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This article presents a rigorous formulation for the pursuit-evasion (PE) game when velocity constraints are imposed on agents of the game or players. The game is formulated as an infinite-horizon problem using a non-quadratic functional, then sufficient conditions are derived to prove capture in a finite-time. A novel tracking Hamilton–Jacobi–Isaacs (HJI) equation associated with the non-quadratic value function is employed, which is solved for Nash equilibrium velocity policies for each agent with arbitrary nonlinear dynamics. In contrast to the existing remedies for proof of capture in PE game, the proposed method does not assume players are moving with their maximum velocities and considers the velocity constraints a priori. Attaining the optimal actions requires the solution of HJI equations online and in real-time. We overcome this problem by presenting the on-policy iteration of integral reinforcement learning (IRL) technique. The persistence of excitation for IRL to work is satisfied inherently until capture occurs, at which time the game ends. Furthermore, a nonlinear backstepping control method is proposed to track desired optimal velocity trajectories for players with generalized Newtonian dynamics. Simulation results are provided to show the validity of the proposed methods.
Yusuf Kartal; Kamesh Subbarao; Atilla Dogan; Frank Lewis. Optimal game theoretic solution of the pursuit‐evasion intercept problem using on‐policy reinforcement learning. International Journal of Robust and Nonlinear Control 2021, 1 .
AMA StyleYusuf Kartal, Kamesh Subbarao, Atilla Dogan, Frank Lewis. Optimal game theoretic solution of the pursuit‐evasion intercept problem using on‐policy reinforcement learning. International Journal of Robust and Nonlinear Control. 2021; ():1.
Chicago/Turabian StyleYusuf Kartal; Kamesh Subbarao; Atilla Dogan; Frank Lewis. 2021. "Optimal game theoretic solution of the pursuit‐evasion intercept problem using on‐policy reinforcement learning." International Journal of Robust and Nonlinear Control , no. : 1.
The temperature distribution in the battery significantly impacts the short-term and long-term performance of battery systems. Therefore, efficient, safe, and reliable battery system operation requires an accurate estimation of the temperature field. The current industry standard for sensors to battery cell ratio is quite frugal. Thus, the problem of sensor placement for accurate temperature estimation becomes non-trivial, especially for large-scale systems. In this letter, we explore a greedy approach for sensor placement suitable for large-scale battery systems. An observer to estimate the thermal field is designed in an
Vedang M. Deshpande; Raktim Bhattacharya; Kamesh Subbarao. Sensor Placement With Optimal Precision for Temperature Estimation of Battery Systems. IEEE Control Systems Letters 2021, 6, 1082 -1087.
AMA StyleVedang M. Deshpande, Raktim Bhattacharya, Kamesh Subbarao. Sensor Placement With Optimal Precision for Temperature Estimation of Battery Systems. IEEE Control Systems Letters. 2021; 6 ():1082-1087.
Chicago/Turabian StyleVedang M. Deshpande; Raktim Bhattacharya; Kamesh Subbarao. 2021. "Sensor Placement With Optimal Precision for Temperature Estimation of Battery Systems." IEEE Control Systems Letters 6, no. : 1082-1087.
In this paper, a set-membership filtering-based leader–follower synchronization protocol for discrete-time linear multi-agent systems is proposed, wherein the aim is to make the agents synchronize with a leader. The agents, governed by identical high-order discrete-time linear dynamics, are subject to unknown-but-bounded input disturbances. In terms of its own state information, each agent only has access to measured outputs that are corrupted with unknown-but-bounded output disturbances. Also, the initial states of the agents are unknown. To deal with all these unknowns (or uncertainties), a set-membership filter (or state estimator), having the “correction-prediction” form of a standard Kalman filter, is formulated. We consider each agent to be equipped with this filter that estimates the state of the agent and consider the agents to be able to share the state estimate information with the neighbors locally. The corrected state estimates of the agents are utilized in the local control law design for synchronization. Under appropriate conditions, the global disagreement error between the agents and the leader is shown to be bounded. An upper bound on the norm of the global disagreement error is calculated and shown to be monotonically decreasing. Finally, a simulation example is included to illustrate the effectiveness of the proposed leader–follower synchronization protocol.
