Tracking Control Scheme Research Articles

Disturbance Observer-Based Fixed-Time Tracking Control for a Tilt Trirotor Unmanned Aerial Vehicle

This paper proposed a new fixed-time trajectory tracking control strategy based on the disturbance observer (DOB) for a tilt trirotor unmanned aerial vehicle (TTUAV) which is subject to unknown external disturbances. To facilitate the TTUAV's trajectory tracking controller design, the dynamic model of the TTUAV is divided into two subsystems, the position subsystem (outer-loop) and the attitude subsystem (inner-loop). For the dynamics of the TTUAV's outer-loop, the unknown external disturbances consist of the unknown wind disturbances, the unknown aerodynamic frictions forces, the lateral force generated by the rear servo and the states coupling between the outer-loop and the inner-loop. Then, a nonlinear DOB is designed to estimate the unknown external disturbances, and a nonsingular terminal sliding-mode controller (NTSMC) is further developed to drive the TTUAV's position tracking errors to zero in a fixed time. For the dynamics of the TTUAV's inner-loop, the unknown external disturbances are mainly introduced by the aerodynamic frictions torques. Then, a modified sliding mode controller is designed to reject the unknown external disturbances, and to ensure that the attitude tracking errors converge to zero exponentially. In addition, a composite stability analysis based on Lyapunov stability theory is provided to guarantee the fixed-time convergence of the closed-loop dynamics of the TTUAV. Finally, the results of the real-time experiments are presented to verify the effectiveness of the proposed control strategy.

Prescribed time formation synchronous tracking of unmanned aerial vehicles with denial of service attacks

This paper addresses the issue of robust prescribed time synchronous tracking control of unmanned aerial vehicles (UAVs) formation with denial of service attacks. A novel prescribed time synchronous tracking control scheme is proposed within a denial of service attack conversion mechanism. Firstly, on account of the UAV formation in the presence of aerodynamic damping and denial of service attacks, a formation cooperative control model is established under a second-order system. Secondly, to perform formation synchronous tracking within a settling time, a time-varying auxiliary function on account of synchronous state errors is designed for the convergence of prescribed time tracking. The control parameters are designed using a key eigenvalue scaling technique under the effect of denial of service attacks on network topology. The proposed scheme is also extended to UAV formation with a detailed-balanced graph. Finally, simulation results are presented to demonstrate the effectiveness of the proposed strategy.

Robust practical prescribed time trajectory tracking of USV with guaranteed performance

In this paper, a practical prescribed time tracking control scheme is proposed to drive the unmanned surface vehicle (USV) under input saturation and unknown disturbances to track the desired trajectory with guaranteed transient and steady-state performances. First, by employing the logarithmic type barrier Lyapunov function and prescribed time function, the virtual velocity law is designed at the kinematic level. Then, to deal with the unknown disturbances, a prescribed time observer is constructed to achieve perturbation attenuation in a user-defined time. Together with the linear anti-windup compensator, a robust trajectory tracking controller is constructed, which is capable of guaranteeing that all signals in the closed-loop system are uniformly ultimately bounded (UUB) and the tracking error converges to a user-defined compact set in predetermined time with prescribed transient performance. Finally, the effectiveness of the proposed control scheme is validated through Lyapunov theory and numerical studies.

A fast dynamic pose estimation method for vision-based trajectory tracking control of industrial robots

Vision-based robotic trajectory tracking control is considered a promising technology. However, the slow sampling rate and latency of the vision sensor enormously limit the tracking performance. To conquer the issues, this paper proposes a dual-space error-state Kalman filter (DS-ESKF). By combining the encoder measurement with the vision measurement, the end-effector’s pose between adjacent vision measurements is restored, and the pose estimation cycle is synchronized with the control cycle. The critical distinguishing of DS-ESKF is that the encoder-driven error-state kinematics for the industrial robot is reconstructed. The experimental results on the Staubli TX60 industrial robot show that compared with the existing dual-rate Kalman filters (DR-KF), DS-ESKF can reduce estimation errors by about 50 % and have robust estimation performance. By applying the trajectory tracking control scheme combining DS-ESKF with a simple PID controller to Staubli TX60, the tracking accuracy is significantly improved (±0.11 mm for position and ± 0.05°for orientation).

Event-triggered trajectory tracking control for USV with prescribed performance and time delay based on differential flatness

This paper presents a trajectory tracking control scheme for underactuated surface vessels (USVs) with input delay. Firstly, the underactuated surface vessel system is transformed into a fully actuated system using differential flatness theory. To estimate the unknown nonlinear terms introduced in the transformation process, a fuzzy neural network (FNN) is employed. Secondly, to conserve control resources and communication bandwidth, the controller of the system under prescribed performance is designed using the backstepping method. This method updates the controller according to an event-triggered condition that is designed using a Lyapunov function. Finally, theoretical proof and simulation experiments are conducted to demonstrate the convergence and effectiveness of the proposed method.

