Radhakant Padhi | Indian Institute of Science (original) (raw)

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Journal Papers by Radhakant Padhi

Unmanned Systems, 2013

A dynamic inversion-based three-dimensional nonlinear aiming point guidance law is presented in t... more A dynamic inversion-based three-dimensional nonlinear aiming point guidance law is presented in this paper for reactive collision
avoidance of unmanned aerial vehicles. When an obstacle is detected in the close vicinity and collision is predicted, an artificial safety sphere is put around the center of the obstacle. Next, the velocity vector of the vehicle is realigned towards an `aiming point' on the surface of the sphere in such a way that passing through it can guarantee safe avoidance of the obstacle. The guidance command generation is based on angular correction between the actual and the desired direction of the velocity vector. Note that the velocity vector gets aligned along the selected aiming point quickly (i.e., within a fraction of the available time-to-go), which makes it possible to avoid pop-up obstacles. The guidance algorithm has been verified with simulations carried out both for single obstacles as well as for multiple obstacles on the path and also with different safety sphere sizes around the obstacles. The proposed algorithm has been validated using both kinematic as well as point mass model of a prototype unmanned aerial vehicle. For better confidence, results have also been validated by incorporating a first-order autopilot models for the velocity vector magnitude and directions.

Abstract: Anonlinear suboptimal guidance law is presented in this paper for successful intercepti... more Abstract: Anonlinear suboptimal guidance law is presented in this paper for successful interception of ground targets by airlaunched missiles and guided munitions. The main feature of this guidance law is that it accurately satisfies terminal impact angle constraints in both azimuth as well as elevation simultaneously. In addition, it is capable of hitting the target with high accuracy as well as minimizing the lateral acceleration demand. The guidance law is synthesized using recently developed model predictive static programming (MPSP). Performance of the proposed MPSP guidance is demonstrated using three-dimensional (3-D) nonlinear engagement dynamics by considering stationary, moving, and maneuvering targets. Effectiveness of the proposed guidance has also been verified by considering firstorder autopilot lag as well as assuming inaccurate information about target maneuvers. Multiple munitions engagement results are presented as well. Moreover, comparison studies with respect to an augmented proportional navigation guidance (which does not impose impact angle constraints) as well as an explicit linear optimal guidance (which imposes the same impact angle constraints in 3-D) lead to the conclusion that the proposed MPSP guidance is superior to both. A large number of randomized simulation studies show that it also has a larger capture region.

Abstract: Using the recently developed computationally efficient model predictive static programm... more Abstract: Using the recently developed computationally efficient model predictive static programming and a closely related model predictive spread control concept, two nonlinear suboptimal midcourse guidance laws are presented in this paper for interceptors engaging against incoming high-speed ballistic missiles. The guidance laws are primarily based on nonlinear optimal control theory, and hence imbed effective trajectory optimization concepts into the guidance laws. Apart from being energy efficient by minimizing the control usage throughout the trajectory (minimum control usage leads to minimum turning, and hence leads to minimum induced drag), both of these laws enforce desired alignment constraints in both elevation and azimuth in a hard-constraint sense. This good alignment during midcourse is expected to enhance the effectiveness of the terminal guidance substantially. Both point mass as well as six-degree-of-freedom simulation results (with a realistic inner-loop autopilot based on dynamic inversion) are presented in this paper, which clearly shows the effectiveness of the proposed guidance laws. It has also been observed that, even with different perturbations of missile parameters, the performance of guidance is satisfactory. A comparison study, with the vector explicit guidance scheme proposed earlier in the literature, also shows that the newly proposed model-predictive-static-programming-based and model-predictive-spread-control-based guidance schemes lead to lesser lateral acceleration demand and lesser velocity loss during engagement.

Abstract: Much of the benefits of deploying unmanned aerial vehicles can be derived from autonomo... more Abstract: Much of the benefits of deploying unmanned aerial vehicles can be derived from autonomous missions. For such missions, however, sense-and-avoid capability (i.e., the ability to detect potential collisions and avoid them) is a critical requirement. Collision avoidance can be broadly classified into global and local path-planning algorithms, both of which need to be addressed in a successful mission. Whereas global path planning (which is mainly done offline) broadly lays out a path that reaches the goal point, local collision-avoidance algorithms, which are usually fast, reactive, and carried out online, ensure safety of the vehicle from unexpected and unforeseen obstacles/collisions. Even though many techniques for both global and local collision avoidance have been proposed in the recent literature, there is a great interest around the globe to solve this important problem comprehensively and efficiently and such techniques are still evolving. This paper presents a brief overview of a few promising and evolving ideas on collision avoidance for unmanned aerial vehicles, with a preferential bias toward local collision avoidance.

