A bottoming planar solid oxide fuel cell (SOFC) gas turbine (GT) hybrid system control approach has been conceptualized and designed. Based on previously published modeling techniques, a dynamic model is developed that captures the physics sufficient for dynamic simulation of all processes that affect the system with time scales of . The dynamic model was used to make system design improvements to enable the system to operate dynamically over a wide range of power output (15–100% power). The wide range of operation was possible by burning supplementary fuel in the combustor and operating the turbine at variable speed for improved thermal management. The dynamic model was employed to design a control strategy for the system. Analyses of the relative gain array (RGA) of the system at several operating points gave insight into input/output (I/O) pairing for decentralized control. Particularly, the analyses indicate that, for SOFC/GT hybrid plants that use voltage as a controlled variable, it is beneficial to control system power by manipulating fuel cell current and to control fuel cell voltage by manipulating the anode fuel flowrate. To control the stack temperature during transient load changes, a cascade control structure is employed in which a fast inner loop that maintains the GT shaft speed receives its set point from a slower outer loop that maintains the stack temperature. Fuel can be added to the combustor to maintain the turbine inlet temperature for the lower operating power conditions. To maintain fuel utilization and to prevent fuel starvation in the fuel cell, fuel is supplied to the fuel cell proportionally to the stack current. In addition, voltage is used as an indicator of varying fuel concentrations, allowing the fuel flow to be adjusted accordingly. Using voltage as a sensor is shown to be a potential solution to making SOFC systems robust to varying fuel compositions. The simulation tool proved effective for fuel cell/GT hybrid system control system development. The resulting SOFC/GT system control approach is shown to have transient load-following capability over a wide range of power, ambient temperature, and fuel concentration variations.