Tracking Control Scheme Research Articles

Multi‐event‐triggered adaptive dynamic programming for non‐zero‐sum game of unknown nonlinear system

AbstractIn this article, a multi‐event‐triggered (MET) near‐optimal tracking control algorithm is developed for a discrete‐time (DT) nonlinear non‐zero‐sum game (NZSG). Firstly, the iterative dual heuristic dynamic programming (DHP) approach is utilized to obtain the optimal tracking control set. Subsequently, distinct independent triggering conditions are formulated for control inputs to improve the utilization efficiency of resources and ensure that the independence between them and the closed‐loop system has an excellent control performance. Meanwhile, input‐to‐state stability (ISS) is proven for the MET tracking plant. Additionally, neural networks (NNs) are designed in the iterative DHP algorithm to construct the model module, the critic module and the action modules, with aims to identify the unknown system, approximate costate function and estimate optimal tracking control strategy set, respectively. Finally, two numerical experimental simulations are conducted to verify the effectiveness of the proposed scheme.

Safe tracking control based on a secure boundary protection method for nonlinear systems with unknown initial tracking condition

Aiming to the sudden change of the system actual output constraint, a novel safe tracking control strategy is investigated for a class of non-strict feedback nonlinear systems with unknown initial tracking condition in this paper. A secure boundary protection method (SBPM) based on prescribed performance and a new prescribed finite-time performance function (PFTPF) are proposed. The SBPM can automatically construct two adjustable secure boundaries, so that the system output meets both the control performance prescribed by the PFTPF and the secure boundary constraint. In order to solve the problem of the excessive control input jitter caused by the sudden change of output constraint, a bidirectional filtering smoothing mechanism (BFSM) is proposed. The proposed SBPM can effectively ensure the safe tracking control of the system with unknown initial tracking condition when the actual output constraint changes suddenly, and ensure that the system has the prescribed finite-time control performance given by the PFTPF. Differently from the existing works, the system output will be strictly constrained into the actual output constraint without the prediction for the system output value. Finally, the effectiveness of this proposed method is verified by simulations.

Distributed Fixed-Time Formation Tracking Control for the Multi-Agent System and an Application in Wheeled Mobile Robots

This work addresses the issue of multi-agent system (MAS) formation control under external disturbances and a directed communication topology. Firstly, a new disturbance observer is proposed to effectively reconstruct and compensate for external disturbances within a short period of time. Then, the integral terminal sliding mode technology is introduced to devise a novel distributed formation control protocol, ultimately realizing the stability of the MAS within a fixed time. Moreover, by means of rigorous Lyapunov theory analyses, a faster formation convergence rate and more accurate consensus accuracies are achieved in the proposed fixed-time strategy with variable exponent form. Finally, the formation tracking control scheme is applied to a multi-wheeled mobile robot (WMR) system. The experimental results strongly support the fine effectiveness of the control scheme designed in this work.

Collision-Free Formation-Containment Tracking of Multi-USV Systems with Constrained Velocity and Driving Force

This paper studied the collision avoidance issue in the formation-containment tracking control of multi-USVs (unmanned surface vehicles) with constrained velocity and driving force. Specifically, based on a dual-layer control framework, it designed a multi-USV formation-containment tracking control strategy that accounts for constrained motion velocity and input driving force and validated the stability of this strategy using the Lyapunov method. Then, by utilizing zeroing control barrier function certificates, it considered collision avoidance among USVs with various roles as well as between each USV and static obstacles. A collision-free multi-USV formation-containment tracking control strategy considering constrained motion velocity and driving force was thus established, and its effectiveness was validated through the proposed simulation.

Backstepping-based adaptive fuzzy tracking control for pure-feedback nonlinear multi-agent systems

This work developed an adaptive fuzzy tracking control strategy for pure-feedback nonlinear multi-agent systems via backstepping. The relevant unknown functions are addressed by fuzzy logic systems (FLSs), which take into account entirely unknown nonlinearities. The non-affine pure-feedback form is dealt with a Butterworth low-pass filter (BLF), and the converted systems can be used to construct a controller. The implementation of the first-order sliding-mode differentiator overcomes the difficulty of calculation explosion. The backstepping method is applied to design the virtual controller step by step, and the actual controller is designed successfully. Furthermore, through Lyapunov stability theory, the stability of systems is ensured, and that the tracking error is kept to a minimum. Finally, the simulation result shows the validity of the designed control strategy.

A Polytopic Model-Based Robust Predictive Control Scheme for Path Tracking of Autonomous Vehicles

A Polytopic Model-Based Robust Predictive Control Scheme for Path Tracking of Autonomous Vehicles

Global Prescribed Performance Control for Strict Feedback Systems Pursuing Uncertain Target.