Diganta Bhattacharjee; Kamesh Subbarao. Set-Membership Filtering-Based Leader–Follower Synchronization of Discrete-Time Linear Multi-Agent Systems. Journal of Dynamic Systems, Measurement, and Control 2021, 143, 1 .
AMA StyleDiganta Bhattacharjee, Kamesh Subbarao. Set-Membership Filtering-Based Leader–Follower Synchronization of Discrete-Time Linear Multi-Agent Systems. Journal of Dynamic Systems, Measurement, and Control. 2021; 143 (6):1.
Chicago/Turabian StyleDiganta Bhattacharjee; Kamesh Subbarao. 2021. "Set-Membership Filtering-Based Leader–Follower Synchronization of Discrete-Time Linear Multi-Agent Systems." Journal of Dynamic Systems, Measurement, and Control 143, no. 6: 1.
We propose two perturbation-based extremum seeking control (ESC) schemes for general single input single output nonlinear dynamical systems, having structures similar to that of the classical ESC scheme. We propose novel adaptation laws for the excitation signal amplitudes in each scheme that drive the amplitudes to zero. The rates of decay for both the laws are governed by the gradient measures of the unknown reference-to-output equilibrium map We show that the proposed ESC schemes achieve practical asymptotic convergence to the extremum with a proper tuning of the parameters in the proposed schemes. As the extremum is reached, and the magnitudes of the gradient measures become small, the excitation signal amplitudes converge to zero. Thus, the proposed schemes ensure that the excitation signal is driven to zero as the system output converges to a neighborhood of the extremum and the steady-state oscillations about the extremum, typically observed for the classical ESC schemes, are attenuated. Simulation examples are included to illustrate the effectiveness of the proposed schemes.
Diganta Bhattacharjee; Kamesh Subbarao. Extremum seeking control with attenuated steady-state oscillations. Automatica 2021, 125, 109432 .
AMA StyleDiganta Bhattacharjee, Kamesh Subbarao. Extremum seeking control with attenuated steady-state oscillations. Automatica. 2021; 125 ():109432.
Chicago/Turabian StyleDiganta Bhattacharjee; Kamesh Subbarao. 2021. "Extremum seeking control with attenuated steady-state oscillations." Automatica 125, no. : 109432.
In this technical note, a recursive {set-membership} filtering algorithm for discrete-time nonlinear dynamical systems subject to unknown but bounded process and measurement noises is proposed. The nonlinear dynamics is represented in a pseudo-linear form using the state dependent coefficient (SDC) parameterization. Matrix Taylor expansions are utilized to expand the state dependent matrices about the state estimates. Upper bounds on the {norms of} remainders in the matrix Taylor expansions are calculated on-line using a non-adaptive random search algorithm at each time step. Utilizing these upper bounds and the ellipsoidal set description of the uncertainties, a two-step filter is derived that utilizes the ‘correction-prediction’ structure of the standard Kalman Filter variants. At each time step, correction and prediction ellipsoids are constructed that contain the true state of the system by solving the corresponding semi-definite programs (SDPs). Finally, a simulation example is included to illustrate the effectiveness of the proposed approach.
Diganta Bhattacharjee; Kamesh Subbarao. Set-Membership Filter for Discrete-Time Nonlinear Systems Using State Dependent Coefficient Parameterization. IEEE Transactions on Automatic Control 2021, PP, 1 -1.
AMA StyleDiganta Bhattacharjee, Kamesh Subbarao. Set-Membership Filter for Discrete-Time Nonlinear Systems Using State Dependent Coefficient Parameterization. IEEE Transactions on Automatic Control. 2021; PP (99):1-1.
Chicago/Turabian StyleDiganta Bhattacharjee; Kamesh Subbarao. 2021. "Set-Membership Filter for Discrete-Time Nonlinear Systems Using State Dependent Coefficient Parameterization." IEEE Transactions on Automatic Control PP, no. 99: 1-1.
