Angle Constraints Research Articles

A UAV Path Planning Method for Building Surface Information Acquisition Utilizing Opposition-Based Learning Artificial Bee Colony Algorithm

To obtain more building surface information with fewer images, an unmanned aerial vehicle (UAV) path planning method utilizing an opposition-based learning artificial bee colony (OABC) algorithm is proposed. To evaluate the obtained information, a target information entropy ratio model based on observation angles is proposed, considering the observation angle constraints under two conditions: whether there is an obstacle around the target or not. To efficiently find the optimal observation angles, half of the population that is lower-quality generates bit points through opposition-based learning. The algorithm searches for better individuals near the bit points when generating new solutions. Furthermore, to prevent individuals from observing targets repeatedly from similar angles, the concept of individual abandonment probability is proposed. The algorithm can adaptively abandon similar solutions based on the relative position between the individual and the population. To verify the effectiveness of the proposed method, information acquisition experiments were conducted on real residential buildings, and the results of 3D reconstruction were analyzed. The experiment results show that while model accuracy is comparable to that of the comparison method, the number of images obtained is reduced to one-fourth of the comparison method. The operation time is significantly reduced, and 3D reconstruction efficiency is remarkably improved.

Nonlinear three dimensional all-aspect guidance with terminal impact angle constraints

In this paper, a nonlinear three dimensional all-aspect guidance law, to intercept maneuvering target at pre-specified orientation, is presented. Without decoupling the engagement kinematics into two perpendicular planes, the proposed guidance law is derived in three dimensions directly. More importantly, the proposed strategy is an ‘all-aspect’ guidance law, which allows missile to intercept the target at the desired impact angle, even in the presence of very large initial pointing errors. First, in order to design a guidance law with all-aspect interception capability, the collision conditions analysis process is carefully developed and an additional necessary constraint condition is derived. Then, based on chattering reduction sliding mode control, a nonlinear three dimensional terminal impact angle constrained guidance law is derived considering maneuvering targets. After capturability analysis, an additional sliding mode surface and a switching logic are further designed, so that the all-aspect capability is guaranteed. Finally, numerical simulations are provided to demonstrate the effectiveness of the proposed guidance strategy.

Distributed observer‐based fixed‐time cooperative guidance law against maneuvering target

SummaryThis paper presents a fixed‐time cooperative guidance law for leader‐following missiles, comprising one leader missile with the target seeker and several seeker‐less follower missiles. The aim is to achieve a simultaneous attack on a maneuvering target at desired impact angles. First, a guidance law with impact angle control for the leader missile against a maneuvering target is proposed based on nonsingular fast terminal sliding mode (NFTSM) control algorithm. Then, the design of cooperative guidance law for the follower missiles is composed of two parts: along the follower‐to‐leader line of sight (LOS) direction, the guidance command derived from bi‐homogeneous property is designed to ensure that the follower‐leader ranges keep proportional consensus with the range‐to‐go of the leader missile, thus avoiding the estimation of time‐to‐go (); in the normal follower‐to‐leader LOS direction, considering the relative impact angle constraints which is determined by the leader LOS angle, the guidance command is proposed based on predefined‐time sliding mode control method. What's more, a distributed fixed‐time observer is designed for the follower missiles to compensate for unobtainable leader missile information. The fixed‐time stability of the proposed methods is demonstrated using the Lyapunov theory and bi‐homogeneous property. Finally, simulation results confirm the effectiveness and superiority of the proposed fixed‐time cooperative guidance law with leader‐following strategy.

Application of the Improved Rapidly Exploring Random Tree Algorithm to an Insect-like Mobile Robot in a Narrow Environment.

When intelligent mobile robots perform global path planning in complex and narrow environments, several issues often arise, including low search efficiency, node redundancy, non-smooth paths, and high costs. This paper proposes an improved path planning algorithm based on the rapidly exploring random tree (RRT) approach. Firstly, the target bias sampling method is employed to screen and eliminate redundant sampling points. Secondly, the adaptive step size strategy is introduced to address the limitations of the traditional RRT algorithm. The mobile robot is then modeled and analyzed to ensure that the path adheres to angle and collision constraints during movement. Finally, the initial path is pruned, and the path is smoothed using a cubic B-spline curve, resulting in a smoother path with reduced costs. The evaluation metrics employed include search time, path length, and the number of sampling nodes. To evaluate the effectiveness of the proposed algorithm, simulations of the RRT algorithm, RRT-connect algorithm, RRT* algorithm, and the improved RRT algorithm are conducted in various environments. The results demonstrate that the improved RRT algorithm reduces the generated path length by 25.32% compared to the RRT algorithm, 26.42% compared to the RRT-connect algorithm, and 4.99% compared to the RRT* algorithm. Moreover, the improved RRT algorithm significantly improves the demand for reducing path costs. The planning time of the improved RRT algorithm is reduced by 64.96% compared to that of the RRT algorithm, 40.83% compared to that of the RRT-connect algorithm, and 27.34% compared to that of the RRT* algorithm, leading to improved speed. These findings indicate that the proposed method exhibits a notable improvement in the three crucial evaluation metrics: sampling time, number of nodes, and path length. Additionally, the algorithm performed well after undergoing physical verification with an insect-like mobile robot in a real environment featuring narrow elevator entrances.