Abstract: A nonlinear optimal guidance and control scheme for the atmospheric reentry of an RLV u... more Abstract: A nonlinear optimal guidance and control scheme for the atmospheric reentry of an RLV using pitch plane maneuver is presented. The guidance law generates an angle of attack control command that satisfies the terminal constraints (considered as hard constraints) and the path constraints (considered as soft minimizable constraints). The guidance update process is done rapidly and in closed form using model predictive static programming (MPSP), a technique that provides a finite time nonlinear suboptimal guidance law. A nonlinear optimal controller for the reaction control system (RCS) and aerodynamic controls has been designed using dynamic inversion (DI) and optimal dynamic inversion (ODI) respectively. A fusion logic for the RCS and aerodynamic control combination provides the total control action required. After each guidance cycle, the guidance command updates the trajectory using the actual states obtained from the control design. The control design is found to track the guidance commands well for perturbations in the initial reentry conditions.

Abstract: Diabetes is a long-term disease during which the body’s production and use of insulin a... more Abstract: Diabetes is a long-term disease during which the body’s production and use of insulin are impaired, causing glucose concentration level to increase in the bloodstream. Regulating blood glucose levels as close to normal as possible leads to a substantial decrease in long-term complications of diabetes. In this paper, an intelligent online feedback-treatment strategy is presented for the control of blood glucose levels in diabetic patients using single network adaptive critic (SNAC) neural networks (which is based on nonlinear optimal control theory). A recently developed mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system has been revised and considered for synthesizing the neural network for feedback control. The idea is to replicate the function of pancreatic insulin, i.e. to have a fairly continuous measurement of blood glucose and a situation-dependent insulin injection to the body using an external device. Detailed studies are carried out to analyze the effectiveness of this adaptive critic-based feedback medication strategy. A comparison study with linear quadratic regulator (LQR) theory shows that the proposed nonlinear approach offers some important advantages such as quicker response, avoidance of hypoglycemia problems, etc. Robustness of the proposed approach is also demonstrated from a large number of simulations considering random initial conditions and parametric uncertainties.

Abstract: Using the recently developed model predictive static programming (MPSP) technique, a no... more Abstract: Using the recently developed model predictive static programming (MPSP) technique, a nonlinear suboptimal reentry guidance scheme is presented in this paper for a reusable launch vehicle (RLV). Unlike traditional RLV guidance, the problem considered over here is restricted only to pitch plane maneuver of the vehicle, which allows simpler mission planning and vehicle load management. The computationally efficient MPSP technique brings in the philosophy of trajectory optimization into the framework of guidance design, which in turn results in very effective guidance schemes in general. In the problem addressed in this paper, it successfully guides the RLV through the critical reentry phase both by constraining it to the allowable narrow flight corridor as well as by meeting the terminal constraints at the end of the reentry segment. The guidance design is validated by considering possible aerodynamic uncertainties as well as dispersions in the initial conditions.

Abstract: Based on dynamic inversion, a relatively straightforward approach is presented in this ... more Abstract: Based on dynamic inversion, a relatively straightforward approach is presented in this paper for nonlinear flight control design of high performance aircrafts, which does not require the normal and lateral acceleration commands to be first transferred to body rates before computing the required control inputs. This leads to substantial improvement of the tracking response. Promising results are obtained from six degree-offreedom simulation studies of F-16 aircraft, which are found to be superior as compared to an existing approach (which is also based on dynamic inversion). The new approach has two potential benefits, namely reduced oscillatory response (including elimination of non-minimum phase behavior) and reduced control magnitude. Next, a model-following neuron-adaptive design is augmented the nominal design in order to assure robust performance in the presence of parameter inaccuracies in the model. Note that in the approach the model update takes place adaptively online and hence it is philosophically similar to indirect adaptive control. However, unlike a typical indirect adaptive control approach, there is no need to update the individual parameters explicitly. Instead the inaccuracy in the system output dynamics is captured directly and then used in modifying the control. This leads to faster adaptation, which helps in stabilizing the unstable plant quicker. The robustness study from a large number of simulations shows that the adaptive design has good amount of robustness with respect to the expected parameter inaccuracies in the model.

