Complex Trajectory Tracking Research Articles

Cascade Model Predictive Control for Enhancing UAV Quadcopter Stability and Energy Efficiency in Wind Turbulent Mangrove Forest Environment

Unmanned aerial vehicle (UAV) modelling and control, particularly in quadrotors with high position-orientation coupling, present significant challenges for practical applications, such as environmental monitoring missions in windy mangrove forests. Conventional control strategies like the PID controller, often employed in simulations due to their simplicity, often underperform in real-world scenarios due to their linear assumptions. This research proposes a novel hierarchical cascaded model predictive control system for altitude, attitude, and battery efficiency for quadrotor in mangrove area. This control system addresses computational complexity by decomposing the overall MPC strategy into two distinct schemes, one for translational displacements and another for rotational movements, enhancing the UAV's resilience to wind turbulence, a significant disturbance factor in mangrove environments. Rigorous simulation and experiment test flight involving complex trajectory tracking and windy conditions demonstrate the proposed controller's superior performance compared to conventional PID controller, particularly in terms of stability, disturbance rejection, underscoring its potential for UAV applications in challenging environments.

Motion/force coordinated trajectory tracking control of nonholonomic wheeled mobile robot via LMPC-AISMC strategy

Nonholonomic constrained wheeled mobile robot (WMR) trajectory tracking requires the enhancement of the ground adaptation capability of the WMR while ensuring its attitude tracking accuracy, a novel dual closed-loop control structure is developed to implement this motion/force coordinated control objective in this paper. Firstly, the outer-loop motion controller is presented using Laguerre functions modified model predictive control (LMPC). Optimised solution condition is introduced to reduce the number of LMPC solutions. Secondly, an inner-loop force controller based on adaptive integral sliding mode control (AISMC) is constructed to ensure the desired velocity tracking and output driving torques by combining second-order nonlinear extended state observer (ESO) with the estimation of dynamic uncertainties and external disturbances during WMR travelling process. Then, Lyapunov stability theory is utilised to guarantee the consistent final boundedness of the designed controller. Finally, the system is numerically simulated and practically verified. The results show that the double-closed-loop control strategy devised in this paper has better control performance in terms of complex trajectory tracking accuracy, system resistance to strong interference and computational timeliness, and is able to realise effective coordinated control of WMR motion/force.

Multi-stage trajectory tracking control design under comprehensive constraints based on Generalized Udwadia–Kalaba theory

A novel control design based on Generalized Udwadia–Kalaba (GUK) theory is proposed to achieve the trajectory tracking under comprehensive constraints in this paper. To describe the complex task requirements, a constraint framework including equality and inequality constraints is constructed. Thus, the complex trajectory tracking problem is converted into a constraint-following problem. Based on the framework above, GUK equation is introduced to consider the equality and inequality constraints individually. Specifically, the equality constraints are transformed into second-order matrix form, while the inequality constraints are addressed via a diffeomorphism. Then, a novel control method including servo control term and high-order control term is proposed. Through these two control terms, the constraint forces for equality and inequality can be solved separately. The effectiveness of this control method is verified by the stability analysis based on Lyapunov minimax apprach and illustrative application of unmanned surface vehicle (USV). Meanwhile, the superiority of this method is demonstrated through a comparative analysis with Udwadia–Kalaba (UK) method, Linear Quadratic Regulator (LQR) method and sliding mode control (SMC) method.

Based on graph theory, design of distributed control system for multi-quadcopter UAVs

This paper addresses the formation control system for multi-quadcopter UAVs, proposing a control strategy based on finite-time stability theory. It designs position controllers with a dual power structure and attitude controllers combined with non-singular terminal sliding mode to achieve fast convergence and high-precision tracking. Through Lyapunov stability analysis, the paper proves the finite-time convergence of the control strategy. Simulation experiments validate the method's excellent performance in formation establishment, maintenance, and complex trajectory tracking, demonstrating rapid convergence, high precision, and strong disturbance rejection capabilities. This research provides theoretical and technical support for cooperative control of multi-quadcopters.

