A hardware implementable two-level parallel computing algorithm for general minimum-time control

A hardware implementable two-level parallel computing algorithm for general minimum-time control is proposed. The minimum-time control problem for a continuous-time system is discretized and transformed into a parameter optimization problem which is large dimensional and nonseparable. The proposed two-level algorithm decomposes this parameter optimization problem into a master-slave problem. The master problem is easily solved by a one-dimensional gradient method, and the slave problem is solved by a parallel computing method which combines recursive quadratic programming with the dual method. The convergence of this iterative two-level parallel computing algorithm under some conditions is proved. On the basis of the VLSI array processor technology, a dedicated hardware computing architecture for realizing this algorithm is presented. The corresponding time complexity, is also analyzed. Simulation of practical problems shows that the algorithm is well suited for real-time application of minimum-time control