In this paper, analytical expressions for cycle-averaged aerodynamic forces generated by flapping wings are derived using a force model and flapping kinematics suitable for the forward flight of avian creatures. A strip theory-based formulation is proposed and the analytical expressions are found as functions of the amplitude of twist profile, mean twist angle, the flow separation point on the upper surfaces of the wings, and Strouhal number. Numerical results are obtained for a rectangular planform as well as for a representative avian wing planform. Utilizing these results, it is shown that there exists a narrow Strouhal number range where cycle-averaged net thrust, lift, and lift to drag ratio are optimal for a given flow pattern over the upper surfaces of the wings. This narrow Strouhal number range, found to be between 0.1 and 0.3, corresponds to the cruising range for a large number of avian creatures, as documented in current literature. An explanation, based on force constraints and local optimization in aerodynamic force generation, is provided for the unique range of Strouhal numbers utilized in avian cruising flight. The results and the approach outlined in the paper can be utilized to design efficient bio-inspired flapping vehicles.
Diganta Bhattacharjee; Kamesh Subbarao. A flight mechanics-based justification of the unique range of Strouhal numbers for avian cruising flight. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 2020, 235, 1488 -1506.
AMA StyleDiganta Bhattacharjee, Kamesh Subbarao. A flight mechanics-based justification of the unique range of Strouhal numbers for avian cruising flight. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering. 2020; 235 (11):1488-1506.
Chicago/Turabian StyleDiganta Bhattacharjee; Kamesh Subbarao. 2020. "A flight mechanics-based justification of the unique range of Strouhal numbers for avian cruising flight." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 235, no. 11: 1488-1506.
In this technical note, a recursive set membership filtering algorithm for discrete-time nonlinear dynamical systems subject to unknown but bounded process and measurement noise is proposed. The nonlinear dynamics is represented in a pseudo-linear form using the state dependent coefficient (SDC) parameterization. Matrix Taylor expansions are utilized to expand the unknown state dependent matrices about the corresponding state estimates. Upper bounds on the remainders in the matrix Taylor expansions are calculated on-line using a non-adaptive random search algorithm at each time step. Utilizing these upper bounds and the ellipsoidal set description of the uncertainties, a two-step filter is derived that utilizes the `correction-prediction' structure of the standard Kalman Filter variants. At each time step, correction and prediction ellipsoids are constructed that contain the true state of the system by solving the corresponding semi-definite programs (SDPs). Sufficient conditions for boundedness of those ellipsoidal sets are derived. Finally, a simulation example is included to illustrate the effectiveness of the proposed approach.
Diganta Bhattacharjee; Kamesh Subbarao. Set Membership Filter for Discrete-Time Nonlinear Systems Using State Dependent Coefficient Parameterization. 2020, 1 .
AMA StyleDiganta Bhattacharjee, Kamesh Subbarao. Set Membership Filter for Discrete-Time Nonlinear Systems Using State Dependent Coefficient Parameterization. . 2020; ():1.
Chicago/Turabian StyleDiganta Bhattacharjee; Kamesh Subbarao. 2020. "Set Membership Filter for Discrete-Time Nonlinear Systems Using State Dependent Coefficient Parameterization." , no. : 1.
The purpose of this paper is to present a new path-planning algorithm for planetary exploration rovers that will guide the vehicle safely to a reachable state. In particular, this work will make use of a special class of artificial potential functions called navigation functions which are guaranteed to be free of local minimum. The construction of the navigation functions in this work is motivated by the grid-based wavefront expansion method but differs in that the contour levels are defined in terms of the control effort of the system. Two new methods will be introduced in this paper for defining the navigation function. The first method will generate a minimum control effort path plan and the second method will be based on an inverse dynamics approach. Each of the control effort based methods will generate a path plan that will guide the rover’s approach towards an objective reachable state. Finally, a stable backstepping-like controller is implemented to track a trajectory defined along the path plan to the rover’s objective.
Paul Quillen; Josué Muñoz; Kamesh Subbarao. Path Planning to a Reachable State Using Minimum Control Effort Based Navigation Functions. The Journal of the Astronautical Sciences 2019, 66, 554 -581.
AMA StylePaul Quillen, Josué Muñoz, Kamesh Subbarao. Path Planning to a Reachable State Using Minimum Control Effort Based Navigation Functions. The Journal of the Astronautical Sciences. 2019; 66 (4):554-581.