Control structure design with constraints for a slung load quadrotor system

We propose a control structure for a quadrotor carrying a slung load with swing-angle constraints. This quadrotor is supposed to pass through the waypoints at specified speeds. First, a cascaded PID autopilot is designed, which adaptively gives attention to position and speed requirements as a function of their errors. Its parameters are found from an optimization problem solved using the PSO algorithm. Second, this controller’s performance is improved by adding the Complementary Controller employing an ANN. 5. Training data for the ANN is created by solving optimal control problems. The ANN is activated when the swing angle constraint is about to be violated. It is trained using optimal control values corresponding to the cases where the swing angle falls in a particular band about the upper swing angle constraint. Simulations are performed in a MATLAB environment. Finally, some of the simulation results are validated on a physical system.

Cooperative attack based on small-unit UAV swarms formation with trajectory tracking

Cooperative attack with unmanned aerial vehicles (UAVs) plays a critical role in modern military warfare. To achieve multi-swarm cooperative attack with obstacle avoidance of formation, this paper proposes a cooperative control strategy that integrates flight control and autonomous marshaling. Firstly, an improved dynamics model with virtual leader-following mode is constructed to achieve obstacle avoidance of the formation. And an improved interference fluid dynamic system (IIFDS) is applied to improve path selectivity during multi-swarm attack. Secondly, a two-layer attack framework based on distributed swarm coordinated trajectory tracking with heading angle constraints is designed to achieve autonomous clustering of the UAVs and target striking. Finally, the proposed improved dynamics model is compared with the particle swarm optimization (PSO) algorithm and artificial potential field (APF) method in terms of obstacle avoidance of formation to demonstrate its superiority, which can obtain better benefits. Furthermore, two simulations of multi-swarm cooperative attack are conducted to validate the effectiveness of the control strategy. The proposed method expands the application of UAVs attack with obstacle avoidance of formation and provides a valuable reference for modern military operations.

Ballistic Missile Trajectory Design Considering Impact Angle Constraint

The current paper investigates the problem of guiding ballistic re-entry vehicles to the terminal point under the additional terminal constraint of final flight path angle. In this regard, the classical Lambert’s Problem is reformulated to include the final flight path angle constraint. The proposed solution of the modified Lambert’s problem consists of a minimum of two different trajectories starting from the same initial location and intersecting each other at a location, which is determined by applying the desired time of flight and terminal flight path angle constraints. The modified Lambert strategy strategy is shown to satisfy terminal flight path angle constraint along with the time of flight, initial and final location constraints. This scheme requires the ballistic vehicle to perform an additional stage burn during descent in-order to switch from an initial trajectory, using Lambert strategy, to a final trajectory which satisfies the final flight path angle constraint. An additional stage burn is provided such that the position and velocity of the vehicle traveling in the initial trajectory is matched with that required for it to be on the final trajectory. It is also found that the amount of propellant required for the trajectory transfer, is dependent on the total time of flight and the altitude at which the additional stage burn occurs. The optimal values of these two parameters are found using interior-point optimization technique.

Phase-angle adaptive current differential protection for active distribution network

With the distributed generator to be attached to the distribution network, the current differential protection scheme may have some problems, resulting in maloperation or rejection of protection. This paper investigates the current distribution properties of an active distribution network with branches of undetected load and draws the conclusion that undetected load may cause differential protection maloperation. The differences in fault properties of differential protection in transmission network scenarios and distribution networks containing distributed generator are evaluated, leading to the conclusion that differential protection applied to active distribution networks may have reduced resistance to transition resistance and that poor signal synchronization conditions in distribution networks may lead to larger synchronization errors. A phase-angle adaptive current differential protection is proposed. It adaptively adjusts the phase angle constraint using the magnitude of the power frequency full current component proportion at both sides of the line. It can accommodate the protection needs of various operation modes of distribution networks containing distributed generator, and has the characteristics of strong resistance to transition resistance and strong phase shift braking ability. The correctness of the suggested protection scheme was verified using the PSCAD platform.

