Distributed robust tracking control for multiple unmanned aerial vehicles: theory and experimental verification

Distributed tracking control of unmanned aerial vehicles under wind disturbance and model uncertainty

The robotic airship is a unique and promising light-than-air platform, which has attracted worldwide developing interests for its broad applications. This article addresses the control problem of trajectory tracking for robotic airships. A neural network fuzzy sliding mode controller is proposed to steer a robotic airship along a referenced trajectory precisely. First, the dynamics model of a robotic airship is presented, and the problem of trajectory tracking is formulated. Second, a sliding mode controller is designed to track a time-varying trajectory. The neural network is employed to approximate the uncertain model of the airship, with the tracking error and its derivatives and the trajectory and its derivatives as neural network inputs and the approximation of the uncertain model as neural network output. And a fuzzy logic system is adopted to reduce the chattering results from the sliding mode controller. The control gains are tuned synchronously with the sliding surface according to fuzzy rules, with switching sliding surface as fuzzy logic inputs and control gains as fuzzy logic outputs. The stability and convergence of the closed-loop controller are proven using the Lyapunov stability theorem. Finally, the effectiveness and robustness of the proposed controller are demonstrated via simulation results. Contrasting simulation results indicate that the neural network fuzzy sliding mode controller reduces the chattering effectively and has better performance against the sliding mode controller.

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.

A spherical robot is a nonlinear, nonholonomic, and unstable system which increases the difficulty of the direction and trajectory tracking problem. In this study, we propose a new direction controller Hierarchical Terminal Sliding Mode Controller (HTSMC), an instruction planning controller called Model Prediction Control-based Planner (MPCBP), and a trajectory tracking framework named MPCBP-HTSMC-HSMC (MHH). The HTSMC is designed by integrating a fast terminal algorithm, a hierarchical method, the motion features of a spherical robot, and its dynamics. In addition, the new direction controller has an excellent control effect with a quick response speed and strong stability. MPCBP can obtain optimal commands that are then transmitted to the velocity and direction controller. Since the two torque controllers in MHH are all Lyapunov-based sliding mode controllers, the MHH framework may achieve optimal control performance while assuring stability. Finally, the two controllers eliminate the requirement for MPCBP's stability and dynamic constraints. Finally, hardware experiments demonstrate the efficacy of the HTSMC, MPCBP, and MHH.

Robust adaptive three-dimensional trajectory tracking control for unmanned underwater vehicles with disturbances and uncertain dynamics

This paper mainly introduces the output voltage control of the three‐phase inverter without current sensor. Aiming at internal parameter perturbation and external unknown disturbance, a generalized proportional integral observer (GPIO) is designed to observe the lumped interference and feedforward compensation. Then, a finite‐time control strategy based on nonsingular terminal sliding mode control (NTSMC) is designed to improve control accuracy and fault tolerance under various interference. Compared with traditional PI control and sliding mode control (SMC), this strategy has the finite‐time convergence of voltage tracking error and active anti‐interference ability. The stability of the proposed control strategy is proved strictly. Finally, the simulation results show that in the presence of interference, the proposed control strategy has better robustness and smaller chattering. The feasibility and effectiveness of the controller are fully illustrated by exploring the experimental results. This controller eliminates the current sensor and has active anti‐interference capability. The output voltage chattering and overshoot under interference conditions are both significantly attenuated.

This brief is devoted to the predesigned motion trajectory-based finite time dynamic positioning (DP) control for a marine surface vehicle (MSV) with unknown external disturbances. Firstly, a preset motion trajectory is presented through establishing the relationship function among position tracking errors and heading tracking error, facilitating the MSV to arrive in the equilibrium point along the pre-designed trajectory. Furthermore, a novel nonsingular and fast terminal sliding mode control (NTSMC) approach is investigated, which ensures faster convergence rate and better stability performance of the close-loop system than the conventional backstepping control approach. What’s more, by incorporating the adaptive technique with the NTSMC approach, an adaptive nonsingular and fast terminal sliding mode control (ANTSMC) strategy is addressed. Compared to the NTSMC approach, it strengthens robustness to disturbances and guarantees system states to converge to a closer neighborhood of the equilibrium point. Finally, simulation results illustrate the remarkable effectiveness of proposed control schemes.

The robotic airship can be used as an aerostatic platform for many potential applications, for example, communication, hovering payload deliveries, data-gathering for research studies, etc. These applications require a fully autonomous perspective of an airship. One of the important aspects of airship autonomy is trajectory tracking control. An airship has complex and uncertain nonlinear dynamics which pose a major challenge for designing a precise trajectory tracking control. This paper addresses the airship trajectory tracking control problem under model uncertainties and wind disturbance. We propose a lumped model uncertainties and wind disturbance estimation approach based on an unscented Kalman filter. The estimated lumped uncertainty is used by the Sliding Mode Controller (SMC) for ultimate control of airship trajectory tracking. This comprehensive algorithm, Unscented Kalman filter-based Sliding Mode Controller (USMC), is used as a robust adaptive control solution to track the desired trajectory. The stability and convergence of the proposed method are investigated using the Lyapunov stability analysis. Simulation results show that the proposed method efficiently tracks the desired trajectory. The method solves the stability, convergence, and chattering problem of SMC without the bound constraint of model uncertainties and wind disturbance.