Abstract: A nonlinear suboptimal robust hybrid guidance scheme is proposed in this paper for long... more Abstract: A nonlinear suboptimal robust hybrid guidance scheme is proposed in this paper for long range flight vehicles propelled by solid motors, for which coming up with an effective guidance law is more difficult as compared to a liquid engine propelled vehicle (because of the absence of thrust cutoff facility and presence of uncertainties in the thrust-time behaviour as well as energy content of solid motors). This challenging objective is achieved by combining a recently-developed nonlinear model predictive static programming technique (which is a real time suboptimal technique) with either null range direction concept or dynamic inversion approach. Owing to the closed form nature of the necessary guidance command update, the proposed hybrid guidance algorithm is computationally very efficient and can possibly be implemented online. The guidance law is verified from simulation studies in a solid motor propelled research vehicle. Assuming the starting point of the second stage to be a deterministic point beyond the atmosphere, the scheme guides the vehicle properly so that it completes the mission within a tight error bound. Simulation results demonstrate the robustness of the guidance scheme in its ability to intercept the target, even even with an uncertainty in the energy content of the solid motor leading to more than 10% in burnout time.

Abstract: The recently developed single network adaptive critic (SNAC) design has been used in th... more Abstract: The recently developed single network adaptive critic (SNAC) design has been used in this study to design a power system stabiliser (PSS) for enhancing the small-signal stability of power systems over a wide range of operating conditions. PSS design is formulated as a discrete non-linear quadratic regulator problem. SNAC is then used to solve the resulting discrete-time optimal control problem. SNAC uses only a single critic neural network instead of the action-critic dual network architecture of typical adaptive critic designs. SNAC eliminates the iterative training loops between the action and critic networks and greatly simplifies the training procedure. The performance of the proposed PSS has been tested on a single machine infinite bus test system for various system and loading conditions. The proposed stabiliser, which is relatively easier to synthesise, consistently outperformed stabilisers based on conventional lead-lag and linear quadratic regulator designs.

Abstract: Euler–Bernoulli beams are distributed parameter systems that are governed by a non-line... more Abstract: Euler–Bernoulli beams are distributed parameter systems that are governed by a non-linear partial differential equation (PDE) of motion. This paper presents a vibration control approach for such beams that directly utilizes the non-linear PDE of motion, and hence, it is free from approximation errors (such as model reduction, linearization etc.). Two state feedback controllers are presented based on a newly developed optimal dynamic inversion technique which leads to closed-form solutions for the control variable. In one formulation a continuous controller structure is assumed in the spatial domain, whereas in the other approach it is assumed that the control force is applied through a finite number of discrete actuators located at predefined discrete locations in the spatial domain. An implicit finite difference technique with unconditional stability has been used to solve the PDE with control actions. Numerical simulation studies show that the beam vibration can effectively be decreased using either of the two formulations.

Abstract: Control systems arising in many engineering fields are often of distributed parameter t... more Abstract: Control systems arising in many engineering fields are often of distributed parameter type, which are modeled by partial differential equations. Decades of research have lead to a great deal of literature on distributed parameter systems scattered in a wide spectrum. Extensions of popular finite-dimensional techniques to infinite-dimensional systems as well as innovative infinite-dimensional specific control design approaches have been proposed. A comprehensive account of all the developments would probably require several volumes and is perhaps a very difficult task. In this paper, however, an attempt has been made to give a brief yet reasonably representative account ofmany of these developments in a chronological order. To make it accessible to a wide audience, mathematical descriptions have been completely avoided with the assumption that an interested reader can always find the mathematical details in the relevant references.

Abstract: An adaptive drug delivery design is presented in this paper using neural networks for e... more Abstract: An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing “nominal model patients” (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing “realistic model patients” (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a modelfollowing adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

Abstract: A new structured model-following adaptive approach is presented in this paper to achiev... more Abstract: A new structured model-following adaptive approach is presented in this paper to achieve large attitude maneuvers of rigid bodies. First, a nominal controller is designed using the dynamic inversion philosophy. Next, a neuro-adaptive design is proposed to augment the nominal design in order to assure robust performance in the presence of parameter inaccuracies as well as unknown constant external disturbances. The structured approach proposed in this paper (where kinematic and dynamic equations are handled separately), reduces the complexity of the controller structure. From simulation studies, this adaptive controller is found to be very effective in assuring robust performance.

