This paper discusses the possibility of using fuzzy logic to nd the optimal path through a map co... more This paper discusses the possibility of using fuzzy logic to nd the optimal path through a map containing non-crisp hazards. The paper will discuss several topics, including fuzzy logic, genetic algorithms, and how they can be used e ectively in selecting a path when minimum total exposure is desired. The strengths and limitations of the methods will be covered, as well as a selection or results comparing this type of path planning to more traditional crisp-obstacle solvers. The authors will show that fuzzy logic can be used very e ectively to minimize hazard exposure over a wide variety of terrain types.
We use a genetic fuzzy logic approach for solving the aircraft conflict resolution problem. We co... more We use a genetic fuzzy logic approach for solving the aircraft conflict resolution problem. We consider a small uncertainty in the velocity and the maneuver parameters which causes each aircraft's position at any instant to be within a region of uncertainty represented by a convex hull. The objective is to find conflict-free trajectories for the aircraft that minimize the cost of maneuvers. This paper introduces our unique architecture that consists of a hidden layer of neurons and layer of Fuzzy Inference Systems (FISs). An artificial intelligence called EVE is used to train the system and once it is trained, its capability is evaluated on a set of test scenarios. We compare the cost and the computational time of our approach with that obtained by directly applying Genetic Algorithm (GA). The results show the effectiveness of our approach in finding quick near-optimal solutions.
51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, Jan 5, 2013
ABSTRACT Forest fires, and the scale of damage and destruction they leave in their wake, are well... more ABSTRACT Forest fires, and the scale of damage and destruction they leave in their wake, are well known and documented. With limitations in manual methods for fire monitoring, there is a strong need for developing automated methods for the same. In recent years, there has been considerable development in vision-based systems for fire detection. Forest fire tracking using visual sensors require the ability to identify fire regions in imagery, and a model for fire and smoke identification using Fuzzy Logic based image processing is presented in this paper. The model is tested on a wide range of images containing fire and smoke regions and its effectiveness is demonstrated.. The proposed model facilitates the development of a comprehensive fire and smoke detection system and is very attractive for military and civilian applications.
In this work, a Fuzzy Inference System (FIS) is proposed to develop a sense and avoid technique f... more In this work, a Fuzzy Inference System (FIS) is proposed to develop a sense and avoid technique for conflict-free Unmanned Aerial Vehicle (UAV) flight operations in the national airspace. The proposed method is implemented alongside the flight control software guiding the UAV towards a predefined goal. The fuzzy system makes decisions for sense and avoid with respect to the state of other intruder aircraft in the airspace. The fuzzy rules are selected under consideration of the heading and position data of the intruder aircraft obtained using ADS-B sensor relative to the controlled UAV. The avoidance controller is implemented alongside a traditional PID-based flight controller to test the effectiveness of the sense-and-avoid technique. The PID controller drives the controlled UAV towards the goal and the fuzzy controller is for conflict avoidance based on an event trigger logic if the controlled UAV is in the intrusion zone of another aircraft. The integration of the dynamic model of the controlled UAV and fuzzy inference system is described. The numerical simulations are shown to evaluate the performance of the proposed method in the presence of moving as well as stationary intruder aircraft.
The Multiple Traveling Salesmen Problem (MTSP) is a well-known combinatorial optimization problem... more The Multiple Traveling Salesmen Problem (MTSP) is a well-known combinatorial optimization problem, in which a set of locations is to be visited exactly once by a collection of traveling agents. The goal is to either minimize the sum of all tour lengths or the longest tour. This problem has high sensitivity to the perfect knowledge of city locations; however, in many applications, e.g. military or search missions, locations of the tasks is known only up to some level of accuracy. We solve the MTSP using a market-based solution (MBS) in which agents bid for tasks and trade them amongst themselves based on the additional cost of traveling to an additional location. By using a fuzzy cost instead of an crisp cost, taking into account the level of uncertainty in the locations, the sensitivity of the problem to task locations can be reduced. Particle Swarm Optimization (PSO) is used for optimizing the membership functions of the fuzzy cost used in the MBS. We show that the results of the optimized fuzzy market are better than using a crisp cost.