Chicago/Turabian StylePaul Quillen; Josué Muñoz; Kamesh Subbarao. 2019. "Path Planning to a Reachable State Using Minimum Control Effort Based Navigation Functions." The Journal of the Astronautical Sciences 66, no. 4: 554-581.
This paper demonstrates the use of generalized polynomial chaos expansion for the propagation of uncertainties present in various dynamical models. Specifically, a sampling based non-intrusive approach using pseudospectral stochastic collocation is employed to obtain the coefficients required for the generalized polynomial chaos expansion. Various recently developed quadrature techniques are employed within the generalized polynomial chaos expansion framework in order to illustrate their efficacy. In addition to that, the paper also provides an efficient numerical quadrature technique to be used as a sampling technique in stochastic collocation to quantify the uncertainties which are governed by different distribution functions. Results are presented for the orbital motion of a 2U CubeSat subject to initial condition uncertainty and drag related parametric uncertainty demonstrating the accuracy and effectiveness of the proposed technique. Further, stochastic sensitivity analysis is performed to gain insight into the impact of uncertain variables on the evolution of the quantities of interest.
Rajnish Bhusal; Kamesh Subbarao. Generalized Polynomial Chaos Expansion Approach for Uncertainty Quantification in Small Satellite Orbital Debris Problems. The Journal of the Astronautical Sciences 2019, 67, 225 -253.
AMA StyleRajnish Bhusal, Kamesh Subbarao. Generalized Polynomial Chaos Expansion Approach for Uncertainty Quantification in Small Satellite Orbital Debris Problems. The Journal of the Astronautical Sciences. 2019; 67 (1):225-253.
Chicago/Turabian StyleRajnish Bhusal; Kamesh Subbarao. 2019. "Generalized Polynomial Chaos Expansion Approach for Uncertainty Quantification in Small Satellite Orbital Debris Problems." The Journal of the Astronautical Sciences 67, no. 1: 225-253.
The range and endurance of an unmanned aerial system operating nominally in an outdoor environment depends upon the available power and environmental factors like the magnitude and direction of the prevailing wind. This paper focuses on the development of semi-analytical approaches to computing the range and endurance of battery-powered multi-copter unmanned aerial system under varying wind conditions. The analytically derived range is verified against a comprehensive unmanned aerial system simulation which includes experimentally validated elements such as the propulsion system and electric power consumption modules. It is shown that the analytical approach yields the range maps in close agreement with the simulation results.
Ameya Godbole; Kamesh Subbarao; Atilla Dogan; Brian Huff. Semi-analytical range and endurance computation of battery-powered multi-copter unmanned aerial systems under steady wind conditions. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 2019, 233, 5282 -5294.
AMA StyleAmeya Godbole, Kamesh Subbarao, Atilla Dogan, Brian Huff. Semi-analytical range and endurance computation of battery-powered multi-copter unmanned aerial systems under steady wind conditions. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering. 2019; 233 (14):5282-5294.
Chicago/Turabian StyleAmeya Godbole; Kamesh Subbarao; Atilla Dogan; Brian Huff. 2019. "Semi-analytical range and endurance computation of battery-powered multi-copter unmanned aerial systems under steady wind conditions." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 14: 5282-5294.
This paper develops a framework for propagation of uncertainties, governed by different probability distribution functions in a stochastic dynamical system. More specifically, it deals with nonlinear dynamical systems, wherein both the initial state and parametric uncertainty have been taken into consideration and their effects studied in the model response. A sampling-based nonintrusive approach using pseudospectral stochastic collocation is employed to obtain the coefficients required for the generalized polynomial chaos (gPC) expansion in this framework. The samples are generated based on the distribution of the uncertainties, which are basically the cubature nodes to solve expectation integrals. A mixture of one-dimensional Gaussian quadrature techniques in a sparse grid framework is used to produce the required samples to obtain the integrals. The familiar problem of degeneracy with high-order gPC expansions is illustrated and insights into mitigation of such behavior are presented. To illustrate the efficacy of the proposed approach, numerical examples of dynamic systems with state and parametric uncertainties are considered which include the simple linear harmonic oscillator system and a two-degree-of-freedom nonlinear aeroelastic system.