Coordinated transportation of tethered multi-rotor UAVs based on differential graphical games

This paper investigates the stability control of the tethered multi-rotor unmanned aerial vehicles (T-MRUAVs) system in cargo delivery, where precise payload trajectory control is deemed unnecessary, with a focus on enhancing controller simplicity and robustness. To achieve this objective, it is imperative to employ an optimal formation tracking control, ensuring not only the symmetrical positioning of UAVs concerning the payload but also the achievement of distributed optimal solutions. Therefore, a formation tracking control strategy based on differential graphical games is designed to ensure optimized performance metrics and minimized suspended load swing. The designed control framework includes an outer loop and an inner loop control, which respectively achieve formation tracking and attitude stability. In addition to maintaining equilibrium states, each UAV is required to track the desired trajectory. Consequently, the formation tracking control consists of a gravity compensation term at the equilibrium point and a formation tracking control term based on differential graphical games. Then, a PID control strategy is displayed for the inner loop control, and the altitude control adopts feedback linearization. Finally, numerical simulations have validated the effectiveness of the designed algorithm.

Adaptive tracking control for constrained nonlinear nonstrict-feedback switched stochastic systems with unknown control directions

This brief proposes a novel tracking control strategy to cope with the asymmetric state constraints for nonstrict-feedback and nonlinear switched stochastic systems with unknown control directions. Firstly, without requiring piecewise Barrier Lyapunov functions (BLFs), the asymmetric constraint restrictions are unfastened well in the recursive idea according to a series of new-style coordinate transformations. Then, a novel error compensation mechanism based on the state constraint conditions is incorporated into the tracking differentiator (TD) technology to tackle the “differential explosion” problem in the backstepping design, and a low-cost adaptive control strategy under single adaptive law is built to simplify the computation, meanwhile, the control objective is achieved. Followed by the rigorous theoretical proof, the applicability is presented by a practical example.

Cooperative control strategy of trajectory tracking and driving stability for distributed-drive vehicles under extreme conditions

Active chassis dynamics control has become increasingly important in recent years for achieving high-level automated driving of intelligent electric vehicles. To improve tracking performance of the commonly-used model predictive control (MPC) in extreme scenarios, such as emergency lane changing, an improved MPC motion stability controller (MPC_ISMC) based on sliding mode variable structure active steering control and differential torque yaw control is proposed. Firstly, an MPC-based trajectory tracking controller is designed to track the desired trajectory. Subsequently, active front-wheel steering (AFS) and direct yaw moment (DYC) controllers are designed by using the backstepping sliding mode variable structure and the adaptive super-twisting sliding mode variable structure, respectively. Moreover, a cooperative control law for the AFS and the DYC is formulated by the smooth switching function and intervention intensity factor with respect to vehicle stable state and trajectory tracking error. After that, a torque distribution scheme of four wheels is optimized to achieve the additional yaw moment target. Finally, the effectiveness of the proposed cooperative control strategy is validated using a hardware-in-the-loop platform. The results indicate that the proposed controller has better performance in trajectory tracking and vehicle stability under extreme conditions compared with traditional MPC and other methods.

Event-based adaptive secure asymptotic tracking control for nonlinear cyber–physical systems against unknown deception attacks

This article addresses the event-triggered adaptive neural network asymptotic tracking control problem for a class of nonlinear cyber–physical systems under unknown deception attacks. In the process of recursive design, a novel adaptive asymptotic tracking control strategy is proposed based on bound estimation method, backstepping technique and some smooth functions. The designed asymptotic tracking controller can ensure that the output of the system asymptotically tracks the desired signal, while ensuring that all signals in the closed-loop system are bounded. Particularly, the underlying system can be guaranteed to possess faster convergence response and higher control precision. Additionally, the Zeno behavior is ruled out. Finally, a two-stage chemical reactor is employed as an example to demonstrate the feasibility and viability of the designed control algorithm.

A novel cascaded trajectory tracking control for UUVs under time-varying disturbances

In this paper, a novel cascaded trajectory tracking control strategy based on the characteristics of kinematics and dynamics is proposed for unmanned underwater vehicles (UUVs) under complex disturbances. A kinematic controller based on an improved model predictive control (MPC) is designed to solve the speed jump problem by considering system constraints. Moreover, an improved whale optimizer with elite strategy (EIWOA) is used to the rolling optimization process of MPC, ensuring that the global best solution is derived by obtaining the elite individuals in the population. Besides, a dynamic controller that consists of an adaptive disturbance observer and a fuzzy integral sliding mode control (ADO-FISMC) is proposed to obtain optimal thrust force under time-varying disturbances. The benefit of ADO lies in that it can estimate time-varying disturbances without specific information about disturbances. The fuzzy logic system is introduced to alleviate the chattering of sliding mode control. The simulation results demonstrate the great tracking performance of the cascaded trajectory tracking controller. The viability of the proposed algorithm is also confirmed by trials conducted in water pools.