This paper implements a variable damper admittance control in a multi UAV system. Two Unmanned Ae... more This paper implements a variable damper admittance control in a multi UAV system. Two Unmanned Aerial Vehicles (UAVs) are considered in this work for simplicity, to collaboratively transport a common payload. A leader-follower architecture is used. The leader UAV uses a traditional Proportional, Integral and Derivative (PID) control whereas the follower UAV makes control decision by a force feedback admittance controller. The admittance controller simulates a virtual spring mass damper system to implement a force feedback controller for the follower UAV. It ensures effective force compliance via proper choice of admittance parameters, which are stiffness, mass and damping of a virtual spring mass damper system. However, the performance of the controller can be improved by following a variable damping admittance strategy that allows adaptation of the damping coefficient based on the interaction contact forces and their rates, acting on the follower, due to leaders motion. Calculation of variable damping coefficient is proposed to be carried out using Fuzzy Logic (FL) that utilizes heuristic and intuitive knowledge for calculations. The proposed scheme provides effective performance in comparison to a constant damping admittance scheme, which is validated through the results provided in this paper.
HAL (Le Centre pour la Communication Scientifique Directe), Mar 1, 2017
It is extremely important to have an efficient mechanism to determine optimum conflict-free paths... more It is extremely important to have an efficient mechanism to determine optimum conflict-free paths for aircraft in order to improve airspace safety. This research focuses on developing a genetic fuzzy logic based approach for solving the aircraft conflict resolution problem where the objective is to obtain conflict-free trajectories for aircraft in a circular airspace while minimizing the cost of maneuver. Uncertainties in the velocity and the maneuver parameters are also considered which causes each aircraft's position at any instant to be within a region of uncertainty represented by a convex hull. A new and unique architecture for Fuzzy Logic System (FLS) is used that consists of a hidden layer of neurons and a layer of decoupled Fuzzy Inference Systems (FISs) which is capable of iteratively traversing the search space to find a near optimal solution. For this purpose, an artificial intelligence (AI) called EVE is used to tune the parameters of the system and once it is trained, its capability is evaluated on a set of test scenarios. The results obtained for the five and ten aircraft problem for different levels of uncertainty are compared to those obtained by directly applying Genetic Algorithm (GA). The FLS is able to obtain near-optimal solutions comparable to those of GA at a fraction of the computational cost.
Abstract: Wildfires are a major cause of economic and ecological loss. Unmanned aerial vehicles (... more Abstract: Wildfires are a major cause of economic and ecological loss. Unmanned aerial vehicles (UAVs) can be used for detecting and tracking wildfires. Using UAVs to assist in firefighting reduces human involvement for this high-risk job. Fire detection is an important aspect of such a mission and is the focus of this chapter. A fuzzy logic system is trained using the genetic algorithm to have the capability of detecting fire pixels using both visual and FLIR video feeds as inputs. In this chapter, a two-stage cascaded fuzzy logic system is presented, where the first stage uses the visual data and the second stage processes the FLIR data to make a near-accurate detection of fire pixels. The use of both visual and IR data increases the accuracy of fire detection. Unlike other conventional approaches, a genetic fuzzy system provides an easy mechanism to fuse the visual and FLIR inputs. Due to its computational efficiency, this system can be used for real-time operations on board a UAV.
Tilt-rotor quadcopters are a novel class of quadcopters with a servo motor attached on each arm t... more Tilt-rotor quadcopters are a novel class of quadcopters with a servo motor attached on each arm that assist the quadcopter’s rotors to tilt to a desired angle thereby enabling thrust vectoring. Using these additional tilt angles, this type of a quadcopter can be used to achieve desired trajectories with faster maneuvering and can handle external disturbances better than a conventional quadcopter. In this paper, a non-linear controller has been designed using sliding mode technique for the pitch, roll, yaw motions and the servo motor tilt angles of the quadcopter. The dynamic model of the tilt-rotor quadcopter is presented, based on which sliding surfaces were designed to minimize the tracking errors. Using the control inputs derived from these sliding surfaces, the state variables converge to their desired values in finite-time. Further, the non-linear sliding surface coefficients are obtained by stability analysis. The robustness of this proposed sliding mode control technique is shown when a faulty motor scenario is introduced. The quadcopter transforms into a T-copter design upon motor failure thereby abetting the UAV to cope up with the instabilities experienced in yaw, pitch and roll axes and still completing the flight mission. The dynamics of the T-copter design and the derivation of the switching surface coefficients for this reconfigurable system are also presented.