Rajnish Bhusal; Kamesh Subbarao. Uncertainty Quantification Using Generalized Polynomial Chaos Expansion for Nonlinear Dynamical Systems With Mixed State and Parameter Uncertainties. Journal of Computational and Nonlinear Dynamics 2019, 14, 021011 .
AMA StyleRajnish Bhusal, Kamesh Subbarao. Uncertainty Quantification Using Generalized Polynomial Chaos Expansion for Nonlinear Dynamical Systems With Mixed State and Parameter Uncertainties. Journal of Computational and Nonlinear Dynamics. 2019; 14 (2):021011.
Chicago/Turabian StyleRajnish Bhusal; Kamesh Subbarao. 2019. "Uncertainty Quantification Using Generalized Polynomial Chaos Expansion for Nonlinear Dynamical Systems With Mixed State and Parameter Uncertainties." Journal of Computational and Nonlinear Dynamics 14, no. 2: 021011.
This paper deals with the observability and sensitivity analysis of the lightcurve measurement for use in the estimation of instantaneous pose (orientation) and shape geometry. Since several reflectance models exist that are typically used in obtaining a synthetic lightcurve measurement, they are compared to assess the observability or/and ‘sensitivity’ to determine the ‘best model’ for use. These measurement models are nonlinear with implicit and non-trivial dependency on the states; a numerical Jacobian as well as an unscented Kalman filter derived observation matrix are synthesized for each choice of the measurement model and compared. As the linearization is about an attitude (orientation) trajectory, distinct cases are considered to elaborate the results. For the cases evaluated here, it is shown that the attitude and shape/size can indeed be estimated from the lightcurve, but this is also dependent upon the initial conditions (subsequent attitude trajectory). Linear observability analysis of a discretized system is also performed with respect to the attitude states and shape/size parameters using the singular value decomposition of the observability matrix synthesized for a batch of measurements. The results are summarized for various initial conditions of the resident space object's attitude and angular velocity states.
K. Subbarao; L. Henderson. Observability and sensitivity analysis of lightcurve measurement models for use in space situational awareness. Inverse Problems in Science and Engineering 2018, 27, 1399 -1424.
AMA StyleK. Subbarao, L. Henderson. Observability and sensitivity analysis of lightcurve measurement models for use in space situational awareness. Inverse Problems in Science and Engineering. 2018; 27 (10):1399-1424.
Chicago/Turabian StyleK. Subbarao; L. Henderson. 2018. "Observability and sensitivity analysis of lightcurve measurement models for use in space situational awareness." Inverse Problems in Science and Engineering 27, no. 10: 1399-1424.
This article puts forth a framework using model-based techniques for path planning and guidance for an autonomous mobile robot in a constrained environment. The path plan is synthesized using a numerical navigation function algorithm that will form its potential contour levels based on the “minimum control effort.” Then, an improved nonlinear model predictive control approach is employed to generate high-level guidance commands for the mobile robot to track a trajectory fitted along the planned path leading to the goal. A backstepping-like nonlinear guidance law is also implemented for comparison with the NMPC formulation. Finally, the performance of the resulting framework using both nonlinear guidance techniques is verified in simulation where the environment is constrained by the presence of static obstacles.
Paul Quillen; Kamesh Subbarao. Minimum control effort–based path planning and nonlinear guidance for autonomous mobile robots. International Journal of Advanced Robotic Systems 2018, 15, 1 .
AMA StylePaul Quillen, Kamesh Subbarao. Minimum control effort–based path planning and nonlinear guidance for autonomous mobile robots. International Journal of Advanced Robotic Systems. 2018; 15 (6):1.
Chicago/Turabian StylePaul Quillen; Kamesh Subbarao. 2018. "Minimum control effort–based path planning and nonlinear guidance for autonomous mobile robots." International Journal of Advanced Robotic Systems 15, no. 6: 1.
Using tools from artificial intelligence, mainly artificial neural networks, this paper presents an walking-engine for humanoid robots. This engine uses dynamic neural networks with feedback for gait generation, a modified Zhang neural network for a singularity-robust inverse kinematics solver, and feedforward neural networks for neuro-adaptive control. The Atlas humanoid robot model in simulation is used to test and verify the capabilities of the neuro-dynamic walking engine. Results show that the engine is capable of generating conventional ZMP stable walking gaits and executing them using the Atlas robot in simulation.
