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This paper develops a new dynamic processor allocation algorithm for multiple receding horizon controllers (RHC) executing on a multi-core parallel computer. The proposed formulation accounts for bounded model uncertainty, sensor noise, and computation delay. A cost function appropriate for control of multiple coupled vehicle systems on multiple processors is used and an upper bound on the cost as a function of the execution horizon is employed. A parallel processing adaptation of the SNOPT optimization package is used and the efficiency factor of the parallel optimization routine is estimated through simulation benchmarks. Minimization of the cost function upper bound combined with the efficiency factor information results in a combinatorial optimization problem for dynamically allocating the optimal number of logical processors for each RHC subsystem. The new approach is illustrated through simulation of a leader-follower control system for two 3DOF helicopters running on a computer with two quad-core processors.