This paper provides insights on the tilt-rotor quadcopters being a fully actuated system. The til... more This paper provides insights on the tilt-rotor quadcopters being a fully actuated system. The tilt-rotor quadcopters are a novel class of quadcopters with the capability of rotating each arm/rotor of the quadcopter to an angle using a servo motor. With the additional servo control inputs, the tilt-rotor quadcopters are fully actuated systems and hence can even hover at any desired orientation. The dynamics of the tilt-rotor quadcopters are derived based on hardware developed in the laboratory with minimal assumptions. A novel nonlinear sliding mode controller is designed that provides the controller input values to achieve any orientation and position as desired. Computational Fluid Dynamic (CFD) simulations were performed on a CAD model of the tilt-rotor quadcopter to obtain real time drag forces for various wind velocities. The robustness of the sliding mode controller is demonstrated under various wind disturbance scenarios while the quadcopter is hovering at a desired position and attitude.
The Multiple Depots, Multiple Traveling Salesmen Problem extends the well-known Traveling Salesma... more The Multiple Depots, Multiple Traveling Salesmen Problem extends the well-known Traveling Salesman Problem (TSP) to cases where there are several traveling salesmen originating from various initial locations (depots). We are interested in a variant of this problem, in which there is no constraint on visiting all the cities, but rather each city offers a benefit value associated with visiting it, and the goal is to maximize the profit by the team of salesmen. We propose a solution based on economic markets, and show that it is capable of producing near-optimal results at a much faster runtime relative to a solution based on Binary Programming.
This paper presents a novel control approach to perform collaborative transportation by using mul... more This paper presents a novel control approach to perform collaborative transportation by using multiple quadcopter Unmanned Aerial Vehicles (UAVs). In this paper, a leader-follower approach is implemented. The leader UAV uses a Proportional, Integral and Derivative (PID) controller to reach the desired goal point or follow a predefined trajectory. Traditionally, a Position Feedback Controller (PFC) has been used in literature to control the follower UAV. PFC takes the feedback of leader UAVs position to control the follower UAV. Such control schemes work effectively in indoor environments using accurate motion tracking cameras. However, the paper focuses on outdoor applications that requires usage of Global Positioning System (GPS) to receive the positional information of the leader UAV. GPS has inherent errors of order of magnitude that can destabilize the system. The control scheme proposed in this research addresses this major limitation. In this paper, a Force Feedback Controller (FFC) is used to control the follower UAV. An admittance controller is employed to implement this FFC. This controller simulates a virtual spring mass damper system, to generate a desired trajectory for the follower UAV, which complies with the contact forces acting on it. This desired trajectory is then tracked by a traditional PID controller. With the proposed control scheme, the follower UAV can be controlled without using leaders positional feedback and the system can be implemented for real-world applications. The paper presents results of numerical simulations showing the effectiveness of the proposed controller for way-point navigation and complex trajectory tracking.
ABSTRACT This work presents a methodology for real-time estimation of wildland fire growth, utili... more ABSTRACT This work presents a methodology for real-time estimation of wildland fire growth, utilizing a fire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed in its criticality towards potential applications such as forest fire surveillance with unmanned systems equipped with onboard sensor suites. The effectiveness of the estimation process is evaluated numerically over fire growth data simulated using a well-established fire growth model described by coupled partial differential equations. The methodology is shown to be fairly accurate in estimating spatio-temporal process states through noise-ridden measurements for real-time deployability.
Advances in Computing and Communications, Jun 1, 2018
A central computational issue in solving infinite-horizon Linear Quadratic Regulator (LQR) proble... more A central computational issue in solving infinite-horizon Linear Quadratic Regulator (LQR) problems is the treatment of the horizon. In this paper, we directly address this issue by implementing the Laguerre Functions and Ritz method. By rigorous proof, it is shown that the proper class of Laguerre Functions can optimally estimate the unknown state and control input of the LQR problem. The error analysis of the proposed method is also provided. We have also used a benchmark problem to show the applicability and effectiveness of the proposed technique and compared this with the other popular numerical methods.