Self-powered noncontact triboelectric nanogenerators with microstructured square-loop surface and dielectric electron-blocking layer for far-distance motion perception and trajectory tracking

Continuous monitoring of indoor human activities is crucial for the healthcare of elder people or patients. The self-powered noncontact triboelectric nanogenerator (TENG) sensor has been recently developed as a promising noncontact sensing tool with many advantages, but its capability of detecting object motion in a far distance still remains inferior. Herein, by implementing multiple strategies of micro-structuring triboelectric surface, introducing dielectric layer, and using functional nano fillers, we develop a single-electrode-mode noncontact TENG sensor by constructing a triboelectric cobalt nanoporous carbon/Ecoflex nanocomposite layer with microstructured square-loop surface on top of a dielectric copper calcium titanate/Ecoflex nanocomposite layer with colossal permittivity. After in-depth optimization of the material selection, component composition and structure design, the developed sensor with effective electrode area of 6.25 cm2 can deliver a high output voltage of 29 V at 1 cm, and is capable of detecting motions at an extremely far distance of 6 m. Towards practical applications, the TENG unit for single-motion detection of mouth breathing, human walking, and basketball bouncing are demonstrated. Furthermore, multiple TENG units can be assembled into array to realize the complex trajectory tracking for the use of proximity touch pad, indoor human activity monitoring, and garage car parking. This work for the first time extends the TENG noncontact sensing capability to several meters, which is potential in the proximity motion detection and indoor activity monitoring.

Design and analysis of tracking differentiator based on SO(3)

Motivated by the issue of insufficient dynamic performance and tracking accuracy in SO(3)-based attitude tracking differentiators during large-angle maneuvers and complex trajectory tracking, a novel design approach for a three-degree-of-freedom attitude tracking differentiator within the SO(3) framework is proposed by incorporating second-order system theory and Lie group theory and improving the classical tracking differentiator. The kinematics model and error dynamics model of a rigid body on SO(3) are derived, and a reasonable virtual control input on SO(3) is constructed subsequently in order to achieve better dynamic response and tracking performance. Simulation and experimental results validate that the designed tracking differentiator could realize rapid and smooth convergence during large-angle maneuvers, and the initial large tracking error rapidly drops to near zero in a short period of time; additionally, it can also track expected time-varying curves well in complex trajectory tracking, with initial errors rapidly decreasing and maintaining at normal levels, demonstrating excellent tracking and control capabilities. There are strong application prospects for this new approach in addition to its theoretical significance.

Adaptive Terminal Sliding Mode Trajectory Tracking Control for Autonomous Vehicles Considering Completely Unknown Parameters and Unknown Perturbation Conditions

In the actual implementation of autonomous vehicle controller and related applications, it is difficult to obtain all the actual parameters of the vehicle. Considering factors such as uneven pavement and different pavement conditions, it is difficult to accurately establish the vehicle dynamic system model. Based on the non-singular terminal sliding mode and adaptive control theory, this paper establishes a trajectory tracking control strategy for an autonomous vehicle with unknown parameters and unknown disturbances. Firstly, the complex trajectory tracking problem is decoupled from the position and heading angle tracking problem, and the preview error equation is established. Secondly, a non-singular terminal sliding mode (NTSM) controller is established to stabilize the trajectory tracking error to the origin in a finite time, and adaptive laws are proposed to estimate the unknown vehicle parameters to adapt to environmental changes. Through the CarSim–Matlab platform, typical working conditions are implemented to verify the proposed controller. Our experimental outcomes affirm that the NTSM controller effectively guarantees the autonomous vehicle’s accurate following of the reference path, ensuring smooth control inputs throughout the entire process.

Structural design and experimental evaluation of a coarse-fine parallel dual-actuation XY flexure micropositioner with low interference behavior.

