Tracking Guidance Research Articles

Guidance Method with Collision Avoidance Using Guiding Vector Field for Multiple Unmanned Surface Vehicles

For the guidance problem of trajectory tracking in multiple unmanned surface vehicles (USVs), a trajectory tracking guidance method with collision avoidance based on a novel guiding vector field is proposed. Firstly, within the framework of the virtual leader–follower method for formation control, a tracking error model for followers is developed based on the motion model of USVs. Secondly, considering the limitations of conventional trajectory tracking guidance methods in addressing various initial error conditions, a novel guiding vector field is developed for the design of the heading guidance law to enhance tracking performance. Then, a multi-USV collision avoidance strategy is proposed for formation navigation safety. The trigger conditions, actions and release conditions for collision avoidance are established in this strategy. USVs could avoid collision in time by following the commands outlined in the strategy, especially in complex situations where multiple USVs are simultaneously at risk of colliding with each other. And the theoretical proof is completed. Furthermore, the heading and velocity guidance laws are designed by combining the guidance vector field and the collision avoidance strategy. It is demonstrated that the tracking errors of the system are uniformly bounded based on Lyapunov stability theory. Finally, the effectiveness of the method is verified through simulation.

Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

A tracking guidance method with funnel scheduling for Mars landing

A tracking guidance method with funnel scheduling for Mars landing

Terminal Line-of-Sight Angle-Constrained Target Tracking Guidance for Unmanned Surface Vehicles

Terminal Line-of-Sight Angle-Constrained Target Tracking Guidance for Unmanned Surface Vehicles

Pseudospectral-Based Rapid Trajectory Planning and Feedforward Linearization Guidance

A trajectory-based guidance strategy is proposed for the three-dimensional terminal return task of an uncrewed space vehicle (USV). The overall guidance scheme consists of reference trajectory planning and robust trajectory tracking modules. The trajectory planning algorithm involves determining the motion of the USV to achieve a prescribed target under multiple constraints. The altitude-domain-based USV model is firstly proven to be differentially flat utilizing the dynamic pressure and position of the USV as flat outputs. The original trajectory planning problem is reformulated in a lower-dimensional flat output space. The discretization of the planning problem is then achieved using the pseudospectral method, based on which an initial guess technique is designed in order to accelerate the solving speed of the planning algorithm. Subsequently, a feedforward linearization-based trajectory tracking guidance law is designed using the differential flatness property of the altitude-domain model. Simulation results in different scenarios show that the proposed guidance strategy provides a satisfactory guidance solution.

Three-dimensional line-of-sight-angle-constrained leader-following cooperative interception guidance law with prespecified impact time

Three-dimensional line-of-sight-angle-constrained leader-following cooperative interception guidance law with prespecified impact time

Augmented reality navigation method based on image segmentation and sensor tracking registration technology

With the rapid development of modern science and technology, navigation technology provides great convenience for people's life, but the problem of inaccurate localization in complex environments has always been a challenge that navigation technology needs to be solved urgently. To address this challenge, this paper proposes an augmented reality navigation method that combines image segmentation and multi-sensor fusion tracking registration. The method optimizes the image processing process through the GA-OTSU-Canny algorithm and combines high-precision multi-sensor information in order to achieve accurate tracking of positioning and guidance in complex environments. Experimental results show that the GA-OTSU-Canny algorithm has a faster image edge segmentation rate, and the fastest start speed is only 1.8 s, and the fastest intersection selection time is 1.2 s. The navigation system combining the image segmentation and sensor tracking and registration techniques has a highly efficient performance in real-world navigation, and its building recognition rates are all above 99%. The augmented reality navigation system not only improves the navigation accuracy in high-rise and urban canyon environments, but also significantly outperforms traditional navigation solutions in terms of navigation startup time and target building recognition accuracy. In summary, this research not only provides a new framework for the theoretical integration of image processing and multi-sensor data, but also brings innovative technical solutions for the development and application of practical navigation systems.

Robust Trajectory Planning of Gliding-Guided Projectiles with Weak Maneuverability

Due to constraints in launch platforms and cost, the maneuverability of gliding-guided projectiles is limited, necessitating a rational design of their trajectory schemes. To reduce the sensitivity of trajectory schemes to uncertainties while ensuring compatibility between flight schemes and guidance control systems and fully exploiting the control capability of the projectile, a closed-loop robust trajectory planning method is proposed. Models of major uncertain factors and state deviation at the control start point are established. Based on the NIPCE method, the stochastic dynamic model is transformed into a high-dimensional deterministic model with PCE coefficients as state variables, and the uncertainty propagation law is obtained. A PID algorithm is employed to design a tracking guidance law based on position error feedback, and open-loop and closed-loop robust trajectory planning models are established accordingly. The optimal control problem is solved by transforming it into a nonlinear programming problem using the direct shooting method. Our simulation results indicate that the NIPCE method can significantly improve the computational efficiency of uncertainty propagation while ensuring accuracy; compared with parallel MCS, the computation time is reduced by 96.8%. Open-loop robust planning can effectively mitigate the sensitivity of gliding trajectories to uncertainties (the standard deviations of terminal altitude and lateral deviations are reduced by 23.6% and 35.3%, respectively, compared to deterministic planning) but cannot completely eliminate terminal dispersion. Closed-loop robust planning effectively improves control effort consumption on the basis of open-loop planning.