Abstract: Combining the philosophies of nonlinear model predictive control and approximate dynami... more Abstract: Combining the philosophies of nonlinear model predictive control and approximate dynamic programming, a new suboptimal control design technique is presented in this paper, named as model predictive static programming (MPSP), which is applicable for finite-horizon nonlinear problems with terminal constraints. This technique is computationally efficient, and hence, can possibly be implemented online. The effectiveness of the proposed method is demonstrated by designing an ascent phase guidance scheme for a ballistic missile propelled by solid motors. A comparison study with a conventional gradient method shows that the MPSP solution is quite close to the optimal solution.

Abstract: A new technique is presented in this paper for the suboptimal control design of distrib... more Abstract: A new technique is presented in this paper for the suboptimal control design of distributed parameter systems in general. This technique is used to synthesize the controller for a nonlinear heat diffusion problem. The method of proper orthogonal decomposition is used for model reduction of the distributed parameter systems. A suboptimal control is then designed using the recently emerging θ -D technique for lumped parameter systems. This control for the reduced order system is then mapped back to the distributed domain using the same basis functions, leading to distributed controls. Simulation results indicate that the method holds promise as a control design technique for nonlinear distributed parameter systems.

Abstract: A computational tool is presented in this paper for the optimal control synthesis of a ... more Abstract: A computational tool is presented in this paper for the optimal control synthesis of a class of nonlinear distributed parameter systems. This systematic methodology incorporates proper orthogonal decomposition based basis function design followed by Galerkin projection, which results in a low-dimensional lumped parameter model. The optimal control problem in the reduced lumped parameter framework is then solved following the philosophy of recently developed ‘single network adaptive critic (SNAC)’ neural networks. This time domain solution is then mapped back to the distributed domain, which essentially leads to a closed form solution for the control variable in a state feedback form. Finite-element based numerical simulation results are presented for a onedimensional benchmark nonlinear heat conduction problem.

Abstract: Combining the philosophies of nonlinear model predictive control theory and approximate... more Abstract: Combining the philosophies of nonlinear model predictive control theory and approximate dynamic programming, a new nonlinear optimal control design method is presented in this paper named as model predictive static programming (MPSP) for a class of nonlinear optimal control problems. Innovativeness of the MPSP technique lies in successfully converting a dynamic programming problem to a static programming problem, which requires a static costate vector. Moreover, this costate vector has a symbolic solution, and hence it leads to a closed form solution of the optimal control history update. This avoids the numerical complexities of optimal control theory making it computationally very efficient and hence suitable for online implementation. Among various applications, the MPSP technique holds good promise for optimal missile guidance. It brings in the philosophy of trajectory optimization into the framework of guidance design, which in turn results in very effective missile guidance. Simulation results for two different classes of problems are presented in this paper, which demonstrate that the proposed method is equally applicable for both strategic as well as tactical missile guidance.

Unmanned Systems, 2013

Mobile Intelligent Autonomous Systems (Chp.20), 2012

2018 AIAA Guidance, Navigation, and Control Conference, Jan 7, 2018

Public reporting burden for the collection of information is estimated to average 1 hour per resp... more Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.

Unmanned Systems, 2020

A nonlinear robust control design approach is presented in this paper for a prototype reusable la... more A nonlinear robust control design approach is presented in this paper for a prototype reusable launch vehicle (RLV) during the critical re-entry phase where the margin for error is small. A nominal control is designed following the dynamic inversion philosophy for the reaction control system (RCS) and optimal dynamic inversion philosophy for the aerodynamic control actuation. This nominal controller is augmented next with a barrier Lyapunov function based neuro-adaptive control in the inner loop, which enforces the body rates of the actual system i.e. in presence of uncertainties to track the closed-loop body rates of the nominal plant. A fusion logic is also presented for fusing the RCS and aerodynamic control. The control design approach presented here assures robust tracking of the guidance commands despite the presence of uncertainties in the plant model. Extensive nonlinear six degree-of-freedom (DoF) simulation study, which embeds additional practical constraints such as actuator delay in the aerodynamic control actuation and constraints related to the RCS, shows that the proposed design approach has both good command following as well as robustness characteristics.