Ghassan Atmeh; Kamesh Subbarao. A neuro-dynamic walking engine for humanoid robots. Robotics and Autonomous Systems 2018, 110, 124 -138.
AMA StyleGhassan Atmeh, Kamesh Subbarao. A neuro-dynamic walking engine for humanoid robots. Robotics and Autonomous Systems. 2018; 110 ():124-138.
Chicago/Turabian StyleGhassan Atmeh; Kamesh Subbarao. 2018. "A neuro-dynamic walking engine for humanoid robots." Robotics and Autonomous Systems 110, no. : 124-138.
This paper discusses the derivation and implementation of a nonlinear model predictive control law for tracking reference trajectories and constrained control of a quadrotor platform. The approach uses the state-dependent coefficient form to capture the system nonlinearities into a pseudo-linear system matrix. The state-dependent coefficient form is derived following a rigorous analysis of aerial vehicle dynamics that systematically accounts for the peculiarities of such systems. The same state-dependent coefficient form is exploited for obtaining a nonlinear equivalent of the model predictive control. The nonlinear model predictive control law is derived by first transforming the continuous system into a sampled-data form and and then using a sequential quadratic programming solver while accounting for input, output and state constraints. The boundedness of the tracking errors using the sampled-data implementation is shown explicitly. The performance of the nonlinear controller is illustrated through representative simulations showing the tracking of several aggressive reference trajectories with and without disturbances.
Pengkai Ru; Kamesh Subbarao. Nonlinear Model Predictive Control for Unmanned Aerial Vehicles. Aerospace 2017, 4, 31 .
AMA StylePengkai Ru, Kamesh Subbarao. Nonlinear Model Predictive Control for Unmanned Aerial Vehicles. Aerospace. 2017; 4 (2):31.
Chicago/Turabian StylePengkai Ru; Kamesh Subbarao. 2017. "Nonlinear Model Predictive Control for Unmanned Aerial Vehicles." Aerospace 4, no. 2: 31.
This work presents a case wherein the selection of models when producing synthetic light curves affects the estimation of the size of unresolved space objects. Through this case, “inverse crime” (using the same model for the generation of synthetic data and data inversion), is illustrated. This is done by using two models to produce the synthetic light curve and later invert it. It is shown here that the choice of model indeed affects the estimation of the shape/size parameters. When a higher fidelity model (henceforth the one that results in the smallest error residuals after the crime is committed) is used to both create, and invert the light curve model the estimates of the shape/size parameters are significantly better than those obtained when a lower fidelity model (in comparison) is implemented for the estimation. It is therefore of utmost importance to consider the choice of models when producing synthetic data, which later will be inverted, as the results might be misleadingly optimistic.
Laura S. Henderson; Kamesh Subbarao. ‘Inverse Crime’ and Model Integrity in Lightcurve Inversion applied to unresolved Space Object Identification. The Journal of the Astronautical Sciences 2016, 64, 399 -413.
AMA StyleLaura S. Henderson, Kamesh Subbarao. ‘Inverse Crime’ and Model Integrity in Lightcurve Inversion applied to unresolved Space Object Identification. The Journal of the Astronautical Sciences. 2016; 64 (4):399-413.
Chicago/Turabian StyleLaura S. Henderson; Kamesh Subbarao. 2016. "‘Inverse Crime’ and Model Integrity in Lightcurve Inversion applied to unresolved Space Object Identification." The Journal of the Astronautical Sciences 64, no. 4: 399-413.
Paul Quillen; Kamesh Subbarao; Josué Muñoz. Guidance and Control of a Mobile Robot via Numerical Navigation Functions and Backstepping for Planetary Exploration Missions. AIAA SPACE 2016 2016, 1 .
AMA StylePaul Quillen, Kamesh Subbarao, Josué Muñoz. Guidance and Control of a Mobile Robot via Numerical Navigation Functions and Backstepping for Planetary Exploration Missions. AIAA SPACE 2016. 2016; ():1.
Chicago/Turabian StylePaul Quillen; Kamesh Subbarao; Josué Muñoz. 2016. "Guidance and Control of a Mobile Robot via Numerical Navigation Functions and Backstepping for Planetary Exploration Missions." AIAA SPACE 2016 , no. : 1.