Finite-time Cooperative Guidance Law for Multiple Missiles with Impact Angle Constraints and Switching Communication Topologies

Finite-time Cooperative Guidance Law for Multiple Missiles with Impact Angle Constraints and Switching Communication Topologies

Chasing rainbows and ocean glints: Inner working angle constraints for the Habitable Worlds Observatory

ABSTRACT NASA is engaged in planning for a Habitable Worlds Observatory (HabWorlds ), a coronagraphic space mission to detect rocky planets in habitable zones and establish their habitability. Surface liquid water is central to the definition of planetary habitability. Photometric and polarimetric phase curves of starlight reflected by an exoplanet can reveal ocean glint, rainbows, and other phenomena caused by scattering by clouds or atmospheric gas. Direct imaging missions are optimized for planets near quadrature, but HabWorlds ’ coronagraph may obscure the phase angles where such optical features are strongest. The range of accessible phase angles for a given exoplanet will depend on the planet’s orbital inclination and/or the coronagraph’s inner working angle (IWA). We use a recently created catalog relevant to HabWorlds of 164 stars to estimate the number of exo-Earths that could be searched for ocean glint, rainbows, and polarization effects due to Rayleigh scattering. We find that the polarimetric Rayleigh scattering peak is accessible in most of the exo-Earth planetary systems. The rainbow due to water clouds at phase angles of ∼20○ − 60○ would be accessible with HabWorlds for a planet with an Earth equivalent instellation in ∼46 systems, while the ocean glint signature at phase angles of ∼130○ − 170○ would be accessible in ∼16 systems, assuming an IWA = 62 mas (3λ/D). Improving the IWA = 41 mas (2λ/D) increases accessibility to rainbows and glints by factors of approximately 2 and 3, respectively. By observing these scattering features, HabWorlds could detect a surface ocean and water cycle, key indicators of habitability.

Optimal spatial-temporal cooperative guidance against a maneuvering target

This paper proposes an optimal three-dimensional (3-D) spatial-temporal cooperative guidance (STCG) law for intercepting a maneuvering target with impact angle and time constraints. The guidance problem is studied to achieve spatial cooperation for multi-directional attack in the normal channel and temporal cooperation for simultaneous interception in the tangential channel, respectively. Firstly, the 3-D optimal impact-angle-control guidance (OIACG) is introduced to formulate spatial interception geometry. Based on this law, the relative trajectory length is analytically derived and an accurate time-to-go predictor is formulated against maneuvering targets. In the tangential channel, an optimal temporal cooperative guidance is proposed by leveraging high-dimensional Schwarz inequality method. The proposed algorithm is believed to outperform the existing nonlinear cooperative guidance laws due to its optimality with specific performance index for minimizing the control expenditure. The convergence properties of the proposed STCG law are provided to facilitate its practical implementation. Comparison simulations and application under the realistic pursuer model and target estimation are performed to demonstrate the effectiveness and robustness of the proposed cooperative method.

Cubature Kalman Filters Model Predictive Static Programming Guidance Method with Impact Time and Angle Constraints Considering Modeling Errors

This paper proposes a CKF-MPSP guidance method for hitting stationary targets with impact time and angle constraints for missiles in the presence of modeling errors. This innovative guidance scheme is composed of three parts: First, the model predictive static programming (MPSP) algorithm is used to design a nominal guidance method that simultaneously satisfies impact time and angle constraints. Second, the cubature Kalman filter (CKF) is introduced to estimate values of the influence of the inevitable modeling errors. Finally, a one-step compensation scheme is proposed to eliminate the modeling errors’ influence. The proposed method uses a real missile dynamics model, instead of a simplified one with a constant-velocity assumption, and eliminates the effects of modeling errors with the compensation scheme; thus, it is more practical. Simulations in the presence of modeling errors are conducted, and the results illustrate that the CKF-MPSP guidance method can reach the target with a high accuracy of impact time and angles, which demonstrates the high precision and strong robustness of the method.