In this work, an online solution for reconstructing and predicting the uncertain target trajectory in real-time is proposed based on general regression neural network (GRNN). On this basis, an adaptive tracking control scheme guaranteeing prescribed performance is suggested for a class of strict-feedback systems with unknown control directions. In contrast to existing trajectory reconstruction methods, the one presented in this note does not require prior modeling of the uncertain target or offline training. Contrary to most current state-of-the-art prescribed performance control (PPC) technology, a novel time-varying scaling function and its corresponding translation function are introduced such that no strict constraints on initial conditions are needed, that is, global stability is achieved. The proposed control scheme allows the output of the system to chase the predicted value of the uncertain target, and the tracking error converges to a prescribed small set within a preassigned time, despite unmatched uncertainties and unknown control directions. The benefits of the proposed control scheme are confirmed by numerical simulations.

Nussbaum-Based Adaptive Fault-Tolerant Control for Nonlinear CPSs With Deception Attacks: A New Coordinate Transformation Technology.

In this article, two novel adaptive fault-tolerant control schemes for a class of nonlinear strict-feedback cyber-physical systems (CPSs) with deception attacks are presented. Deception attacks, such as false data-injection attacks, which destroy sensor networks, make the outputs and states of the CPSs unavailable. It is very difficult and challenging for a designer to achieve the tracking control under the circumstance of cyberattacks. To realize the tracking control for the studied CPSs, we propose a new coordinate transformation technology without precedent, where it takes the attack gains into account and uses the compromised states to design the corresponding controllers. In the backstepping design process, Nussbaum functions are presented to alleviate the influence of the unknown attack gains. Furthermore, we consider the actuator faults problem, which includes the loss of effectiveness and the bias fault. By skillfully designing the adaptive laws, the effect of actuator faults is completely eliminated. It is theoretically proved that the first proposed tracking control scheme can guarantee all signals in the closed-loop system are bounded and the output can track the desired reference signal. In addition, the second adaptive control scheme is also developed for the CPSs under the actuator faults and a more general assumption on the deception attacks is proposed simultaneously. Finally, the feasibility of the new proposed methods is verified by MATLAB simulation analysis.

Fast Finite-Time Super-Twisting Sliding Mode Control with an Extended State Higher-Order Sliding Mode Observer for UUV Trajectory Tracking

This paper proposes a trajectory tracking control scheme consisting of a fast finite-time super-twisting sliding mode control (FSTSMC) approach and an extended state higher-order sliding mode observer (ESHSMO) for unmanned underwater vehicles (UUVs) with external disturbances and model uncertainties. Firstly, an extended state higher-order sliding mode observer with the finite-time convergence is designed based on the higher-order sliding mode technique and the extended state observer technique. Next, on the basis of disturbances and model uncertainties observation, a fast finite-time super-twisting sliding mode control approach is proposed, and the finite time stabilization property of the tracking errors is proved by Lyapunov theory. Finally, through numerical simulation and experiment in a water pool, it has been verified that the proposed control scheme has achieved the high control precision, the smaller chattering, the disturbance compensation and the fast finite-time convergence in UUV trajectory tracking.

Fault‐tolerant adaptive tracking control for spacecraft attitude with asymptotic convergence

AbstractIn this paper, we present a novel spacecraft attitude adaptive tracking control strategy that addresses the challenges posed by unknown inertia parameters, bounded unstructured uncertainties, and various actuator faults. To mitigate the adverse effects of these multiple uncertainties, our proposed control algorithm utilizes a simple tracking‐error feedback and compensation term, which only requires two adaptive parameters. This approach ensures asymptotic tracking convergence by employing an infinitely integrable inequality that incorporates saturation functions. As a result, the complexity of controller design and computational burden are significantly reduced. Finally, several numerical simulations are conducted to validate the feasibility and superiority of our proposed controller.

An identical path tracking control strategy of the tractor-trailer wheeled mobile robot with an off-axle hitching based on a passive steering angle

For a tractor-trailer wheeled mobile robot (TTWMR, for short) with an off-axle hitching, it is challenging for both tractor and trailer to track a desired path due to the insufficient steering capability of the trailer. As such, a passive steering angle is first introduced, which allows the trailer to follow the same path as the leading tractor. In this way, a given motion task can be reduced to the accurate path tracing problem for the tractor. By considering such a passive steering angle, the motion speed relation between two vehicles of the TTWMR with an off-axle hitching is then derived, based on which its kinematics and dynamics equations are established. Thereafter, a proportion integration feedback controller is then developed by combining the curvature tracing method and the directed Lyapunov method, so that both vehicles can move along an identical path. Finally, simulation results indicate the effectiveness and robustness of the resulting control strategy.

