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Peak-Seeking Technology to Optimize Flight, Manufacturing, and Business Operations
September 28, 2014

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Approach detects environmental changes in real time to adjust and improve performance

Innovators at NASA's Armstrong Flight Research Center have developed a patented peak-seeking algorithm that can optimize performance of complex operations in real time. Originally designed for aircraft flying in formation, the algorithm automatically finds optimal formation configurations to reduce aircraft drag and therefore increase fuel efficiency. The method is capable of using real-time measurements and quickly adapting to changing environmental conditions. In addition to aerospace applications, including commercial flight, this technology could be used in a variety of situations where optimization is critical, such as manufacturing operations, business processes, energy management, and the automotive industry. This technology was recognized as an Outstanding Technology Development by the Federal Laboratory Consortium for Technology Transfer's Far West Region.


  • Responsive: Adjusts control in response to real-time environmental changes
  • Forward-thinking: Considers the impact of noise during the initial design phase
  • Results-oriented: Increases performance and fuel savings for flight applications; optimizes performance for other applications
  • Streamlined: Allows for design of all dimensions of the process simultaneously
  • Cost-effective: Allows implementation for aircraft at relatively low cost


Peak-seeking approaches can find the most beneficial positions in a variety of industries. This technology can be applied to numerous processes and operations that use peak seeking for real-time optimization, including some within the following industries:

  • Aerospace/Aeronautics
  • Automotive (e.g., anti-lock braking systems)
  • Manufacturing
  • Chemical
  • Tissue and biochemical engineering (e.g., bioreactors)
  • Petroleum
  • Wind turbine

Technology Details

This peak-seeking control technology was developed, in part, to help improve drag reduction for aircraft flying in formation. When flying with a group of airplanes, pilots can reduce drag and use up to 20 percent less fuel by placing a wingtip in the vortex of the leading airplane. However, manually keeping the plane in the most optimal position during a long flight can fatigue the pilot, as conditions continually change and adjustments are necessary. Working with professor Jason Speyer of the Department of Mechanical and Aerospace Engineering at the University of California, Los Angeles, the researchers at NASA's Armstrong Flight Research Center solved this problem by developing an algorithm that automatically places each aircraft in the most beneficial position by measuring and reacting to changing conditions in real time.

How It Works

Peak-seeking algorithms optimize physical processes in real time and are widely used throughout a variety of industries. However, measuring associated parameters in changing conditions—and responding to them appropriately—is difficult because the measurements are typically distorted by noise. Armstrong's technology addresses that problem by employing a time-varying Kalman filter. The filter is an algorithm previously developed to estimate unknown parameters within systems that are intrinsically random and uncertain. The Kalman filter is excellent at finding estimates when it encounters noisy signals. As a minimal-variant filter, it inherently produces the best estimates of a function with the smallest amount of variation from the true value. Thus, the filter can help accurately determine the optimal coordinates of the peak-seeking function as conditions in the environment change.

In addition, this technology takes a multiple-input and multiple-output approach to design for all dimensions simultaneously. This is in contrast to traditional peak-seeking architectures, which can only be designed by considering one dimension at a time, making the design effort difficult. Typical peak-seeking architectures also require specific persistent excitation signals; the Armstrong method allows nearly any persistent excitation signal to be used, allowing for greater flexibility.

Why It Is Better

The algorithm developed at Armstrong overcomes critical drawbacks of previous peak-seeking control methods. More constricted techniques have been used in other industries and disciplines, such as manufacturing and automotive engineering. Armstrong's technology removes some of the restrictions of these approaches, because it can optimize multi-dimensional business processes and operations. In addition, it considers the effect of noise at the beginning of the design cycle rather than correcting for it at the end, and it allows for nearly any type of persistent excitation signal. These advantages can simplify implementing a peak-seeking control system. The technology also improves the level of optimization and broadens the range of applications for peak-seeking control.

Real-World Examples

Researchers at Armstrong Flight Research Center have applied and tested this algorithm in two additional applications. One application optimizes the lift-distribution for aircraft flying in formation, which increases the formation's performance. The other can help aircraft reduce drag and improve performance by optimizing the aircraft trim in real time.


NASA has patented this technology (U.S. Patent No. 8,447,443).

Licensing and Partnering Opportunities

This technology is part of NASA's Innovative Partnerships Office, which seeks to transfer technology into and out of NASA to benefit the space program and U.S. industry. NASA invites companies to consider licensing its technologies for peak-seeking control (DRC-009-026, DRC-011-027, DRC-012-002) for commercial applications.

Contact Information

If you would like more information about this technology or about NASA's technology transfer program, please contact:

Technology Transfer Office
NASA's Armstrong Flight Research Center
PO Box 273, M/S 1100
Edwards, CA 93523-0273
Phone: (661) 276-3368
E-mail: DFRC-TTO@mail.nasa.gov

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Page Last Updated: July 31st, 2015
Page Editor: NASA Administrator