This paper proposes a novel two degree of freedom large range coarse-fine parallel dual-actuation flexure micropositioner (CFPDFM) with low interference behavior. First, the structure and working principle of the CFPDFM are introduced. Then, based on the stiffness matrix method, the analytical models of the motion range, input stiffness, and amplification ratio of the mechanism are established. Subsequently, the accuracy of the analytical model is verified by finite element analysis and experiments. Moreover, the dual-servo cooperative drive control strategy is designed to improve the closed-loop positioning ability of the CFPDFM. Finally, the CFPDFM experimental system is built to verify the plane trajectory tracking performance. The results reveal that the micropositioner can achieve a total range of 3.02 × 3.11mm2, a resolution of ≤40nm, low interference performance of coarse and fine actuators, good cross-axis decoupling, and planar complex trajectory tracking performance, while possessing a compact structure. It can be used in many plane positioning situations requiring large range and high precision.

Finite-time prescribed performance trajectory tracking control for the autonomous underwater helicopter

To address the complex trajectory tracking problem of AUH near the seabed when performing high-precision operations such as comprehensive underwater inspections for offshore engineering structures, a prescribed performance control strategy with a finite-time performance function (FTPF) and the fast terminal sliding surface is proposed. The influence of ocean current is fully considered by the combination of ocean current velocity estimated by a current observer and ocean current disturbance in the dynamic model. An arctan-type disturbance observer and neural network are designed to compensate for environmental disturbances, model uncertainty, and thruster failure effects on the system. The system stability is proven by the Lyapunov method, and the numerical simulation shows that the proposed scheme is effective, robust, and efficient, even under disturbances and thruster failure.

Force-torque (F-T) based multi-drone cooperative transport using fuzzy logic and low-cost and imprecise F-T sensor

This paper presents a novel approach to perform the task of cooperative transportation (CT) by using multiple quadcopter drones. A leader-follower approach is utilized. Considering that the leader drone can be controlled using different means, such as Proportional, Integral, and Derivative (PID) control or remote control by an operator, this paper focuses on designing the control scheme for the follower drone. This paper specifically considers outdoor application of such systems that requires usage of Global Positioning System (GPS) to receive the positional information of the drones. However, GPS has inherent errors of order of magnitude that can destabilize the system. In order to address this major limitation, a Force-Torque Feedback Controller (FT-FC) is proposed to control the follower drone. The FT-FC provides control based on the interaction forces and torques acting at the point of contact between the follower drone and the payload. Using such passive control schemes, drones are thus not required to communicate with each other. Fuzzy Logic (FL) is used to implement the FT-FC. Fuzzy Logic provides effective force-torque coordination between drones, emulates human behavior during CT, and allows use of noisy inexpensive force-torque sensors. This paper presents results from numerical simulations showing the effectiveness of the proposed controller for way-point navigation and complex trajectory tracking. Additionally, the effectiveness of the fuzzy-based FT-FC in terms of handling disturbances is also demonstrated. The proposed FL FT-FC is also experimentally validated for two applications viz. three-dimensional physical Human Drone Interaction (HDI) and CT.

Design of Particle Swarm Optimization Adaptive Sliding Mode Controller Based on an Extended State Observer for the Longitudinal Motion of a Supercavitating Vehicle with Input Saturation

The aim of this paper is to present a novel sliding mode control scheme for the supercavitating vehicle trajectory tracking problem that subjects to external disturbances and actuator saturation with two symmetric elevators and a cavitator as actuators by analytical methods and computer simulations. Firstly, the nonlinear and highly coupled dynamic and kinematic models of a supercavitating vehicle are presented in a comprehensive way by taking the cavity memory effect and time‐variant planing force into consideration. The PSO algorithm is employed to optimize the control parameters for achieving better and more practical tracking performance by minimizing the objective function. A second‐order extended state observer (ESO) is utilized to estimate the unknown external and state‐dependent disturbances and compensates for control inputs. In addition, an antiwindup compensator is adopted to cope with actuator saturation. Finally, the proposed control scheme is employed for complex trajectory tracking of a supercavitating vehicle under various conditions by conducting comparative numerical simulations. Rigorous theoretical analysis and simulation results indicate that the proposed control scheme can achieve satisfactory tracking performance and have a good capability of robustness.