Variable Power Tracking Control Strategy of Doubly Fed Induction Generators for Fast Frequency Responses

Frequency regulation and droop control of doubly fed induction generators (DFIGs) can quickly respond to frequency changes and reduce the maximum rate of frequency (MROFF) in power systems. However, due to real-time dynamic changes in the MPPT control loop, the ability to improve the lowest frequency point is limited. Therefore, this article first describes an in-depth analysis of the dynamic characteristics of the incremental power of frequency regulation with droop control using an equivalent linear model. The limitations of improving the lowest frequency point under the influence of dynamic changes in the MPPT control loop are revealed. Secondly, to address the impact of these dynamics, an improved decoupling frequency regulation (IDFR) strategy based on power tracking is proposed, aiming to increase the maximum frequency deviation (MFD) and MROCOF. Then, in order to overcome the difficulty of adjusting control coefficients in the IDFR strategy, an adaptive control coefficient tuning fuzzy control method based on frequency deviation and ROCOF was proposed to flexibly adjust control requirements under various working conditions, thereby improving the control stability and performance of the system and effectively solving the problem of control coefficient allocation. Finally, to verify the frequency regulation performance of the proposed IDFR strategy under various operating conditions, simulations were conducted based on different disturbances and wind conditions. The results show that the proposed IDFR strategy significantly improves the system MFD and MROCOF improvement ability under various conditions.

Double-loop LQR depth tracking control of underactuated AUV: Methodology and comparative experiments

In this paper, a double-loop depth tracking control scheme based on linear quadratic regulator (LQR) is proposed for underactuated autonomous underwater vehicles (AUV). The motivation is to address the problem that the classic single-loop LQR depth controller which is easy to use in practice yet cannot effectively overcome the underactuated AUV features and complex disturbances. First, a double-loop depth control framework is proposed which divides complex disturbances into outer-loop kinematic disturbances and inner-loop dynamic disturbances. Second, the adaptive line-of-sight (ALOS) guidance law is designed in the outer loop to account for the underactuated characteristics. The depth tracking error is converted to the desired pitch and the kinematic disturbance caused by the unknown angle of attack is compensated. Furthermore, based on the linear model in the inner-loop, a concise LQR method is designed to track the desired pitch. Meanwhile, an extended state observer (ESO) is introduced to estimate dynamic disturbances such as model nonlinearity, uncertainty and external environmental disturbances. Finally, the proposed scheme is validated by tank test and compared with the single-loop LQR method. The experiment results show that the proposed double-loop depth tracking method can effectively overcome complex disturbances and the depth tracking accuracy is increased by 83%.

Fixed‐time sliding mode trajectory tracking control for marine surface vessels under mismatched conditions and input saturation

SummaryThis paper addresses a trajectory tracking control problem for marine surface vessels (MSVs) in the presence of mismatched conditions and input saturation. Firstly, an MSV model under mismatched conditions is established to solve the problem of unreasonable modeling methods in the existing literature. Secondly, fixed‐time disturbance observers (FXDOs) are designed, where the designed FXDOs not only avoid selecting complicated parameters but also has simple structures, and the disturbance estimation errors can converge to the origin within a setting time. Thirdly, based on the FXDOs and an anti–saturation auxiliary dynamic system, a trajectory tracking control scheme in the presence of mismatched conditions and input saturation is constructed by virtue of fixed‐time integral sliding mode control (SMC), and the actual tracking error signals are uniformly fixed‐time bounded rather than finite‐time one. Fourthly, in order to decrease theoretical calculation values of the original setting time in fixed‐time control, the new setting time under three different parameter conditions is derived, and thus reducing the conservatism. Finally, the simulation results are provided to show the effectiveness and superiority of the designed tracking control scheme.

Negative-imaginary-based spacecraft attitude tracking control using modified Rodrigues parameters

This paper investigates a counter-clock-wise input-output map about spacecraft attitude dynamics and kinematics using Modified Rodrigues Parameters. A gyro-free attitude control scheme is established by constructing a negative imaginary system for spacecraft attitude stabilization. Attitude tracking control scheme is also explored where the negative-imaginary-based controller has no need on the angular velocity measurements. Numerical simulations are presented to show the effectiveness of the proposed attitude control scheme.