Adaptive model-parameter-free nonsingular fixed-time sliding mode control for underwater cleaning vehicle

This paper presents the design and implementation of a novel sliding mode control integrated with active disturbance rejection (SMCDR) for precise robust trajectory tracking of piezoelectric nanopositioning stages. The model uncertainties, nonlinearity, and external disturbances of the piezoelectric nanopositioning stage are regarded as a lumped disturbance, which is estimated by an extended state observer. The active disturbance rejection control (ADRC) strategy is used to realize a preliminary trajectory tracking, while the sliding mode control is adopted to handle the estimation error and residual uncertainties, and to improve the tracking performance. The exponential stability of the proposed SMCDR is proved using Lyapunov’s direct method. The proposed SMCDR controller combines the strength of both ADRC and sliding mode control, exhibits a simple structure, requires only the position measurements, and does not require any information of model parameters except for an approximate constant gain. Experimental results reveal the robustness of the SMCDR approach in suppressing the hysteresis of piezoelectric actuator, and illustrate the superior performance over conventional ADRC, integral sliding mode controller (ISMC) and PID controller for trajectory tracking control of piezoelectric nanopositioning stages.

<p>This paper presents a 3D guidance scheme for<br>\nUnmanned Aerial Vehicles (UAVs). The proposed guidance scheme<br>\nis based on the sliding mode approach using nonlinear sliding<br>\nmanifolds. Generalized 3D kinematic equations are considered<br>\nhere during the design process to cater for the coupling between<br>\nlongitudinal and lateral motions. Sliding mode based guidance<br>\nscheme is then derived for the multiple-input multiple-output<br>\n(MIMO) system using the proposed nonlinear manifolds. Instead of<br>\ntraditional sliding surfaces, nonlinear sliding surfaces are proposed<br>\nhere for performance and stability in all flight conditions. In the<br>\nreaching phase control inputs, the bang-bang terms with signum<br>\nfunctions are accompanied with proportional terms in order to reduce<br>\nthe chattering amplitudes. The Proposed 3D guidance scheme is<br>\nimplemented on a 6-degrees-of-freedom (6-dof) simulation of a UAV<br>\nand simulation results are presented here for different 3D trajectories<br>\nwith and without disturbances.</p>

For the problem of position and force trajectory tracking of flexible joint manipulators whose motion is constrained in the end, a finite-time position/force control strategy is proposed using adaptive terminal sliding mode. Firstly, position control and force control are decoupled according to the coordinate transformation and a reduced dynamic model for the manipulator is obtained. Then a new terminal sliding mode is established and an adaptive position/force control law is designed to overcome the uncertainties of the dynamic model. The system variables can be driven to reach the terminal sliding mode and slide to equilibrium point along the mode in finite time. Unlike previous position/force control strategies, this strategy can make both position and force tracking errors of the manipulator converge to zero in finite time. Simulation results are presented to validate the proposed method.

This paper concerns the finite-time trajectory tracking control problem for an underactuated marine surface vessel (MSV) suffering from the external disturbance and parameter uncertainties. First, the virtual velocity command is proposed based on a novel piecewise function. It will be illustrated that the position tracking error can be stabilized to small regions in finite time once the desired velocity commands are tracked. Then, an adaptive tracking controller is developed such that sway and yaw velocities can converge to the desired ones in finite time. Utilizing the proposed control strategy, global finite-time stability can be ensured for the position and velocity tracking errors even in the presence of external disturbances and parameter uncertainties. Finally, the effectiveness of the proposed controller is illustrated by numerical simulation.

The key attributes of Two Wheeled Balancing Mobile Robots (TWBMRs) are nonholonomic constraints and inherent instability. This paper deals with the problem of balancing and trajectory tracking of TWBMR using backstepping Sliding Mode Controller (SMC). First, the mathematical representation of TWBMR is derived using Lagrangian method by incorporating the dynamics of DC motors. Then, a decoupling approach is applied for simplifying the dynamic equations. The backstepping SMC technique is finally adopted to achieve the balancing and trajectory tracking of the TWBMR, whereas both model uncertainties and exogenous disturbance are taken into account in the controller design methodology. In order to determine the velocity, the trajectory tracking is achieved by the kinematic control, which is a common backstepping controller. For the velocity convergence of TWBMR to the generated desired value, two SMCs are designed, in which the motors voltage are directly controlled as the control laws. Simplicity in practical implementation and control law, ability to overcome uncertainties and appropriate performance are the main advantages of the proposed controller. The effectiveness of the proposed controller is verified through simulation and experimental results.

In this paper, a robust tracking control problem for underactuated underwater vehicles in horizontal motion is investigated. The presented control scheme that performs the trajectory tracking task is a combination of the backstepping technique and the integral sliding mode control method using the inertial quasi velocities (IQVs) resulting from the inertia matrix decomposition. Unlike many known solutions, the proposed approach allows not only trajectory tracking, but also, due to the fact that IQV includes dynamic and geometric model parameters, allows us to obtain additional information about changes in vehicle behavior during movement. In this way, some insight into its dynamics is obtained. Moreover, the control strategy takes into account model inaccuracies and external disturbances, which makes it more useful from a technical point of view. Another advantage of this work is to indicate problems occurring during the implementation of trajectory tracking in algorithms with a dynamics model containing a diagonal inertia matrix, i.e., without inertial couplings. The theoretical results are illustrated by simulation tests conducted on two models of underwater vehicles with three degrees of freedom (DOF).