Security-based distributed fuzzy funnel cooperative control for uncertain nonlinear multi-agent systems against DoS attacks

This article focuses on the distributed funnel cooperative control of nonlinear multi-agent systems suffering denial-of-service (DoS) attacks, which aim to disrupt communication links between agents and can lead to discontinuities in system outputs. First, an actual measurement model of output signals is given, and a fuzzy switching observer is designed by utilizing the practical output model to obtain the unknown states. Second, a funnel-based tracking control strategy is presented by skillfully blinding the funnel function and backstepping technique to defend against DoS attacks. A crucial stability criterion is established by combining an improved average dwell time (ADT) approach and Lyapunov stability theory that integrates the constraints imposed by DoS attacks. In particular, based on an appropriate error transformation, the developed control law has a simpler structure than existing barrier function methods to solve performance constraints. It guarantees that the output of each follower agent yi is able to track the reference signal yd, and synchronization errors ϵi=∑s=1Mai,s(yi−ys)+bi(yi−yd) are consistently confined within a prearranged performance funnel Fϕ, (that is, (t,ϵi(t))∈Fϕ,∀t). Ultimately, a simulation example is presented to prove the validity of the established solution.

Adaptive multi‐level differential coupling control strategy for dual‐motor servo synchronous system based on global backstepping super‐twisting control

AbstractA new dual‐motor servo steering system with improved reliability and safety is proposed. But, despite the advantages of the proposed servo system, it is strongly coupled, non‐linear and multivariable, where the biggest challenge lies in its tracking and synchronization control. To improve the tracking and synchronization control performance of the proposed servo system, a tracking and synchronization control strategy based on backstepping super‐twisting control and multi‐level differential coupling is presented. First, a parallel model of the dual‐motor is established. Then, backstepping and super‐twisting control algorithms are integrated while adaptively optimizing key parameters to ensure the robustness and tracking performance of each motor. After that, an angular synchronization controller with multi‐level differential coupling and backstepping super‐twisting algorithm is proposed to compensate for the synchronization error of the dual‐motor system caused by parameter uncertainty. Finally, the simulation is carried out using Simulink to verify the effectiveness of the proposed control strategy.

An adaptive trajectory tracking control scheme for a novel fully actuated multirotor unmanned aerial vehicle without using velocity signals

SummaryThis paper introduces a novel fully actuated multirotor unmanned aerial vehicle (UAV) and develops an adaptive control scheme for it without relying on velocity signals. Conventional multirotors are limited by their strong coupling between translation and rotation motion, which makes it difficult to operate one motion without affecting the other. However, this novel multirotor's fully actuated design allows for independent translation and rotation motion, leading to better operational performance and expanded application scope. Additionally, velocity measurement signals can be prone to noise pollution and signal drift, making them unreliable for control purposes. Therefore, this proposed control scheme is developed without using velocity signals. The study utilizes a control performance improving method and guarantees stability of the closed‐loop system using the direct Lyapunov method. Finally, numerical simulations are employed to demonstrate the effectiveness of the proposed control scheme.

Comprehensive reconstructions and predictive control for quadrotor UAV information gathering tracking missions based on fully actuated system approaches

This paper introduces a novel approach to the comprehensive reconstruction and predictive control (PC) of the quadrotor UAV for information-gathering missions, employing fully actuated system (FAS) approaches. Unlike conventional PC methods applied to a quadrotor UAV with hybrid constraints, our work integrates reconstructions of the system model, hybrid constraints, and the receding horizon performance index into to an integrated tracking control scheme within the FAS-PC framework. Specifically, the under-actuated quadrotor UAV model is reconstructed into a full-actuated model to inject full-actuation properties. And the implicit hybrid constraints that arise from the model reconstruction are explicitly transformed and decoupled. Simultaneously, the cascaded predictive algorithm is established that the new time-varying input constraints are solved in each predictive horizon, and then the nonlinear optimization problem is decoupled into four linear convex optimization problems subject to the corresponding decoupled linear constraints and the pre-addressed input constraints. Within this framework, the intrinsic complexities, nonlinearities, and interdependencies of the quadrotor UAV system model, along with hybrid constraints and the optimization dilemma, are considerably diminished. This reduction significantly eases computational demands, enabling satisfactory real-time performance. Furthermore, the selection of predictive parameters guarantees the stability of the resultant tracking error closed-loop system. Finally, the efficacy of the proposed method is validated through two sets of flight missions, conducted via simulation and practical experimentation, respectively.