Active Disturbance Rejection Control of Quadrotor UAVs Based on Joint Observation and Feedforward Compensation

Under the influence of uncertain parameters and external disturbance, the accuracy is low and the response is slow of attitude and trajectory tracking in the flight control of the quadrotor unmanned air vehicles (UAV). In order to solve the problems, Because of the excellent adaptability and noise suppression ability of the extended Kalman filter for nonlinear system problems , it is used to suppress the high-frequency signal disturbance to reduce the estimation burden of the extended state observer, and jointly with the expanded state observer to estimate the total disturbance formed by the system uncertainty parameters and external disturbances to reduce system reliance on accurate models, and the differential values of perturbation estimated values is used by feedforward compensation to improve the tracking accuracy under abrupt disturbances and to overcome the phase lag caused by abrupt disturbances. Extended Kalman filtering, extended state observer with the feedforward compensation and PD controller with error compensation are comprehensively integrated into an improved active disturbance rejection controller which can suppress high frequency noise and abrupt disturbances to the better extent. Simulation and experiment results show that the joint observer can effectively reduce the observation error amplitude, correct the observation phase lag in advance, and obtain more accurate state information, and that the improved active disturbance rejection controller can better meet requirements of quadrotor UAV for fast response, efficient and stable control. Therefore, it can accurately and efficiently complete complex trajectory tracking operations.

Representation of New Variable Thrust Vector Underwater Robotic Platform for Complex Trajectory Tracking

Representation of New Variable Thrust Vector Underwater Robotic Platform for Complex Trajectory Tracking

A Robust Hybrid Control for Autonomous Flying Robots in an Uncertain and Disturbed Environment

With the aim of efficiently achieving complex trajectory tracking missions in the presence of model uncertainties and exogenous disturbances, this paper proposes a robust hybrid control for the orientation and position of flying robots by adopting insights from sliding mode, geometric tracking, and nonlinear feedback control strategies. Various retrofits are implemented to the composite control scheme in order to tackle the system uncertainties, eliminate the chattering effects, and enhance the trajectory tracking performance. The convergence and stability analysis demonstrated the asymptotic stability of the proposed control algorithm. To reveal the promising performance of the developed control schemes, a qualitative comparative analysis of different proposed control approaches is performed. The comparative analysis examines highly maneuverable trajectories for various tracking scenarios in the presence of uncertain disturbances. The simulation results demonstrated the versatility, robustness, and convergence of the developed control laws that allow autonomous flying robots to effectively perform agile maneuvers.

Complex Trajectory Tracking Using PID Control for Autonomous Driving

In this paper, a Proportional-Integral-Differential (PID) controller that facilitates track maneuvering for self-driving cars is proposed. Three different design approaches are used to find and tune the controller hyper-parameters. One of them is “WAF-Tune”, which is an ad hoc trial-and-error based technique that is specifically proposed in this paper for this specific application. The proposed controller uses only the Cross-Track-Error (CTE) as an input to the controller, whereas the output is the steering command. Extensive simulation studies in complex tracks with many sharp turns have been carried out to evaluate the performance of the proposed controller at different speeds. The analysis shows that the proposed technique outperforms the other ones. The usefulness and the shortcomings of the proposed tuning mechanism are also discussed in details.