A new neural adaptive finite-time constraint tracking control strategy for stochastic nonlinear systems with quantized input and unknown initial condition

A new neural adaptive finite-time constraint tracking control strategy for stochastic nonlinear systems with quantized input and unknown initial condition

Adaptive output-feedback event-triggered formation control for underactuated ships with obstacle avoidance mechanism

This paper focuses on the adaptive output-feedback event-triggered control strategy for the formation tracking and obstacle avoidance activity of unmanned surface vessels (USVs) with unmeasurable velocity, constrained communication and actuator fault. By using the neural networks and minimal learning parameter, a novel output-feedback event-triggered controller is deigned, effectively alleviates constraints related to continuous feedback signal acquisition in dynamic systems. Subsequently, by incorporating an adjustable threshold, the event-triggered condition is established, thus facilitating updates to the state and adaptive law solely within the discrete-time domain. Then, only two aperiodic adaptive laws are derived to mitigate actuator faults and system uncertainties. As for the path planning, benefiting from the artificial potential field method, a novel obstacle avoidance mechanism is developed for obstacle avoidance and waypoint-based path navigation. Considerable effort has been made to guarantee the semi-globally uniformly ultimately bounded stability. Finally, two numerical simulations are illustrated to demonstrate the remarkable performance of the proposed control strategy.

A distributed containment tracking control of the UAV formation with prescribed performance subject to collision avoidance

SummaryIn this paper, the issue of finite‐time containment tracking control under collision avoidance constraints for unmanned aerial vehicle (UAV) formation is investigated. To tackle the challenge of collision avoidance in the context of formation containment tracking, combined with a prescribed performance function, a distributed containment tracking control scheme is proposed. Firstly, a UAV formation containment control model from a top view perspective is established. Next, to solve the internal collision avoidance within the formation, a restricted movement region is constructed for each UAV using a distributed prescribed performance function, which guarantees that each UAV's trajectory is maintained within a predefined area. Furthermore, invoking with the finite‐time control theory for the formation, a distributed containment tracking control scheme is developed to complete finite‐time tracking of the formation. Finally, simulation results are carried out to demonstrate the efficacy of the proposed approach.

Adaptive multi-dimensional Taylor network tracking control of time-varying delay nonlinear systems subject to input saturation

For the tracking control problem of a class of nonlinear systems with input saturation constraint and time-varying delay, an adaptive tracking control scheme based on multi-dimensional Taylor network (MTN) is designed, and the proposed control scheme has the advantages of simple structure and small computation. A Gaussian error function is introduced to transform the input saturation into a linear model with bounded error. The Lyapunov-Krasovskii function is constructed, and the nonlinearity of the system is approximated using MTN, and an adaptive control strategy is constructed based on the backstepping method. The results show that the proposed control method can both ensure that all signals in the closed-loop system are bounded and achieve convergence of the tracking error to a small neighborhood near the origin. Numerical simulations verify the effectiveness of the method.

Event-triggered adaptive secure tracking control for nonlinear cyber–physical systems against unknown deception attacks

This article presents an event-triggered adaptive neural networks secure tracking control method for a class of nonlinear cyber–physical systems under unknown sensor and actuator deception attacks. To obtain the desired system performance, dynamic surface technique is applied to design controller and radial basis function neural networks are introduced to deal with unknown nonlinear and actuator attacks. By skillfully combining compensation signals with the attack compensators, the unknown deception attacks are effectively mitigated. To reduce the transmission communication load, a novel event-driven control scheme is developed by applying relative threshold triggered mechanism. On this basis, all the signals of closed-loop system are bounded under deception attacks by using Lyapunov stability analysis. Additionally, the presented secure tracking control strategy can ensure the tracking error converges to a small neighborhood of origin and the Zeno behavior is ruled out. Finally, a practical example is employed to verify the feasibility and effectiveness of the designed control algorithm.

Asymptotical tracking control for the complex network based on the dynamic topology

A tracking control scheme is proposed for complex dynamic network (CDN), where the CDN is regarded wholly as a dynamic composite system which consists of two mutually coupled subsystems. One subsystem consists of all nodes and the other consists of all links, and consider the weights of the links to be state variables in the latter subsystem. There are two parts in the structure of the proposed tracking control scheme: the designed controller of nodes and the synthesis of the coupling term in links. These two parts can guarantee two subsystems to asymptotically track the given reference targets, respectively. This approach originates from the communication transmission network (CTN). In CTN, for the network optimization management, the reference network topology (NT), such as the star topology, is required as a target for tracking in communication transmission (links) when each node in network needs to track its own target. The control scheme provided of this paper coincides with above requirement. And finally, a comparative simulation example is given for illustrating the effectiveness of the provided control scheme.