Constrained control using novel nonlinear mapping for underactuated unmanned surface vehicles with unknown sideslip angle

This paper addresses the problem of guidance and control for underactuated unmanned surface vehicles (USVs) with state constraints and input saturation, in support of enabling an underactuated USV to follow a parameterized curved path in the case of unknown sideslip angle and cross-tracking error constraint. First, a cross-tracking error constraint line-of-sight (LOS) guidance law with sideslip angle compensation is originally designed to guide an underactuated USV to convergence to the desired path within a time-varying cross-tracking error constraint. Second, a novel nonlinear mapping (NM) function is first constructed to map the heading and surge control subsystems with state constraints to unconstrained nonlinear systems, transforming the constrained control problem into the unconstrained control problem. Subsequently, adaptive fuzzy control laws are designed to achieve the control objectives for the USV using the new unconstrained nonlinear systems with unknown disturbance and input saturation. Then, a series of theoretical analyses using input-to-state stability theories are presented to prove the boundness of the tracking errors for the underactuated USV during path following. Finally, numerical results obtained using a physics-based simulation model are shown to reveal the effectiveness of the guidance and control algorithms.

Synthesis of Suboptimal Guidance Law for Anti-Tank Guided Missile with Terminal Impact Angle Constraint Based on the SDRE Technique

In this paper, the homing-phase guidance law is proposed against a stationary target in the planar engagement scenario. In this problem, two technical criteria that the guidance law must achieve are: first, zero terminal miss distance, and second, satisfying the desired impact angle constraint at the final time. This guidance law is synthesized as a nonlinear optimal control problem with an infinite-time horizon and is solved using the state-dependent Riccati equation (SDRE) method. To obtain a guidance law with a finite-time horizon, a state weighting matrix based on the time-to-go is utilized in the SDRE control scheme. The synthesized guidance law is applied to a new generation anti-tank guided missile class, with specific thrust and drag parameters. Nonlinear simulations are conducted to demonstrate the fundamental properties, applicability, and effectiveness of the proposed guidance law.

Energy Minimization for Fixed-Wing UAV Assisted Full-Duplex Relaying With Bank Angle Constraint

In order to make turns, a fixed-wing unmanned aerial vehicle (UAV) needs to change its bank angle gradually. While banking at large angle and high velocity leads to an increased risk of stalling the aircraft. It means that there exists a bank angle constraint (BAC) for a flying UAV. However, BAC is often ignored in studies regarding a fixed-wing UAV assisted communications. This letter considers a fixed-wing UAV assisted full-duplex amplify-and-forward relaying with a BAC, where the UAV is flying along a circular path while forwarding a required amount of data-bits from a source to a destination. With the aim of minimizing the energy consumption, a joint optimization scheme for adjusting the UAV’s flight velocity, radius and time is developed. The effectiveness and efficiency of the proposed joint optimization scheme as well as the impact of the BAC on the optimization scheme are verified by computer simulations.

Angle-Constrained Formation Maneuvering of Unmanned Aerial Vehicles

In a global positioning system (GPS)-denied environment, unmanned aerial vehicles (UAVs) rely on local sensing-based formation maneuvering approaches for collective motion. To improve mission efficiency by reducing the total sensing requirements on all UAVs, this article proposes a leader–follower formation maneuvering framework with two leaders, where the followers will track the two leaders and maintain a desired angle-constrained formation with respect to the leaders using direction-only measurements, i.e., removing the need for inter-UAV distance measurements for the followers. To enable the UAV formation to maneuver in translation, rotation, and scaling simultaneously, the desired formation shape is specified by a set of interior angle constraints. By assigning each UAV’s yaw angle and position as the four controllable variables, an estimation-based attitude control algorithm is designed. For the UAVs’ position control, the designed formation maneuvering algorithm consists of a velocity tracking part and a formation shape control part that enables the first leader UAV to control the translational maneuvering, the second leader UAV to control the rotational and scaling maneuvering, and all the follower UAVs to maintain the formation shape. Simulations and experiments on UAVs’ formation maneuvering are conducted to illustrate the effectiveness of the proposed approach.

A new hybrid path planning method for the sailboat architecture wave glider in the wind field environment

To ensure efficient sailing of the SWG in complex marine environments and maintain its controllability in upwind or downwind conditions, a hybrid path planning method is proposed aiming at path time consumption and safety in this paper. The method includes a weight heuristic A* algorithm and a WAPF algorithm. The kinematic and dynamic models of the SWG are established, and the rotary diameter, velocity polar diagram, rotation constraint and dangerous wind angle constraint are obtained. To make better use of the fixed wind field environment and improve the efficiency of the algorithm, a weight heuristic A* algorithm is proposed for global path planning. The algorithm uses the form of weight-heuristic and reduces useless search directions. To ensure navigation safety and overcome the shortcomings of traditional APF algorithm, a WAPF algorithm for local path planning is proposed by introducing kinematic constraints and wind potential field into the algorithm model. Simulations are carried out and the results show that the proposed weight heuristic A* algorithm and WAPF algorithm are more suitable for the SWG navigation in the wind field environment than traditional path planning algorithms. The effectiveness of the WAPF algorithm is verified by sea trial and simulation comparison.