Control Engineering Practice, Sep 1, 2020

This paper presents a new nonlinear robust neuro-adaptive state-constrained control formulation f... more This paper presents a new nonlinear robust neuro-adaptive state-constrained control formulation for effectively controlling a hypersonic flight vehicle in cruise. The proposed controller ensures that the vehicle velocity, attitude and angular body rates remain bounded within the prescribed limits. The asymptotic stability of the closed-loop system in presence of imposed state constraints is shown following barrier Lyapunov function based stability theory. A Sobolev norm-based adaptive control scheme is used along with the nominal controller to ensure the stability of the vehicle in the presence of model uncertainties (as high as 30%). The adaptive control formulation leads to quick learning with much lesser transients and is robust enough not to violate the imposed state-constraints. The effectiveness of the proposed nonlinear control design is illustrated by carrying out a large number of Monte-Carlo like randomized high fidelity six-degree-of-freedom (Six-DOF) simulation studies.

Journal of Dynamic Systems Measurement and Control-transactions of The Asme, Oct 19, 2018

Inspired by fast model predictive control (MPC), a new nonlinear optimal command tracking techniq... more Inspired by fast model predictive control (MPC), a new nonlinear optimal command tracking technique is presented in this paper, which is named as “Tracking-oriented Model Predictive Static Programming (T-MPSP).” Like MPC, a model-based prediction-correction approach is adopted. However, the entire problem is converted to a very low-dimensional “static programming” problem from which the control history update is computed in closed-form. Moreover, the necessary sensitivity matrices (which are the backbone of the algorithm) are computed recursively. These two salient features make the computational process highly efficient, thereby making it suitable for implementation in real time. A trajectory tracking problem of a two-wheel differential drive mobile robot is presented to validate and demonstrate the proposed philosophy. The simulation studies are very close to realistic scenario by incorporating disturbance input, parameter uncertainty, feedback sensor noise, time delays, state constraints, and control constraints. The algorithm has been implemented on a real hardware and the experimental validation corroborates the simulation results.

IFAC-PapersOnLine, 2018

By directly dealing with nonlinear model of the robot this paper presents dynamic inversion as a ... more By directly dealing with nonlinear model of the robot this paper presents dynamic inversion as a method of control for reference trajectory tracking of autonomous wheeled mobile robots. Dynamic Inversion control is a technique that guarantees asymptotic stability of the error dynamics leading to appreciable tracking of reference compared to linearised design approach. Nonlinear kinematic model of a differential drive wheeled mobile robot (WMR) is considered as plant. Experimentation has been done to show the implementability of the method in real-time on a real robot. Results are shown for tracking circle and ∞-shaped reference trajectories.

An output-constrained nonlinear control design technique is presented in this paper for Euler-Lag... more An output-constrained nonlinear control design technique is presented in this paper for Euler-Lagrange type of systems. The controller is formulated to prevent both symmetric as well as asymmetric output constraint violations. The dynamic inversion control philosophy is used to formulate the controller. However, unlike dynamic inversion, error dependent gains are chosen in the proposed control formulation, which leads to a nonlinear closed loop error dynamics. The barrier Lyapunov function is used to prove the asymptotic stability of the closed loop error dynamics. It is shown that the system output will remain bounded by the chosen constraints and all other close loop states will also remain bounded. The effectiveness of the controller is illustrated through extensive simulation results.

IFAC-PapersOnLine, 2018

This paper proposes a nonlinear state-constrained control design technique for a class of nonline... more This paper proposes a nonlinear state-constrained control design technique for a class of nonlinear systems. The closed-form expression of the state feedback control law is derived using barrier Lyapunov function. The derived controller ensures the asymptotic stability of the closed-loop system without violation of imposed state constraints. It is shown that the closedloop states, under the proposed control law, never transgress the imposed constraints even under bounded disturbance functions. It is also pointed out that classical dynamic inversion based control is a special case of the proposed control scheme. The effectiveness of the derived controller is illustrated through a numerical example.