All-Wheel Steering Tracking Control Method for Virtual Rail Trains with Only Interoceptive Sensors

A virtual rail train (VRT) is a multi-articulated vehicle as well as a novel public transportation system due to its low economic cost, environmental friendliness and high transit capacity. Equipped with all-wheel steering (AWS) and a tracking control method, the super long VRT can travel on urban roads easily. This paper proposed a tracking control approach using only interoceptive sensors with high scene adaptivity. The kinematic model was established first under reasonable assumptions when the sensor configuration was completed simultaneously. A hierarchical controller consists of a front axle controller and a rear axle controller. The former applies virtual axles theory to avoid motion interference. The latter generates a first-axle reference path with path segmentation and a data updating method to improve storage and computational efficiency. Then, a fast curvature matching rear axles control method is developed with an actuator time delay considered. Finally, the proposed approach is verified in a hardware in loop (HIL) simulation under various situations with predefined evaluation standards, which shows better tracking performance and applicability.

Research on layered control of path tracking for unmanned industrial vehicles based on fully hydraulic steering leakage compensation

Industrial vehicles work in complex terrain, the variable centre of mass position, leakage nonlinearity of full hydraulic steering and other issues lead to poor path tracking stability and accuracy. In this paper, an intelligent hierarchical controller for industrial vehicles’ path tracking is designed with full hydraulic steering leakage compensation, including an upper decision layer and a lower execution layer. The upper decision layer observes the pavement-tyre adhesion coefficients through an extended Kalman filter algorithm, and uses the real-time observations of the adhesion coefficients to establish a variable constraint control for the linear time-varying MPC, and thus performs the path tracking control. The lower actuator layer receives the upper layer’s target steering wheel angle output and performs steering operations. Based on the establishment of a mathematical model of full hydraulic steering considering the leakage characteristics, it analyses the leakage disturbance factors and constructs a fuzzy feed-forward steering leakage compensation controller to compensate for the leakage disturbances in real time for path tracking steering. Simulation and experimental results show that the lateral acceleration, sideslip angle, tyre side slip angle and tracking error of intelligent industrial vehicles under different loads and working conditions are improved by more than 32.4%, 35.8%, 40.2% and 45.8% respectively, and the designed hierarchical controller for the path tracking of intelligent industrial vehicles, which considers the compensation of all-hydraulic steering leakage, can effectively improve the path tracking stability and tracking accuracy of intelligent industrial vehicles under different loads and working conditions.

A Target Tracking Guidance for Unmanned Surface Vehicles in the Presence of Obstacles

A Target Tracking Guidance for Unmanned Surface Vehicles in the Presence of Obstacles

High-performance steering tracking control of open circuit variable-speed pump-controlled steering system for heavy-duty vehicles based on flow nonlinearity compensation

Heavy-duty vehicles with long bodies, a large number of axles and large loads are subject to increasingly high requirements for precise steering technology due to the increasing trend toward energy conservation and intelligent assisted driving as well as variable driving conditions. In this paper, an energy-efficient open circuit variable-speed pump-controlled steering system (OPCEHSSS) adapted for heavy loads is used, but its strong flow output nonlinearity and system nonlinear dynamic behavior greatly impede the steering performance. Therefore, in order to reduce the influence of the flow leakage of the fixed-displacement pump on the system and to ensure that the flow output of the system matches the control model, a mapping model based on the fitting of a two-layer neural network algorithm with a dynamic real-time compensation strategy (FNC) is proposed. In addition, considering the strong robustness of the system even under parameter uncertainty and unknown disturbance, a complex nonlinear mathematical model is established based on OPCEHSSS physical characteristics, and a dual-objective control strategy of steering angle and pressure based on sliding mode control (SMC) is proposed. However, in order to reduce the influence of high-order switching discontinuity on the steering and ensure the fast convergence of the control system, a fast super twisting algorithm (STA) based on double saturation function of the boundary layer is proposed. The experimental results show that the three different controllers can effectively reduce the steering angle error after the introduction of FNC. And in the case of a single axle loaded with 6 tons, the improved new FNC+STA integrated dual-objective control strategy improves the accuracy by 53.16% compared with PID and 40.67% compared with SMC. The steady-state error is maintained within 0.9°, realizing the high-performance steering tracking control of OPCEHSSS for heavy vehicles.