ABSTRACT Wildland fires have consumed acres of land and affected natural habitat in ways beyond a... more ABSTRACT Wildland fires have consumed acres of land and affected natural habitat in ways beyond a common man’s intuition. More often than not, rescue operations including evacuation of surrounding urban areas have failed in saving the damage to life and property. Case studies of historical fires hold lack of situational awareness the biggest obstacle in forest fire-fighting. Eliminating the considerable rack of accurate information about fire-spread behavior can help fire-managers enhance safety of fire-personnel during on-field attacks. Fire-behavior study tools like FARSITE provide a good platform for study of historical fire and help in better understanding. Similar mathematical algorithms can be applied to real time environmental and spatial information to predict the spread of fire- perimeters and intensities. Systems like this can be used with surveillance-based unmanned aircrafts and enable fire-fighters plan on-field fire-attacks and air-drops. The following is a step towards building such a system. The work uses topographical data from the GAP project for the West Virginia Land Cover. A decision making tool is developed using fuzzy logic to designate a fuel model for forest- fires. This fuel model is then subjected to surface fire-spread techniques provided by Huygen’s Principle and Rothermel’s equation to develop a real time fire-predicting system.
In this study we consider a Dynamic Genetic Algorithm used to optimize the movement of a symmetri... more In this study we consider a Dynamic Genetic Algorithm used to optimize the movement of a symmetric six-legged creature. The optimal movement is that which advances the creature in a straight line forward with the greatest average speed. The mutation rate and crossover rate are adjusted based on number of iterations the algorithm has completed. This dynamic element was added to improve convergence rate as well as reducing the chance that the algorithm is stuck in a local optimum. The chromosomes are represented by a 2-dimensional array, where the rows represent sequences of movement. Each row defines the change in the angle for all the joints. Angular rates are restricted per joint, as well as ranges of motion. The fitness of a chromosome is determined by the resultant average speed, calculated as total displacement of the center of gravity over total time of movements in the chromosome. The results of this study show the possibility to breed mathematically the creature by using the Dynamic Genetic Algorithm proposed. This learning process converged, for all the simulations carried out, to the natural motion of six-legged beings like the ants.
This paper discusses the possibility of using fuzzy logic to nd the optimal path through a map co... more This paper discusses the possibility of using fuzzy logic to nd the optimal path through a map containing non-crisp hazards. The paper will discuss several topics, including fuzzy logic, genetic algorithms, and how they can be used e ectively in selecting a path when minimum total exposure is desired. The strengths and limitations of the methods will be covered, as well as a selection or results comparing this type of path planning to more traditional crisp-obstacle solvers. The authors will show that fuzzy logic can be used very e ectively to minimize hazard exposure over a wide variety of terrain types.
We use a genetic fuzzy logic approach for solving the aircraft conflict resolution problem. We co... more We use a genetic fuzzy logic approach for solving the aircraft conflict resolution problem. We consider a small uncertainty in the velocity and the maneuver parameters which causes each aircraft's position at any instant to be within a region of uncertainty represented by a convex hull. The objective is to find conflict-free trajectories for the aircraft that minimize the cost of maneuvers. This paper introduces our unique architecture that consists of a hidden layer of neurons and layer of Fuzzy Inference Systems (FISs). An artificial intelligence called EVE is used to train the system and once it is trained, its capability is evaluated on a set of test scenarios. We compare the cost and the computational time of our approach with that obtained by directly applying Genetic Algorithm (GA). The results show the effectiveness of our approach in finding quick near-optimal solutions.
51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, Jan 5, 2013
ABSTRACT Forest fires, and the scale of damage and destruction they leave in their wake, are well... more ABSTRACT Forest fires, and the scale of damage and destruction they leave in their wake, are well known and documented. With limitations in manual methods for fire monitoring, there is a strong need for developing automated methods for the same. In recent years, there has been considerable development in vision-based systems for fire detection. Forest fire tracking using visual sensors require the ability to identify fire regions in imagery, and a model for fire and smoke identification using Fuzzy Logic based image processing is presented in this paper. The model is tested on a wide range of images containing fire and smoke regions and its effectiveness is demonstrated.. The proposed model facilitates the development of a comprehensive fire and smoke detection system and is very attractive for military and civilian applications.
