Abstract: A partial enumeration model predictive controller and method of predictive control for a multiple input, multiple output (MIMO) system, including providing a solution table with problem solutions to a model predictive control problem for the MIMO system over a partial parameter region; scanning the solution table for an optimal solution for current parameters; using the optimal solution to control the MIMO system when the optimal solution is in the solution table; and using an alternative solution to control the MIMO system when the optimal solution is not in the solution table.

Abstract: A method of predictive control for a single input, single output (SISO) system, including modeling the SISO system with model factors, detecting output from the SISO system, estimating a filtered disturbance from the output, determining a steady state target state from the filtered disturbance and a steady state target output, populating a dynamic optimization solution table using the model factors and a main tuning parameter, and determining an optimum input from the dynamic optimization solution table. Determining an optimum input includes determining a time varying parameter, determining a potential optimum input from the time varying parameter, and checking whether the potential optimum input is the optimum input.

Abstract: A partial enumeration model predictive controller and method of predictive control for a multiple input, multiple output (MIMO) system, including providing a solution table with problem solutions to a model predictive control problem for the MIMO system over a partial parameter region; scanning the solution table for an optimal solution for current parameters; using the optimal solution to control the MIMO system when the optimal solution is in the solution table; and using an alternative solution to control the MIMO system when the optimal solution is not in the solution table.

Abstract: A method of predictive control for a single input, single output (SISO) system, including modeling the SISO system with model factors, detecting output from the SISO system, estimating a filtered disturbance from the output, determining a steady state target state from the filtered disturbance and a steady state target output, populating a dynamic optimization solution table using the model factors and a main tuning parameter, and determining an optimum input from the dynamic optimization solution table. Determining an optimum input includes determining a time varying parameter, determining a potential optimum input from the time varying parameter, and checking whether the potential optimum input is the optimum input.