This paper develops a cooperative controller for multiple Unmanned Aerial Vehicles (UAVs) with application to target tracking. The cooperation between the UAVs is established based on an algebraic graph connection and the target information is provided externally by pinning it into a subset of the network. A backstepping-like technique is employed to design a consensus-based controller for each UAV in order to achieve target tracking in 3-D. The proposed controller computes commanded signals for the speed, flight path angle, and heading angle to track the target. The paper considers both the cases of fixed and dynamically changing communication topologies. It is shown that target tracking is achieved for fixed connection topology, if the graph has a directed spanning tree; and for the dynamically changing topology, if the union of the graphs over finite time intervals has a directed spanning tree. The system’s stability is shown using a Lyapunov function-based approach for these cases. All tracking errors are shown to be bounded as long as the target states and its derivatives up to second order are bounded. Detailed numerical simulations further illustrate the controller performance.
K Subbarao; M Ahmed. Target tracking using multiple unmanned aerial vehicles: Graph theoretic nonlinear control approach. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 2016, 231, 570 -586.
AMA StyleK Subbarao, M Ahmed. Target tracking using multiple unmanned aerial vehicles: Graph theoretic nonlinear control approach. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering. 2016; 231 (3):570-586.
Chicago/Turabian StyleK Subbarao; M Ahmed. 2016. "Target tracking using multiple unmanned aerial vehicles: Graph theoretic nonlinear control approach." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 3: 570-586.
The development of a computational adaptive optimal controller for regulation and tracking of spacecraft attitude with unknown moment of inertia is the subject of this paper. The control technique accomplishes this by sequentially prioritizing higher goals of stabilization, optimization and identification. The proposed controller assumes measurement of angular velocities, and control torques. Conditions are derived that ensure asymptotic stability of the states. The proposed methodology uses an integral reinforcement learning based approach to drive the system to a linear quadratic optimal control solution. A novel identification method is derived that follows from the optimal controller formulation. Simulations of a spinning satellite with unknown moment of inertia are considered which shows successful optimal regulation and tracking of angular velocities along with accurate identification of unknown inertia.
Pavan Nuthi; Kamesh Subbarao. Computational adaptive optimal control of spacecraft attitude dynamics with inertia matrix identification. 2016 American Control Conference (ACC) 2016, 5836 -5841.
AMA StylePavan Nuthi, Kamesh Subbarao. Computational adaptive optimal control of spacecraft attitude dynamics with inertia matrix identification. 2016 American Control Conference (ACC). 2016; ():5836-5841.
Chicago/Turabian StylePavan Nuthi; Kamesh Subbarao. 2016. "Computational adaptive optimal control of spacecraft attitude dynamics with inertia matrix identification." 2016 American Control Conference (ACC) , no. : 5836-5841.
This paper deals with the control of lighter-than-air vehicles, more specifically the design of an integrated guidance, navigation and control (GNC) scheme that is capable of navigating an airship through a series of constant-altitude, planar waypoints. Two guidance schemes are introduced, a track-specific guidance law and a proportional navigation guidance law, that provide the required signals to the corresponding controllers based on the airship position relative to a target waypoint. A novel implementation of the extended Kalman filter, namely the scheduled extended Kalman filter, estimates the required states and wind speed to enhance the performance of the track-specific guidance law in the presence of time-varying wind. The performance of the GNC system is tested using a high fidelity nonlinear dynamic simulation for a variety of flying conditions. Representative results illustrate the performance of the integrated system for chosen flight conditions.
Ghassan Atmeh; Kamesh Subbarao. Guidance, Navigation and Control of Unmanned Airships under Time-Varying Wind for Extended Surveillance. Aerospace 2016, 3, 8 .
AMA StyleGhassan Atmeh, Kamesh Subbarao. Guidance, Navigation and Control of Unmanned Airships under Time-Varying Wind for Extended Surveillance. Aerospace. 2016; 3 (1):8.
Chicago/Turabian StyleGhassan Atmeh; Kamesh Subbarao. 2016. "Guidance, Navigation and Control of Unmanned Airships under Time-Varying Wind for Extended Surveillance." Aerospace 3, no. 1: 8.