Research on Path Planning and Tracking Control of Autonomous Vehicles Based on Improved RRT* and PSO-LQR

Path planning and tracking control are essential parts of autonomous vehicle research. Regarding path planning, the Rapid Exploration Random Tree Star (RRT*) algorithm has attracted much attention due to its completeness. However, the algorithm still suffers from slow convergence and high randomness. Regarding path tracking, the Linear Quadratic Regulator (LQR) algorithm is widely used in various control applications due to its efficient stability and ease of implementation. However, the relatively empirical selection of its weight matrix can affect the control effect. This study suggests a path planning and tracking control framework for autonomous vehicles based on an upgraded RRT* and Particle Swarm Optimization Linear Quadratic Regulator (PSO-LQR) to address the abovementioned issues. Firstly, according to the driving characteristics of autonomous vehicles, a variable sampling area is used to limit the generation of random sampling points, significantly reducing the number of iterations. At the same time, an improved Artificial Potential Field (APF) method was introduced into the RRT* algorithm, which improved the convergence speed of the algorithm. Utilizing path pruning based on the maximum steering angle constraint of the vehicle and the cubic B-spline algorithm to achieve path optimization, a continuous curvature path that conforms to the precise tracking of the vehicle was obtained. In addition, optimizing the weight matrix of LQR using POS improved path-tracking accuracy. Finally, this article’s improved RRT* algorithm was simulated and compared with the RRT*, target bias RRT*, and P-RRT*. At the same time, on the Simulink–Carsim joint simulation platform, the PSO-LQR is used to track the planned path at different vehicle speeds. The results show that the improved RRT* algorithm optimizes the path search speed by 34.40% and the iteration number by 33.97%, respectively, and the generated paths are curvature continuous. The tracking accuracy of the PSO-LQR was improved by about 59% compared to LQR, and its stability was higher. The position error and heading error were controlled within 0.06 m and 0.05 rad, respectively, verifying the effectiveness and feasibility of the proposed path planning and tracking control framework.

Barrier Lyapunov function and adaptive backstepping-based control of a quadrotor UAV

AbstractThis paper presents backstepping control and backstepping constraint control approaches for a quadrotor unmanned aerial vehicle (UAV) control system. The proposed methods are applied to a Parrot Mambo drone model to control rotational motion along the $x$ , $y$ , and $z$ axes during hovering and trajectory tracking. In the backstepping control approach, each state of the system controls the previous state and is called “virtual control.” The last state is controlled by the real control input. The idea is to compute, in several steps, a control law that ensures the asymptotic stability of the system. The backstepping constraint control method, based on barrier Lyapunov functions (BLFs), is designed not only to track the desired trajectory but also to guarantee no violation of the position and angle constraints. Symmetric BLFs are introduced in the design of the controller. A nonlinear mathematical model is considered in this study. Based on Lyapunov stability theory, it can be concluded that the proposed controllers can guarantee the stability of the UAV system and the state converges asymptotically to the desired trajectory. To make the control robust, an adaptation law is applied to the backstepping control that estimates the unknown parameters and ensures their convergence to their respective values. Validation of the proposed controllers was performed by simulation on a flying UAV system.

Appointed-Time Cooperative Guidance Law With Line-of-Sight Angle Constraint and Time-to-go Control

This study proposes a three-dimensional appointed-time cooperative guidance law for multiple missiles. The maneuvering target can be hit simultaneously by multiple missiles with different expected line-of-sight (LOS) angles. It is worth noting that the actual convergence time of the LOS error or time-to-go can be treated as a tuning parameter along the LOS direction and the normal direction of LOS. Firstly, the simultaneous attack problem of multiple missiles can be regarded as a consensus problem. In the LOS direction, a distributed cooperative guidance law is presented to guarantee the time-to-go of all missiles to be consensus at the appointed time. Subsequently, a guidance law is also presented in the normal direction of LOS to achieve the expected LOS angles at the appointed time. Finally, to improve the robustness of the cooperative guidance system, an appointed-time extended state observer (ATESO) is developed for compensating the guidance commands. The stability of the proposed cooperative guidance law is fully proved by the rigorous theoretical derivation. Numerical simulation results verify the efficacy of this scheme.