Flight Control Optimization Using Genetic Algorithm (GA) and Adapative Partitioned Random Search (APRS)

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N/A
Agency Tracking Number: 26599
Amount: $69,049.00
Phase: Phase I
Program: SBIR
Awards Year: 1994
Solitcitation Year: N/A
Solitcitation Topic Code: N/A
Solitcitation Number: N/A
Small Business Information
Scientific Systems Company,
500 West Cummings Park, Suite, 3950, Woburn, MA, 01801
Duns: N/A
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 R. Mehra, Ph.d./s. Mahmoo
 (617) 933-5355
Business Contact
Phone: () -
Research Institution
The design of flight control systems involves the solution of several difficult optimization problems. Due to nonlinear dynamics, constraints on states and controls and modeling uncertainities, the flight control optimization problem involves local optima and nondifferentiable cost functions. This necessitates the use of global search methods such as Genetic Algorithm (GA) and Adaptive Partitioned Random Search (APRS) methods. We have shown that for a class of signal processing problems involving global maximization of a likelihood function over unkown frequencies, APRS is more efficient than GA. During Phase I, we will apply both GA and APRS to the optimization of gains for the F-18 inner loop command and stability augmentation system. The performance of GA & APRS in terms of solution reliability and function evaluations will be tested on a simulation. Phase II will involve complete optimization and testing of the flight control system using FA and APRS methods.

* information listed above is at the time of submission.

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