ANFIS-based an adaptive continuous sliding-mode controller for robot manipulators in operational space

This paper addresses the task-space robust trajectory tracking control problem for robot manipulators in the presence of uncertainties and external disturbances. First, a discontinuous sliding-mode controller-based inverse dynamics control strategy (IDSMC) with discontinuous robust control action is synthesized. Second, an adaptive inverse dynamics controller based on continuous sliding-mode control (AIDCSMC) is designed, in which the adaptation laws are addressed to compensate for the unknown parameters of the dynamical model of robot manipulators. The global stability of the closed-loop control system is proven using the Lyapunov theorem and the proposed AIDCSMC controller is further proven to guarantee convergence to zero of both trajectory tracking error and error rate. Finally, a hybrid intelligent neuro-fuzzy adaptive fuzzy inference system (ANFIS)-based adaptive inverse dynamics controller with continuous sliding-mode control (ANFIS-AIDCSMC) is adopted. Numerical simulations using the dynamic model of rigid robot manipulators with uncertainties show the effectiveness of the presented approach in simple and complex trajectory tracking problems. The simulation results indicate that the control performance of the robot system is satisfactory, and the proposed approach can achieve favorable tracking performance and it is robust with regard to uncertainties.

Complex Trajectory Tracking of Inverted Pendulum Using PID and LQR

has been studied excessively in control literature. Trajectory tracking of the inverted pendulum is one issues in this field. In this paper, the three methods of controllers are applied to tracking control of inverted pendulum. Simulation results prove that the linear quadratic regulator (LQR) controller is better than (proportional-integral-derivative) PID controller with the white noise input in the tracking trajectory. PID controller and LQR controller both can tracking the trajectory very well.

Modeling and Adaptive Flight Control for Quadrotor Trajectory Tracking

In the near future, unmanned aerial vehicles are probably going to be included in the airspace. Therefore, air traffic management needs to be enhanced in terms of reliability, safety, and accuracy. The main objective of this paper deals with a quadrotor flight control system that generates the necessary control laws to perform accurately, as well as possible, the reference flight trajectories. In this paper, a new quadrotor flight dynamics is developed, including an adopted wind model component where a study of the minimum phase and observability conditions is performed. Based on an adaptive backstepping control algorithm, a developed flight control system generates nonlinear control laws in an iterative and systematic procedure design. In addition to some simulations in a no-wind situation, the proposed adaptive flight control system is simulated in a windy flight condition. The design of adaptation laws according to some quadrotor parameters is developed, and the global stability of the proposed flight control system is guaranteed using the Lyapunov theory. Numerical simulations are performed for the quadrotor engaged in complex trajectory tracking, and obtained results show the feasibility and effectiveness of the proposed control approach.

Repetitive model predictive control for precise control of complex trajectory tracking in dual-stage actuator systems

This article presents a predictive control methodology for the precise tracking of complex reference commands in dual-stage actuator systems. To improve synchronized motion control performance, a cost function was applied to account for dual-stage actuator tracking error as well as tracking error in the first-stage actuator. The dual-stage actuator control system uses repetitive model predictive control with two repetitive controllers to reduce the occurrence of periodic errors. As in precision machining, a complex reference trajectory containing two dynamic tracking signals with non-trivial magnitude and frequency orders in a motor/piezoelectric-driven dual-stage actuator system was used to evaluate the practicability of the proposed repetitive model predictive control method. Experimental results demonstrate the efficacy of the proposed repetitive model predictive control system in enhancing the periodic tracking control of dual-stage actuator systems, even when subjected to persistent short pulse disturbance.

Robust nonlinear PID-like fuzzy logic control of a planar parallel (2PRP-PPR) manipulator

In this paper, a robust nonlinear proportional–integral–derivative (PID)-like fuzzy control scheme is presented and applied to complex trajectory tracking control of a 2PRP-PPR (P-prismatic, R-revolute) planar parallel manipulator (motion platform) with three degrees-of-freedom (DOF) in the presence of parameter uncertainties and external disturbances. The proposed control law consists of mainly two parts: first part uses a feed forward term to enhance the control activity and estimated perturbed term to compensate for the unknown effects namely external disturbances and unmodeled dynamics, and the second part uses a PID-like fuzzy logic control as a feedback portion to enhance the overall closed-loop stability of the system. Experimental results are presented to show the effectiveness of the proposed control scheme.