Multiple Leap Maneuver Trajectory Design and Tracking Method Based on Prescribed Performance Control during the Gliding Phase of Vehicles

A novel standard trajectory design and tracking guidance used in the multiple active leap maneuver mode for hypersonic glide vehicles (HGVs) is proposed in this paper. First, the dynamic equation and multiconstraint model are first established in the flight path coordinate system. Second, the reference drag acceleration-normalized energy (D-e) profile of the multiple active leap maneuver mode is quickly determined by the Newton iterative algorithm with a single design parameter. The range to go error is corrected by the drag acceleration profile update algorithm, and the drag acceleration error of the gliding terminal is corrected by the aerodynamic parameter estimation algorithm. Then, the reference drag acceleration tracking guidance law is designed based on the prescribed performance control method. Finally, the CAV-L vehicle model is used for numerical simulation. The results show that the proposed method can satisfy the design requirements of drag acceleration under multiple active leap maneuver modes, and the reference drag acceleration can be tracked precisely. The adaptability and robustness of the proposed method are verified by the Monte Carlo simulations under various combined deviation conditions.

Motion-pressure coupled control and simulation of long-endurance capability for multicapsule stratospheric airships

Motion-pressure coupled control and simulation of long-endurance capability for multicapsule stratospheric airships

Adaptive tracking guidance for powered aeroassisted orbital maneuver under system uncertainties and input constraints

Adaptive tracking guidance for powered aeroassisted orbital maneuver under system uncertainties and input constraints

Optimal guidance track generation for precision agriculture: A review of coverage path planning techniques

AbstractThe Complete Coverage Path Planning (CCPP) problem is a subfield of industrial motion planning that has applications in various domains, ranging from mobile robotics to treatment applications. Especially in precision agriculture with a high level of automation, the use of CCPP techniques is essential for efficient resource utilization, reduced soil compaction, and increased yields. This paper reviews the CCPP problem in the context of machines operating in agricultural fields and proposes a methodological approach consisting of three steps: Generating the Guidance Tracks (i.e., the track system along which the path should be oriented), determining the traversing sequence through these tracks, and planning a smooth and drivable path. This paper provides an in‐depth review of optimization‐based approaches that deal with the first step, the generation of the guidance track system. Thereby, a comprehensive and pedagogical approach for the generation of guidance tracks for arbitrarily shaped two‐dimensional regions of interest is provided, along with an overview and detailed elaboration on different exact cellular decomposition techniques found in literature. Furthermore, cost functions are outlined for the different approaches presented in this work, which are utilized to generate optimal guidance tracks. Finally, this survey serves as an introductory guide for research and practitioners to solve the CCPP problem effectively and efficiently.

An improved LOS Guidance and Sail-Rudder Cooperative Controller for the Path Tracking of Unmanned Sailboats

An improved LOS Guidance and Sail-Rudder Cooperative Controller for the Path Tracking of Unmanned Sailboats

Path and control-constrained longitudinal guidance for Mars entry

Path and control-constrained longitudinal guidance for Mars entry

Aerial refueling rendezvous routes for UAVs based on nonlinear guide laws

The route fusion rendezvous strategy is mostly used for air refueling within the safety zone, with fewer restrictions on the rendezvous airspace. There are fewer restrictions on the combined airspace. The refueling aircraft follows a set route, and the UAV gradually converges with the refueling aircraft by adjusting its own course. The UAVs gradually merge with the fueler’s route until they track the fueler to a certain distance behind the fueler and synchronize with the fueler’s status. The subsequent docking process is carried out.The fused route design is analogous to the use of missiles to track and strike moving targets. The unmanned aircraft are treated as pursuers moving at high speed. The fueling aircraft are treated as targets moving in a fixed pattern to be returned. The main objective of the convergent route design is to draw on and select appropriate guidance laws to bring the unmanned aircraft close to the fuel tanker. The main objective of the route fusion design is to use and select a suitable guidance law that allows unmanned aircraft to approach the fueling aircraft and achieve autonomous rendezvous. The traditional navigation laws are Pure Pursuit (PP) and Proportional Navigation (PP). The basic idea is to change the speed vector of a drone by varying its size. The difference is that the pure tracking guidance law requires the speed vector of the drone to coincide with the line of sight. In contrast, the example guidance law starts from the fact that the angular rate of rotation of the drone’s speed vector and the ratio guiding law is to keep the angular rate of rotation of the speed vector of the drone and that of the target in a fixed proportion.

Extended state observer based fractional order sliding mode control for steer‐by‐wire systems

AbstractIn this paper, an extended state observer based fractional‐order sliding mode control strategy is studied for vehicle steer‐by‐wire systems (SBWSs). The parameter perturbation and external interference are considered in the dynamic model of SBWSs. A fractional‐order sliding mode control scheme is designed to solve the tracking problem and improve the control performance. An extended state observer is further used to estimate the lumped disturbance, and then the estimated value is considered as a feedforward compensation to reduce the chattering phenomenon. Finally, comparison simulation results show that the excellent steering tracking and strong robustness performance have been achieved by the proposed control strategy for SBWSs.