Adaptive fuzzy anti-saturation tracking control for uncertain nonlinear systems with external disturbance

In this paper, a predictive-based adaptive anti-saturation tracking control scheme is designed for uncertain multiple-input and multiple-output (MIMO) nonlinear systems subject to input constraints and external disturbance. Taking the safety of the MIMO nonlinear systems into account, a safety saturation threshold, which is less than the physical device saturation threshold, is given. In addition, since all signals of the auxiliary systems are not immediately employed to the systems when the input saturation happens, a new predictive-based auxiliary system is designed. Furthermore, to estimate the compound disturbance, with the help of the fuzzy control technology, the nonlinear disturbance observer (NDO) is used. Then, the stability of the closed-loop systems is proved under the designed controller. Finally, a simulation example is given to illustrate the feasibility of the designed anti-saturation controller.

A connectivity-preserving performance guarantee for cooperative control method with improved switching event-triggered mechanism

An adaptive tracking control scheme is designed for multiagent systems. To ensure a certain communication range between agents, a connectivity-preserving performance guarantee mechanism is proposed, which increases the consideration of the connection information between agents and the leader to further improve the cooperativity. Meanwhile, different from traditional constraint error methods, a boundary-based prescribed performance control scheme is constructed, which has the characteristic of getting the variable preset boundary. Furthermore, the improved switching event-triggered mechanism is developed, and the threshold parameters can be adjusted in real-time to adaptively change the update frequency of the controller. All signals are bounded in the closed-loop system. Finally, some simulation results affirm the validity of the control scheme.

Maximum Power Point Tracking Control of Offshore Hydraulic Wind Turbine Based on Radial Basis Function Neural Network

A maximum power point tracking control strategy for an affine nonlinear constant displacement pump-variable hydraulic motor actuation system with parameter uncertainty, used within an offshore hydraulic wind turbine, is studied in this paper. First, we used the feedback linearization method to solve the affine nonlinear problem in the system. However, offshore hydraulic wind turbines have strong parameter uncertainty characteristics. This conflict was resolved through the further application of RBF neural network adaptive control theory. So, we combined feedback linearization with RBF adaptive control as the control theory, and then two control laws were compared by setting the pump rate and rating as outputs, respectively. It is shown by the MATLABR2016a/Simulink emulation results that power control is smoother than speed and friendlier for electric networks. It is also shown by the emulation results, in terms of the undulatory wind speed condition, that the feedback linearization–RBF neural network adaptive control strategy has perfect robustness. According to the simulation results, the feedback linearization–RBF neural network adaptive control strategy adopts the RBF neural network to approach complex nonlinear models and solve the parameter uncertainty problem. This control law also avoids the use of feedback linearization control alone, which can result in the system becoming out of control.

Autonomous Obstacle Avoidance and Trajectory Planning for Mobile Robot Based on Dual-Loop Trajectory Tracking Control and Improved Artificial Potential Field Method

In order to better meet the practical application needs of mobile robots, this study innovatively designs an autonomous obstacle avoidance and trajectory planning control strategy with low computational complexity, high cost-effectiveness, and the ability to quickly plan a collision-free smooth trajectory curve. This article constructs the kinematic model of the mobile robot, designs a dual-loop trajectory tracking control strategy for position control law and attitude control law algorithms, and improves the traditional artificial potential field method to achieve a good obstacle avoidance strategy for mobile robots. Based on the dual-loop trajectory tracking control and the improved artificial potential field method, the autonomous obstacle avoidance and trajectory planning scheme of the mobile robot is designed, and closed-loop stability verification and analysis are conducted on the overall control system. And through the detailed simulation and experiments, the advantages of the proposed method in trajectory tracking accuracy and motion stability compared to the existing methods are verified, showing good effectiveness and feasibility and laying a good foundation for the application of mobile robots in practical complex scenes.

Research on trajectory tracking control of ocean unmanned aerial vehicles based on disturbance observer and nonlinear sliding mode

This paper aims to solve the problem of real time tracking of unmanned aerial vehicle (UAV) with external disturbances, model uncertainty, and multiple control parameter tuning during wave glider (WG) navigation. Firstly, the dynamic model of UAV and WG is instituted; Secondly, an Expanded State Observer (ADOB) is proposed to estimate the total perturbations in real time, including model uncertainties and external wind perturbations; Moreover, the ADOB is integrated with a nonlinear integral sliding mode control to generate a nonlinear sliding mode controller (ASMC) with a compound disturbance observer for the trajectory tracking control strategy; Finally, the bandwidth parameterization theory is used to tune the parameters of the ASMC controller. Simulation and experimental results show that the UAV trajectory tracking landing control scheme proposed in this paper can effectively solve the real-time tracking problem of the UAV during WG navigation.