In this work, a Fuzzy Inference System (FIS) is proposed to develop a sense and avoid technique f... more In this work, a Fuzzy Inference System (FIS) is proposed to develop a sense and avoid technique for conflict-free Unmanned Aerial Vehicle (UAV) flight operations in the national airspace. The proposed method is implemented alongside the flight control software guiding the UAV towards a predefined goal. The fuzzy system makes decisions for sense and avoid with respect to the state of other intruder aircraft in the airspace. The fuzzy rules are selected under consideration of the heading and position data of the intruder aircraft obtained using ADS-B sensor relative to the controlled UAV. The avoidance controller is implemented alongside a traditional PID-based flight controller to test the effectiveness of the sense-and-avoid technique. The PID controller drives the controlled UAV towards the goal and the fuzzy controller is for conflict avoidance based on an event trigger logic if the controlled UAV is in the intrusion zone of another aircraft. The integration of the dynamic model of the controlled UAV and fuzzy inference system is described. The numerical simulations are shown to evaluate the performance of the proposed method in the presence of moving as well as stationary intruder aircraft.
The Multiple Traveling Salesmen Problem (MTSP) is a well-known combinatorial optimization problem... more The Multiple Traveling Salesmen Problem (MTSP) is a well-known combinatorial optimization problem, in which a set of locations is to be visited exactly once by a collection of traveling agents. The goal is to either minimize the sum of all tour lengths or the longest tour. This problem has high sensitivity to the perfect knowledge of city locations; however, in many applications, e.g. military or search missions, locations of the tasks is known only up to some level of accuracy. We solve the MTSP using a market-based solution (MBS) in which agents bid for tasks and trade them amongst themselves based on the additional cost of traveling to an additional location. By using a fuzzy cost instead of an crisp cost, taking into account the level of uncertainty in the locations, the sensitivity of the problem to task locations can be reduced. Particle Swarm Optimization (PSO) is used for optimizing the membership functions of the fuzzy cost used in the MBS. We show that the results of the optimized fuzzy market are better than using a crisp cost.
This paper implements a variable damper admittance control in a multi UAV system. Two Unmanned Ae... more This paper implements a variable damper admittance control in a multi UAV system. Two Unmanned Aerial Vehicles (UAVs) are considered in this work for simplicity, to collaboratively transport a common payload. A leader-follower architecture is used. The leader UAV uses a traditional Proportional, Integral and Derivative (PID) control whereas the follower UAV makes control decision by a force feedback admittance controller. The admittance controller simulates a virtual spring mass damper system to implement a force feedback controller for the follower UAV. It ensures effective force compliance via proper choice of admittance parameters, which are stiffness, mass and damping of a virtual spring mass damper system. However, the performance of the controller can be improved by following a variable damping admittance strategy that allows adaptation of the damping coefficient based on the interaction contact forces and their rates, acting on the follower, due to leaders motion. Calculation of variable damping coefficient is proposed to be carried out using Fuzzy Logic (FL) that utilizes heuristic and intuitive knowledge for calculations. The proposed scheme provides effective performance in comparison to a constant damping admittance scheme, which is validated through the results provided in this paper.
HAL (Le Centre pour la Communication Scientifique Directe), Mar 1, 2017
It is extremely important to have an efficient mechanism to determine optimum conflict-free paths... more It is extremely important to have an efficient mechanism to determine optimum conflict-free paths for aircraft in order to improve airspace safety. This research focuses on developing a genetic fuzzy logic based approach for solving the aircraft conflict resolution problem where the objective is to obtain conflict-free trajectories for aircraft in a circular airspace while minimizing the cost of maneuver. Uncertainties in the velocity and the maneuver parameters are also considered which causes each aircraft's position at any instant to be within a region of uncertainty represented by a convex hull. A new and unique architecture for Fuzzy Logic System (FLS) is used that consists of a hidden layer of neurons and a layer of decoupled Fuzzy Inference Systems (FISs) which is capable of iteratively traversing the search space to find a near optimal solution. For this purpose, an artificial intelligence (AI) called EVE is used to tune the parameters of the system and once it is trained, its capability is evaluated on a set of test scenarios. The results obtained for the five and ten aircraft problem for different levels of uncertainty are compared to those obtained by directly applying Genetic Algorithm (GA). The FLS is able to obtain near-optimal solutions comparable to those of GA at a fraction of the computational cost.
