Kalmanje Krishnakumar

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—This paper presents design and performance analysis of a modified reference model MRAC (M-MRAC) architecture for a class of multi-input multi-output uncertain nonlinear systems in the presence of bounded disturbances. M-MRAC incorporates an error feedback in the reference model definition , which allows for fast adaptation without generating high frequency(More)
Hard turning with cubic boron nitride (CBN) tools has been proven to be more effective and efficient than traditional grinding operations in machining hardened steels. However, rapid tool wear is still one of the major hurdles affecting the wide implementation of hard turning in industry. Better prediction of the CBN tool wear progression helps to optimize(More)
1 Abstract In this paper we highlight four problem domains that are well suited and challenging for intelligent system technologies. The problems are defined and an outline of a probable approach is presented. No attempt is made to define the problems as test cases. In other words, no data or set of equations that a user can code and get results are(More)
This paper examines the feasibility, potential benefits and implementation issues associated with retrofitting a neural-adaptive flight control system (NFCS) to existing transport aircraft, including both cable/hydraulic and fly-by-wire configurations. NFCS uses a neural network based direct adaptive control approach for applying alternate sources of(More)
1 Abstract Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and(More)
—The paper presents a prediction-identification model based adaptive control method for uncertain systems with time varying parameters in the presence of bounded external disturbances. The method guarantees desired tracking performance for the system's state and input signals. This is achieved by feeding back the state prediction error to the identification(More)
  • K Krishnakumar, Karen Gundy-Burlet, Mike Aftosmis, Marian Nemec, Greg Limes, Misty Berry +1 other
  • 2004
This paper describes the effort to provide a preliminary capability analysis and a neural-network based adaptive flight control system for the JPL-led BEES aircraft project. The BEES flyer was envisioned to be a small, autonomous platform with sensing and control systems mimicking those of biological systems for the purpose of scientific exploration on the(More)