Amit K. Sanyal

Amit K. Sanyal

Associate Professor

Mechanical & Aerospace Engineering


  • Ph.D. (Aerospace Engineering, U of Michigan)
  • MS (Mathematics, U of Michigan)
  • MS (Aerospace Engineering, Texas A&M)
  • B. Tech. (Indian Institute of Technology, Kanpur)

Lab/Center Affiliation:

  • Syracuse Center of Excellence
  • Center for Advanced Systems and Engineering (CASE)

Research Interests:

  • Nonlinear dynamics
  • Geometric control
  • Nonlinear estimation
  • Geometric mechanics
  • Aerospace control
  • Mobile robots

Current Research:

My primary research interests are in dynamics modeling, control and estimation of mobile robots, spacecraft and unmanned vehicles modeled as rigid body and multi-body systems. The framework of this research is based on geometric mechanics and geometric control. These methods provide the substantial practical advantage of Lyapunov stability in the control and estimation schemes obtained. A secondary practical advantage is that such schemes lead to energy-efficient and robust control that is implementable with current technology. Geometric mechanics is the study of the mechanics of systems that evolve on state spaces that may not be vector spaces. The overall (translational and attitude) motion of aerospace vehicles cannot be described globally on a vector space, as their states evolve on a differentiable manifold that cannot be continuously deformed to a vector space. For spacecraft, maneuverable aerial vehicles and several robotic systems, the large ranges of rotational motion necessitate a global analysis of the state space to tackle dynamics, state estimation and control problems of interest. The vast majority of current schemes for control and state estimation of such systems are either applicable to local motion due to singularities, or they are unstable in the sense of Lyapunov, or they require discontinuous or hybrid control schemes that cannot be implemented by attitude actuators that can only provide continuous inputs. Technical challenges that can be overcome with the nonlinear estimation and control techniques that I have developed include robustness to uncertainties in the dynamics; coupled control, power and communication constraints; actuator constraints; and control and estimation of system states and uncertain inputs over large ranges of possible motions.

Courses Taught:

Courses taught at NMSU from fall 2013 till spring 2015 are:

  • AE 362 (Orbital Mechanics)
  • ME 452 (Control System Design)
  • AE 561/ME 405 (Spacecraft Dynamics and Control)
  • AE/ME 527 (Control of Mechanical Systems)
  • AE/ME 529 (Nonlinear and Optimal Control)
  • ME 580 (Numerical Analysis II)


  • 2001 Distinguished Graduate Student Masters Research Award, Texas A & M University.
  • 2002 College of Engineering Fellowship, University of Michigan.
  • 2003 Engineering Academic Scholar Certificate, College of Engineering, University of Michigan.
  • 2012 Summer Faculty Fellow, Air Force Research Laboratory.
  • 2013 AIAA Senior Member.
  • 2015 IEEE Senior Member.

Selected Publications:

S. P. Viswanathan, A. K. Sanyal and E. Samiei, “Integrated Guidance and Feedback Control of Underactuated Robotics System in SE(3),” to appear in Journal of Intelligent & Robotic Systems, 2017, doi: 10.1007/s10846-017-0547-0.

M. Izadi and A. K. Sanyal, “Rigid Body Pose Estimation based on the Lagrange-d’Alembert Principle,” Automatica, vol. 71(9), pp. 78-88, 2016, doi: 10.1016/j.automatica.2016.04.028.

S. Br ́as, M. Izadi, C. Silvestre, A. Sanyal and P. Oliveira, “Nonlinear Observer for 3D Rigid Body Motion Estimation using Doppler Measurements”, IEEE Transactions on Automatic Control, vol. 61(11), pp. 3580-3585, 2016, doi: 10.1109/TAC.2016.2526671.

G. Misra, M. Izadi, A. Sanyal and D. Scheeres, “Coupled Orbit-Attitude Dynamics of Spacecraft and Relative State Estimation During Exploration of Small Solar System Bodies,” Advances in Space Research, vol. 57(8), pp. 1747-1761, 2016.

J. Bohn and A. K. Sanyal, “Almost global finite-time stabilization of rigid body attitude dynamics using rotation matrices,” International Journal of Robust and Nonlinear Control, 2016, vol. 26(9), pp. 2008-2022.