Tal Shima

Sliding-Mode Control for Integrated Missile Autopilot Guidance

A sliding-mode controller is derived for an integrated missile autopilot and guidance loop. Motivated by a differential game formulation of the guidance problem, a single sliding surface, defined using the zero-effort miss distance, is used. The performance of the integrated controller is compared with that of two different two-loop designs. The latter use a sliding-mode controller for the inner autopilot loop and different guidance laws in the outer loop: one uses a standard differential game guidance law, and the other employs guidance logic based on the sliding-mode approach. To evaluate the performance of the various guidance and control solutions, a two-dimensional nonlinear simulation of the missile lateral dynamics and relative kinematics is used, while assuming first-order dynamics for the target evasive maneuvers. The benefits of the integrated design are studied in several endgame interception engagements. Its superiority is demonstrated especially in severe scenarios where spectral separation between guidance and flight control, implicitly assumed in any two-loop design, is less justified. The results validate the design approach of using the zero-effort miss distance to define the sliding surface.

Multiple task assignments for cooperating uninhabited aerial vehicles using genetic algorithms

A problem of assigning cooperating uninhabited aerial vehicles to perform multiple tasks on multiple targets is posed as a new combinatorial optimization problem. A genetic algorithm for solving such a problem is proposed. The algorithm allows us to efficiently solve this NP-hard problem that has prohibitive computational complexity for classical combinatorial optimization methods. It also allows us to take into account the unique requirements of the scenario such as task precedence and coordination, timing constraints, and trajectory limitations. A matrix representation of the genetic algorithm chromosomes simplifies the encoding process and the application of the genetic operators. The performance of the algorithm is compared to that of deterministic branch and bound search and stochastic random search methods. Monte Carlo simulations demonstrate the viability of the genetic algorithm by showing that it consistently and quickly provides good feasible solutions. This makes the real time implementation for high-dimensional problems feasible.

Linear Quadratic Guidance Laws for Imposing a Terminal Intercept Angle

Linear quadratic guidance laws that explicitly enable imposing a predetermined intercept angle are presented. Two such guidance laws are derived, using optimal control and differential game theories, for arbitrary-order linear missile dynamics. The obtained guidance laws are dependent on the well-known zero-effort miss distance and on a new variable denoted zero-effort angle. It is shown that imposing the terminal angle constraint raises considerably the gains of the guidance laws. Theoretic conditions for the existence of a saddle-point solution in the differential game are also derived. These conditions show that imposing the terminal angle constraint requires a higher maneuverability advantage from the missile. The performance of the proposed guidance laws is investigated using a nonlinear two-dimensional simulation of the missiles lateral dynamics and relative kinematics, while assuming first-order dynamics for the targets evasive maneuvers. Using a Monte Carlo study, it is shown that, for the investigated problem, a target can be intercepted with a negligible miss distance and intercept angle error even when the target maneuvers and there are large initial heading errors.

Time-Varying Linear Pursuit-Evasion Game Models with Bounded Controls

Future end game interception scenarios of autonomous uncrewed e ying vehicles are expected to be characterized by variable velocities and lateral acceleration limits. A time-varying linear pursuit ‐evasion game model with bounded controls is presented that can be used to analyze such scenarios. The usefulness of this model is demonstrated by simulations of a realistic ballistic missile defense scenario, as an example. It is shown that a differential game guidance law derived using this time-varying model provides a signie cant improvement in the homing accuracy compared to a guidance law based on a model with constant velocities and lateral acceleration limits. Moreover, the time-varying linear model provides a much more accurate prediction of the miss distance, cone rming its validity. Also a general review of possible structures of the game space decomposition is presented. Oneofthese structuresimpliesthateven ifthepursuerdoesnot havea maneuverability advantage overtheevader, but has an agility advantage, a zero miss distance can still be achieved for some initial conditions.

UAV Cooperative Decision and Control: Challenges and Practical Approaches

Unmanned aerial vehicles (UAVs) are increasingly used in military missions because they have the advantages of not placing human life at risk and of lowering operation costs via decreased vehicle weight. These benefits can be fully realized only if UAVs work cooperatively in groups with an efficient exchange of information. This book provides an authoritative reference on cooperative decision and control of UAVs and the means available to solve problems involving them. The contributors present the information in a manner that abstracts the challenges from the concrete problems, making it possible to leverage the solution methods over a broader range of applications. The first chapter offers representative scenarios to describe the problem and its challenges. The second chapter closely examines these challenges by providing an overview of the algorithms that could be used for cooperative control of UAV teams. Later chapters offer methods for performing multiple tasks on multiple targets and assigning multiple tasks to multiple UAVs in one step. Other topics addressed are the application of mixed integer linear programming and genetic algorithms in situations with strict time constraints, the cooperation of UAVs when there are communication delays, and effectiveness measures derived for operations in uncertain environments. The book has two appendices. The first describes the operation of the MultiUAV2 simulation software used to test the cooperation control algorithms, while the second details the UAV path planning problem and Dubins optimal trajectories. A supplementary website offers a MultiUAV2 software manual and relevant code. Audience: The book is primarily geared toward researchers working on practical solutions for implementing systems with multiple UAVs. Academicians, students, and others who want to understand the field of UAV cooperative control will find this book a useful reference. Contents: List of Figures; List of Tables; Foreword; Preface; Acronyms; Chapter 1: Introduction; Chapter 2: Challenges; Chapter 3: Single Task Tours; Chapter 4: Multiple Assignments; Chapter 5: Simultaneous Multiple Assignments; Chapter 6: Estimation Algorithms for Improved Cooperation under Uncertainty; Chapter 7: Effectiveness Measures for Operations in Uncertain Environments; Appendix A: MutliUAV Simulation; Appendix B: Path Planning for UAVs; Index