Abstract: Wildfires are a major cause of economic and ecological loss. Unmanned aerial vehicles (... more Abstract: Wildfires are a major cause of economic and ecological loss. Unmanned aerial vehicles (UAVs) can be used for detecting and tracking wildfires. Using UAVs to assist in firefighting reduces human involvement for this high-risk job. Fire detection is an important aspect of such a mission and is the focus of this chapter. A fuzzy logic system is trained using the genetic algorithm to have the capability of detecting fire pixels using both visual and FLIR video feeds as inputs. In this chapter, a two-stage cascaded fuzzy logic system is presented, where the first stage uses the visual data and the second stage processes the FLIR data to make a near-accurate detection of fire pixels. The use of both visual and IR data increases the accuracy of fire detection. Unlike other conventional approaches, a genetic fuzzy system provides an easy mechanism to fuse the visual and FLIR inputs. Due to its computational efficiency, this system can be used for real-time operations on board a UAV.
Tilt-rotor quadcopters are a novel class of quadcopters with a servo motor attached on each arm t... more Tilt-rotor quadcopters are a novel class of quadcopters with a servo motor attached on each arm that assist the quadcopter’s rotors to tilt to a desired angle thereby enabling thrust vectoring. Using these additional tilt angles, this type of a quadcopter can be used to achieve desired trajectories with faster maneuvering and can handle external disturbances better than a conventional quadcopter. In this paper, a non-linear controller has been designed using sliding mode technique for the pitch, roll, yaw motions and the servo motor tilt angles of the quadcopter. The dynamic model of the tilt-rotor quadcopter is presented, based on which sliding surfaces were designed to minimize the tracking errors. Using the control inputs derived from these sliding surfaces, the state variables converge to their desired values in finite-time. Further, the non-linear sliding surface coefficients are obtained by stability analysis. The robustness of this proposed sliding mode control technique is shown when a faulty motor scenario is introduced. The quadcopter transforms into a T-copter design upon motor failure thereby abetting the UAV to cope up with the instabilities experienced in yaw, pitch and roll axes and still completing the flight mission. The dynamics of the T-copter design and the derivation of the switching surface coefficients for this reconfigurable system are also presented.
This paper provides insights on the tilt-rotor quadcopters being a fully actuated system. The til... more This paper provides insights on the tilt-rotor quadcopters being a fully actuated system. The tilt-rotor quadcopters are a novel class of quadcopters with the capability of rotating each arm/rotor of the quadcopter to an angle using a servo motor. With the additional servo control inputs, the tilt-rotor quadcopters are fully actuated systems and hence can even hover at any desired orientation. The dynamics of the tilt-rotor quadcopters are derived based on hardware developed in the laboratory with minimal assumptions. A novel nonlinear sliding mode controller is designed that provides the controller input values to achieve any orientation and position as desired. Computational Fluid Dynamic (CFD) simulations were performed on a CAD model of the tilt-rotor quadcopter to obtain real time drag forces for various wind velocities. The robustness of the sliding mode controller is demonstrated under various wind disturbance scenarios while the quadcopter is hovering at a desired position and attitude.
The Multiple Depots, Multiple Traveling Salesmen Problem extends the well-known Traveling Salesma... more The Multiple Depots, Multiple Traveling Salesmen Problem extends the well-known Traveling Salesman Problem (TSP) to cases where there are several traveling salesmen originating from various initial locations (depots). We are interested in a variant of this problem, in which there is no constraint on visiting all the cities, but rather each city offers a benefit value associated with visiting it, and the goal is to maximize the profit by the team of salesmen. We propose a solution based on economic markets, and show that it is capable of producing near-optimal results at a much faster runtime relative to a solution based on Binary Programming.
