the VHDL entity to the HDL Cosimulation model. Finally, amend the programs further based on the simulation map, so that it can achieve the perfect performance.Above all, my thesis implement the FPGA into the MPC, and we can see that by using the FPGA, the speed of MPC controller can be improved more or less. The result indicate that the method is feasible and valuable.