This paper describes a market-based approach to controlling a smart matter-based object transport system, in which an array of distributed air jets applies forces to levitate and control the motion of a planar object. In the smart matter regime, the effects of spatial and temporal variation of operating parameters among a multiplicity of sensor, actuators, and controllers make it desirable for a control strategy to exhibit a minimal dependence on system models, and to be able to arbitrate among conflicting goals. A market-based strategy is introduced that aggregates the control requirements of multiple relatively simple local controllers, each of which seeks to optimize the performance of the system within a limited spatial and temporal range. These local controllers act as the market's consumers, and two sets of distributed air jets act as the producers. Experiments are performed comparing the performance of the market-based strategy to a near-optimal model-derived benchmark, as well as to a hand-tuned PD controller. Results indicate that even though the local controllers in the market are not based on a detailed model of the system dynamics, the market is able to effectively approximate the performance of the model-based benchmark. In certain specialized cases, such as tracking a step trajectory, the performance of the market surpasses the performance of the model-based benchmark by balancing the needs of conflicting control goals. A brief overview of the active surface smart matter prototype being developed at Xerox PARC that is the motivation behind this work is also presented.