Integrated Sliding Mode Autopilot-Guidance for Dual-Control Missiles

An integrated autopilot and guidance algorithm is developed, using the sliding mode control approach, for a missile with forward and aft control surfaces. Based on guidance considerations, the zero efiort miss (ZEM), encountered in difierential games guidance solutions, is used as one of the sliding variables in the proposed control scheme. The dual control conflguration provides an additional degree of freedom in the integrated design. This degree of freedom is exploited by introducing a second sliding surface, selected based on autopilot design considerations. Restraining the system to the ZEM surface guarantees zero miss distance, while remaining on the second surface provides a damped response. The performance of the integrated dual controller is evaluated using a two-dimensional nonlinear simulation of the missile lateral dynamics and relative kinematics, assuming flrst order dynamics for the target evasive maneuvers. The simulation results validate the design approach of using ZEM and the ∞ight-control based sliding surfaces to attain high accuracy interceptions.

Intercept-Angle Guidance

interest is aerial interception between a missile and a maneuvering target. The guidance concept is applicable in all aerial interception geometries: namely, head-on, tail-chase, and the novel head-pursuit. Analytical conditions for existence of these different engagement geometries are derived. The guidance concept is implemented using the sliding-modeapproach. Thecommonassumption of flight alonganinitial collisiontriangle isnottaken,andthusthe guidance law is applicable for both midcourse and endgame guidance. The application in the different engagement geometries is studied via simulation. It is shown that the head-on scenario allows the smallest range of intercept angles.Italsoplacesthemostseveremaneuverabilityrequirementsontheinterceptor.Thus,insomecases,tail-chase or head-pursuit engagements should be considered instead. The choice between the two is dependent on the adversary’s speed ratio; for tail-chase, the interceptor must have a speed advantage over its target, while for headpursuit, it must have a speed disadvantage.

Integrated task assignment and path optimization for cooperating uninhabited aerial vehicles using genetic algorithms

The problem of integrating task assignment and planning paths for a group of cooperating uninhabited aerial vehicles, servicing multiple targets, is addressed. In the problem of interest the uninhabited aerial vehicles need to perform multiple consecutive tasks cooperatively on each ground target. A Dubins car model is used for motion planning, taking into account each vehicles specific constraint of minimum turn radius. By using a finite set to define the visitation angle of a vehicle over a target we pose the integrated problem of task assignment and path optimization in the form of a graph. This new approach results in suboptimal trajectory assignments. Refining the visitation angle discretization allows for an improved solution. Due to the computational complexity of the resulting combinatorial optimization problem, we propose genetic algorithms for the stochastic search of the space of solutions. We distinguish between two cases of vehicle group composition: homogeneous, where all vehicles are identical; and heterogeneous, where the vehicles may have different operational capabilities and kinematic constraints. The performance of the genetic algorithms is demonstrated through sample runs and a Monte Carlo simulation study. Results show that the algorithms quickly provide good feasible solutions, and find the optimal solution for small sized problems.

Cooperative Multiple-Model Adaptive Guidance for an Aircraft Defending Missile

A cooperative guidance law, for a defender missile protecting an aerial target from an incoming homing missile, is presented. The filter used is a nonlinear adaptation of a multiple model adaptive estimator, in which each model represents a possible guidance law and guidance parameters of the incoming homing missile. Fusion of measurements from both the defender missile and protected aircraft is performed. A matched defender’s missile guidance law is optimized to the identified homing missile guidance law. It utilizes cooperation between the aerial target and the defender missile. The cooperation stems from the fact that the defender knows the future evasive maneuvers to be performed by the protected target and thus can anticipate the maneuvers it will induce on the incoming homing missile. Moreover, the target performs a maneuver that minimizes the control effort requirements from the defender. The estimator and guidance law are combined in a multiple model adaptive control configuration. Simulation results show that combining the estimations with the proposed optimal guidance law, that utilizes cooperation between the defending missile and protected target, yields hit-to-kill closed loop performance with very low control effort. This facilitates the use of relatively small defending missiles to protect aircrafts from homing missiles.

Line-of-Sight Interceptor Guidance for Defending an Aircraft

= missile evasive maneuver normal to defendermissile line of sight amp = missile evasive maneuver component normal to target-missile line of sight at, ad, am = target, defender, and missile lateral accelerations, respectively at max, ad max, am max = target, defender, and missile maximum lateral accelerations, respectively atplos, adplos, amplos = target, defender, and missile accelerations normal to the line of sight, respectively Rd, Rm, Rdm = target-defender, target-missile, and defendermissile closing ranges, respectively tf = defender-missile interception time vt, vd, vm = target, defender, and missile speeds, respectively vtlos, vdlos, vmlos = target, defender, and missile speeds along the line of sight, respectively vtplos, vdplos, vmplos