This paper presents a novel control approach to perform collaborative transportation by using mul... more This paper presents a novel control approach to perform collaborative transportation by using multiple quadcopter Unmanned Aerial Vehicles (UAVs). In this paper, a leader-follower approach is implemented. The leader UAV uses a Proportional, Integral and Derivative (PID) controller to reach the desired goal point or follow a predefined trajectory. Traditionally, a Position Feedback Controller (PFC) has been used in literature to control the follower UAV. PFC takes the feedback of leader UAVs position to control the follower UAV. Such control schemes work effectively in indoor environments using accurate motion tracking cameras. However, the paper focuses on outdoor applications that requires usage of Global Positioning System (GPS) to receive the positional information of the leader UAV. GPS has inherent errors of order of magnitude that can destabilize the system. The control scheme proposed in this research addresses this major limitation. In this paper, a Force Feedback Controller (FFC) is used to control the follower UAV. An admittance controller is employed to implement this FFC. This controller simulates a virtual spring mass damper system, to generate a desired trajectory for the follower UAV, which complies with the contact forces acting on it. This desired trajectory is then tracked by a traditional PID controller. With the proposed control scheme, the follower UAV can be controlled without using leaders positional feedback and the system can be implemented for real-world applications. The paper presents results of numerical simulations showing the effectiveness of the proposed controller for way-point navigation and complex trajectory tracking.
ABSTRACT This work presents a methodology for real-time estimation of wildland fire growth, utili... more ABSTRACT This work presents a methodology for real-time estimation of wildland fire growth, utilizing a fire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed in its criticality towards potential applications such as forest fire surveillance with unmanned systems equipped with onboard sensor suites. The effectiveness of the estimation process is evaluated numerically over fire growth data simulated using a well-established fire growth model described by coupled partial differential equations. The methodology is shown to be fairly accurate in estimating spatio-temporal process states through noise-ridden measurements for real-time deployability.
Advances in Computing and Communications, Jun 1, 2018
A central computational issue in solving infinite-horizon Linear Quadratic Regulator (LQR) proble... more A central computational issue in solving infinite-horizon Linear Quadratic Regulator (LQR) problems is the treatment of the horizon. In this paper, we directly address this issue by implementing the Laguerre Functions and Ritz method. By rigorous proof, it is shown that the proper class of Laguerre Functions can optimally estimate the unknown state and control input of the LQR problem. The error analysis of the proposed method is also provided. We have also used a benchmark problem to show the applicability and effectiveness of the proposed technique and compared this with the other popular numerical methods.
ABSTRACT Wildland fires have consumed acres of land and affected natural habitat in ways beyond a... more ABSTRACT Wildland fires have consumed acres of land and affected natural habitat in ways beyond a common man’s intuition. More often than not, rescue operations including evacuation of surrounding urban areas have failed in saving the damage to life and property. Case studies of historical fires hold lack of situational awareness the biggest obstacle in forest fire-fighting. Eliminating the considerable rack of accurate information about fire-spread behavior can help fire-managers enhance safety of fire-personnel during on-field attacks. Fire-behavior study tools like FARSITE provide a good platform for study of historical fire and help in better understanding. Similar mathematical algorithms can be applied to real time environmental and spatial information to predict the spread of fire- perimeters and intensities. Systems like this can be used with surveillance-based unmanned aircrafts and enable fire-fighters plan on-field fire-attacks and air-drops. The following is a step towards building such a system. The work uses topographical data from the GAP project for the West Virginia Land Cover. A decision making tool is developed using fuzzy logic to designate a fuel model for forest- fires. This fuel model is then subjected to surface fire-spread techniques provided by Huygen’s Principle and Rothermel’s equation to develop a real time fire-predicting system.
In this study we consider a Dynamic Genetic Algorithm used to optimize the movement of a symmetri... more In this study we consider a Dynamic Genetic Algorithm used to optimize the movement of a symmetric six-legged creature. The optimal movement is that which advances the creature in a straight line forward with the greatest average speed. The mutation rate and crossover rate are adjusted based on number of iterations the algorithm has completed. This dynamic element was added to improve convergence rate as well as reducing the chance that the algorithm is stuck in a local optimum. The chromosomes are represented by a 2-dimensional array, where the rows represent sequences of movement. Each row defines the change in the angle for all the joints. Angular rates are restricted per joint, as well as ranges of motion. The fitness of a chromosome is determined by the resultant average speed, calculated as total displacement of the center of gravity over total time of movements in the chromosome. The results of this study show the possibility to breed mathematically the creature by using the Dynamic Genetic Algorithm proposed. This learning process converged, for all the simulations carried out, to the natural motion of six-legged beings like the ants.
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Papers by Kelly Cohen