The Design of Space Optimization for Weighted Control Allocation Scheme

To increase the using rate of attainable virtual instruction set in static weighted control allocation, a design scheme of space optimization for determining the best weights of instructions offline is proposed based on the improved particle swarm optimization. The mathematical models of weighted pseudo-inverse and mixed optimization methods are built respectively whose uniform control law is deducted and attainable set constructing algorithm is presented. By introducing the quantum and genetic factors, the diversity of particle swarm is enhanced through cross operation to obtain the global optimal weights of control instructions quickly. The simulation results show that the designed scheme can achieve the maximal attainable set space of weighted control allocation.