Journal of The Franklin Institute-engineering and Applied Mathematics, Dec 1, 2022

Aerospace Science and Technology, Feb 1, 2019

A novel three dimensional aiming point guidance law is presented in this paper, which eliminates ... more A novel three dimensional aiming point guidance law is presented in this paper, which eliminates the need for gravity compensation, resulting in engagements occurring with zero acceleration commands, in turn leading to smaller overall control effort and an excellent zero effort miss behavior. The conditions necessary for collision in the presence of gravity are derived using model-based prediction and computationally efficient shooting method. This is followed by employing differential-geometric guidance philosophy for achieving collision with the target. The efficacy of the proposed guidance law is then verified using simulation studies for terminal phase ballistic missile interception, and is compared with proportional navigation, aiming point guidance and compensated-weave guidance. Results indicate that the proposed guidance law ensured collision with desired level of accuracy and outperformed the aforementioned guidance laws used for comparison, in terms of miss distance, zero effort miss behavior and control effort.

Unmanned Systems, Apr 1, 2016

An effective reactive collision avoidance algorithm is presented in this paper for unmanned aeria... more An effective reactive collision avoidance algorithm is presented in this paper for unmanned aerial vehicles (UAVs) using two simple inexpensive pinhole cameras. The vision sensed data, which consists of the azimuth and elevation angles at the two camera positions, is first processed through a Kalman filter formulation to estimate the position and velocity of the obstacle. Once the obstacle position is estimated, the collision cone philosophy is used to predict the collision over a short period of time. In case a collision is predicted, steering guidance commands are issued to the vehicle to steer its velocity vector away using the nonlinear differential geometric guidance. A new cubic spline based post-avoidance merging algorithm is also presented so that the vehicle rejoins the intended global path quickly in a smooth manner after avoiding the obstacle. The overall algorithm has been validated using the point mass model of a prototype UAV with first-order autopilot delay. Both extended Kalman filtering (EKF) and unscented Kalman filtering (UKF) have been experimented. Both are found to be quite effective. However, performance of UKF was found to be better than EKF with minor compromise in computational efficiency and hence it can be a better choice. Note that because of two cameras, stereovision signature gets associated with optical flow signature thereby making the overall signature quite strong for obstacle position estimation. This leads to a good amount of success as compared to the usage of a single pinhole camera, results of which has been published earlier.

Abstract : Two robust adaptive nonlinear controller designs are presented in this report for cont... more Abstract : Two robust adaptive nonlinear controller designs are presented in this report for control of an air-breathing hypersonic vehicle in the cruise phase of flight. The first type of controller uses dynamic inversion and the second one is obtained using newly developed state-constrained generalized dynamic inversion technique with the help of Lyapunov theory. Furthermore, the robustness of both controllers is enhanced by augmenting them with a fast disturbance observer. The controller is derived using dynamic inversion technique, by transforming nonlinear system dynamics into linear system dynamics with the help of transformation matrix. Further, the control expression is obtained using stable linear error dynamics, which ensures the asymptotic stability of the error. However, a perfectly known system is assumed while designing the controller using dynamic inversion, which is very difficult to achieve in the case of air-breathing hypersonic vehicle. Hence, constrained neuro-adaptive dynamic inversion technique with Jacobian learning approach is proposed in this report. In this technique, an unknown disturbance function is learned by the controller along with the Jacobian matrix ofthe unknown disturbance to ensure fewer transients. Further, barrier Lyapunov function is used in the formulation of neuro-adaptive dynamic inversion technique to constrain the errorin disturbance learning.The state-constrained generalized dynamic inversion technique is formulated using Barrier Lyapunov function in this report. Further, the derived controller is robust enough to maintain the states within the constrained bounds in presence of unknown disturbances or model uncertainties. However, the perfect tracking is achieved by augmenting the state constrained generalized dynamic inversion with constrained neuro-adaptive Jacobian matrix learning based disturbance learning mechanism.

Two tracking radars are positioned to determine the position information of a target in their ran... more Two tracking radars are positioned to determine the position information of a target in their range, which will then be used by two laser guns to track the target. Noise contained in the position information is filtered out using the extended Kalman filter. A radar dynamics model accepts the target dynamics to provide the target position information in terms of azimuthal and elevation angles (w.r.t the radars). From this, the firing angles (i.e. the angles w.r.t the laser guns) are calculated, and are corrected at discrete intervals of time (0.1s). Simulation results of the proposed concepts have demonstrated successful tracking of the target by the laser beams. Also, beam bending phenomena in the atmosphere is conceptualized, and is used to improve the tracking precision.