| Multivariable MFA
                          Control System
 In control applications, most processes have multiple
                          inputs and multiple outputs with interactions in between.
                          The level and density loops of an evaporator, and the
                          temperature loops of a multi-zoned furnace are good
                          examples of multivariable processes. Lacking general-purpose
                          multivariable controllers, a large percentage of multivariable
                          processes are treated as single variable processes resulting
                          in poor control, wasted energy and materials, inconsistent
                          quality, and plant upsets.
 
 This graph illustrates a multivariable Model-Free Adaptive
                          (MFA) control system, which consists of a multi-input
                          multi-output (MIMO) process and an MIMO MFA controller.
   Multivariable MFA control system
 Similar to a SISO system, the MIMO system has controller
                          setpoints r(t), error signals e(t),
                          controller outputs u(t), process variables
                          y(t), and disturbance signals d(t).
                          Since it is a multivariable system, all the signals
                          here are vectors represented in bold case.
 2-Input-2-Output MFA Control System
 
 Without losing generality, we will show how a MIMO MFA
                          controller works with a 2-input-2-output (2x2) system
                          as illustrated in following graph. In the 2x2 MFA system,
                          the 2x2 MFA controller consists of two main controllers
                          C11, C22, and two compensators C21, and C12. The process
                          has four sub-processes G11, G21, G12, and G22.
  2-input-2-output MFA control system
  The measured process variables y1 and y2 are used
                          as the feedback signals for the main control loops.
                          They are compared with the setpoints r1 and r2 to produce
                          errors e1 and e2. The output of each controller associated
                          with one of the inputs e1 or e2 is combined with the
                          output of the compensator associated with the other
                          input to produce control signals u1 and u2. The output
                          of each sub-process is cross-added to produce measured
                          process variables y1 and y2. Notice that in real applications
                          the outputs from the sub-processes are not measurable
                          and only their combined signals y1 and y2 can be measured.
                          Thus, by the nature of the 2x2 process, the inputs u1
                          and u2 to the process are interconnected with outputs
                          y1 and y2. The change in one input will cause both outputs
                          to change. 
 The control objective for this 2x2 MFA control system
                          is to produce control outputs u1(t) and u2(t) to force
                          the process variables y1(t) and y2(t) to track their
                          setpoints r1(t) and r2(t), respectively. The minimization
                          of e1(t) and e2(t) is achieved by (i) the regulatory
                          control capability of the MFA controllers, (ii) the
                          decoupling capability of the MFA compensators, and (iii)
                          the adjustment of the MFA weighting factors that allow
                          the controllers to deal with the dynamic changes, large
                          disturbances, and other uncertainties.
 
 2x2 MFA Controller Configuration
 
 A 2x2 MFA controller can be considered to have 2 main
                          controllers C11 and C22. For each main controller, the
                          parameters to configure are: (1) Sample Interval, Ts
                          - the interval between two samples or calculations in
                          seconds. A high speed MFA controller can run at a 1
                          millisecond rate; (2) Controller Gain, Kc1 - use of
                          a default value is recommended, (3) Time Constant, Tc
                          - a rough estimate of the process Time Constant in seconds;
                          (4) Acting Type - direct or reverse acting of the process;
                          and (5) Compensator Gain, Kc2 - to deal with the interaction
                          from the other loop.
 
 MIMO MFA Controller Application Guide
 
 A MIMO system can be much more complex than a SISO system,
                          therefore precautious must be taken when applying a
                          MIMO MFA controller. When designing a multivariable
                          control system, the first step is to decide which process
                          variable is paired with a manipulated variable. A MIMO
                          MFA control system should follow these pairing rules:
                          (1) Each main process (G11, G22) has to be controllable,
                          open-loop stable, and either reverse or direct acting;
                          (2) A process with a large static gain should be included
                          in the main loop as the main process (G11, G22), and
                          a process with a small static gain should be treated
                          as a sub-process. (G21, G12); (3) A faster process should
                          be paired as the main process, and a slower process
                          or processes with time delays should be treated as sub-processes;
                          and (4) If Pairing Rules 2 and 3 are in conflict, a
                          tradeoff is the only option.
 
 As a general guide, an MFA control system should be
                          designed based on the degree of interactions between
                          the loops. This table lists the control system design
                          strategy based on the degree of interaction of a MIMO
                          process.
 MFA control system design strategy
                            
                          
                            | Interaction Measure | Control
                                Strategy |  
                            | Small to non interaction | Tighten both loops with SISO MFA. |  
                            | Moderate interaction | Tighten important loops with SISO MFA and de-tune
                              less important loops; or Use MIMO MFA for better
                              overall control. |  
                            | Severe interaction | Use MIMO MFA to control the process. May need
                              to de-tune less important loops. |      |