Model predictive control apparatus and method

A model predictive control method for controlling a process having a process input signal and a process output signal dependent on said process input signal, comprising the steps of:

• sampling said process output signal;
• calculating an expected future process output signal from data indicative of future process input signal changes calculated during prior control cycles, said process' steady-state gain, a future process output signal change due to past process input signal changes, and said process output signal sample;
• calculating an error signal from a setpoint signal and said expected future process output signal;
• calculating a process input signal change from said error signal, a vector of data elements derived from a pseudo-inverse of an impulse response matrix model of said process, and said data indicative of future process input signal changes calculated during prior control cycles;
• and
• applying said process input signal change to said process input signal for controlling said process output signal.

A method for controlling the operation of a process having a process input signal and a process output signal dependent upon said process input signal, said method comprising the steps of:

• acquiring a sample of said process output signal;
• determining a predicted process output signal at a future steady state condition according to a process model and said sample of said process output signal;
• determining a steady state error signal according to the difference between said predicted process output signal and a desired setpoint signal;
• determining a set of future process input signal changes calculated so that if applied to said process input signal said estimated steady state error would be substantially cancelled by causing at least one approximate step response in said process output signal at a future time;
• and
• applying a first member of said set of future process input signal changes to said process input signal for controlling the operation of said process.

An electronic model predictive control apparatus for controlling a process having a process input signal and a process output signal dependent on said process input signal, comprising:

• electronic memory means for storing a vector of data elements derived from one or more columns of a pseudo-inverse of an impulse response matrix model of said process;
• means for receiving a process output signal sample;
• electronic processor means for calculating an expected future process output signal, for calculating an error signal from a setpoint signal and said expected future process output signal, and for calculating a process input signal change from said error signal, said vector of data elements derived from one or more columns of said pseudo-inverse, and data indicative of future process input signal changes calculated during prior control cycles;
• and
• means for applying said process input signal change to said process input signal for controlling said process output signal.

A method for controlling the operation of a process having a plurality of process input signals and one process output signal dependent upon at least one of said process input signals, said method comprising the steps of:

• acquiring a sample of said process output signal;
• determining a predicted process output signal at a future steady state condition according to a process model and said sample of said output signal;
• determining a steady state error signal according to the difference between said predicted process output signal and a desired setpoint signal;
• determining, for each process input signal, a set of future process input signal changes calculated so that if applied to said plurality of process input signals said estimated steady state error would be substantially cancelled by causing at least one approximate step response in said process output signal at a future time;
• and
• applying a first member from each said set of future process input signal changes to a corresponding one of said process input signals for controlling the operation of said process.

A method for controlling the operation of a process having a plurality of process input signals and a plurality of process output signals each process output signal dependent upon at least one of said process input signals, said method comprising the steps of:

• acquiring a corresponding sample of each of said plurality of process output signals;
• determining, for each of said plurality of process output signals, a corresponding predicted process output signal at a future steady state condition according to a process model and said corresponding sample;
• determining, for each of said plurality of process output signals, a corresponding steady state error signal according to the difference between said corresponding predicted process output signal and a corresponding setpoint signal;
• determining, for each process output signal, a plurality of sets of future process input signal changes, each set corresponding to one of said plurality of process input signals, calculated so that if applied to said plurality of process input signals said corresponding estimated steady state error would be substantially cancelled by causing at least one approximate step response in a corresponding one of said plurality of process output signals at a future time;
• and
• applying, to each one of said plurality of process input signals, a sum of first members from corresponding sets of future process input signal changes for controlling the operation of said process.

A model predictive control method for controlling a process having a process input signal and a process output signal dependent on said process input signal, comprising the steps of:

• sampling said process output signal;
• calculating an expected future process output signal from a future process output signal change due to past process input signal changes and said process output signal sample;
• calculating an error signal from a setpoint signal and said expected future process output signal;
• calculating a process input signal change from said error signal multiplied by the inverse of said process' steady-state gain, said steady-state process gain determined according to an impulse response model of said process;
• and
• applying said process input signal change to said process input signal for controlling said process output signal.