Robust guaranteed cost tracking control of quadrotor UAV with uncertainties

Modeling and sliding mode-based attitude tracking control of a quadrotor UAV with time-varying mass

In the practical applications, the mass of a quadrotor unmanned aerial vehicle (UAV) would be time-varying. This time-varying mass will deteriorate the control performance of UAV. To solve this challenge, the mathematical modeling problem of a quadrotor UAV with time-varying mass is first investigated in this paper. The nonlinear dynamics describing the six-degrees-of-freedom full motion is established. Based on the established model, taking attitude tracking control problem into consideration, a robust control scheme is then designed via the sliding mode control theory. Applying the developed proposed approach, the desired trajectory is followed with the attitude tracking error asymptotically stabilized. The proposed controller has the capability of rejecting the external disturbance and the uncertainties induced by the time-varying mass. The feasibility of the established model and the effectiveness of the presented control approach are validated through a simulation study.

Neuro-adaptive fast integral terminal sliding mode control design with variable gain robust exact differentiator for under-actuated quadcopter UAV

In this paper, a robust global fast terminal attractor based full flight trajectory tracking control law has been developed for the available regular form which is operated under matched uncertainties. Based on the hierarchical control principle, the aforesaid model is first subdivided into two subsystems, i.e., a fully-actuated subsystem and an under-actuated subsystem. In other words, the under-actuated subsystem is further transformed into a regular form whereby the under-actuated characteristics are decoupled in terms of control inputs. In the proposed design, the nonlinear drift terms, which certainly varies in full flight, are estimated via functional link neural networks to improve the performance of the controller in full flight. Besides, a variable gain robust exact differentiator (VG-RED) is designed to provide us with estimated flight velocities. It has consequently reduced the noise in system's velocities and has mapped this controller as a practical one. The finite-time sliding mode enforcement and the states' convergence are shown, for all flight loops, i.e., forward flight and backward flight, via the Lyapunov approach. All these claims are verified via numerical simulations and experimental implementation of the quadcopter system in a Matlab environment. For a more impressive presentation, the developed simulation results are compared with standard literature.

Decentralized coordinated optimal guaranteed cost control for a roll-to-roll web machine

This article investigates a coordinated optimal guaranteed cost control (DCOGCC) for a multi-motor roll-to-roll web machine with time-varying and uncertain parameters. The state-space oriented DCOGCC law is designed to ensure that each subsystem of the web machine is stable and the upper bound of performance index is minimum. Linear matrix inequality (LMI) conditions to guarantee the stability of the systems with DCOGCC are derived. A decentralized model is adopted by regarding the entire machine as a synthetic system, then the original decentralized model is transformed into an equivalent one. By choosing appropriate information of consecutive subsystems as coordination variables, the DCOGCC scheme may attenuate the interaction effects between subsystems. The results of some simulations and experiments are given to verify the feasibility and effectiveness of the DCOGCC.

Adaptive robust servo constraint tracking control for an underactuated quadrotor UAV with mismatched uncertainties

In this research, to achieve the altitude and attitude tracking control of an underactuated quadrotor UAV with mismatched uncertainties, based upon Udwadia-Kalaba theory, a novel adaptive robust tracking control approach is proposed and which will be designed in two steps. First, aiming at the uncertain and underactuated quadrotor UAV, regardless of initial constraint deviation and mismatched uncertainties, a nominal control is constructed through transforming the desired trajectories into corresponding servo constraints; second, for the mismatched uncertainties, we decompose them into two parts, i.e. the matched part and mismatched part, and the mismatched part will "vanish" during the stability analysis of proposed adaptive robust controller. Eventually, with such a decomposition technique, the large mismatched uncertainties can be addressed properly and the burden of controller design will be reduced to a certain degree. In addition, two deterministic robust control performances are also guaranteed by our proposed approach. The simulation results have shown a good robustness and tracking precision of our proposed scheme for quadrotor UAV.

A Robotic Cognitive Architecture for Slope and Dam Inspections

Big construction enterprises, such as electrical power generation dams and mining slopes, demand continuous visual inspections. The sizes of these structures and the necessary level of detail in each mission requires a conflicting set of multi-objective goals, such as performance, quality, and safety. It is challenging for human operators, or simple autonomous path-following drones, to process all this information, and thus, it is common that a mission must be repeated several times until it succeeds. This paper deals with this problem by developing a new cognitive architecture based on a collaborative environment between the unmanned aerial vehicles (UAVs) and other agents focusing on optimizing the data gathering, information processing, and decision-making. The proposed architecture breaks the problem into independent units ranging from sensors and actuators up to high-level intelligence processes. It organizes the structures into data and information; each agent may request an individual behavior from the system. To deal with conflicting behaviors, a supervisory agent analyzes all requests and defines the final planning. This architecture enables real-time decision-making with intelligent social behavior among the agents. Thus, it is possible to process and make decisions about the best way to accomplish the mission. To present the methodology, slope inspection scenarios are shown.

Information fusion estimation-based path following control of quadrotor UAVs subjected to Gaussian random disturbance

Random disturbance has a detrimental effect on the reliability and safety of quadrotor unmanned aerial vehicles (UAVs). This paper proposes an anti-Gaussian random disturbance control method for the path following of a quadrotor UAV. The quadrotor system is linearized and divided into two subsystems, i.e., a translational subsystem and a rotational subsystem, and hierarchical strategy is used to design the overall control architecture. In order to suppress the negative effects of Gaussian random disturbances and simplify the design process of linear-quadratic optimal output tracking control problem, a new information fusion estimation based robust control named Gaussian information fusion control (GIFC) scheme is proposed. The convergence of the output tracking errors of GIFC system is proved via Lyapunov theory. The proposed GIFC control scheme is employed for position and attitude controller designs to enhance the robustness of the quadrotor system to Gaussian random perturbations. Finally numerical simulation experiments illustrate the effectiveness and robustness of the proposed control strategy.

Robust PID control of quadrotors with power reduction analysis

This paper presents a novel robust controller applied to a quadrotor vehicle for regulation and trajectory tracking tasks. In the proposed scheme, the quadrotor position is controlled by a proportional integral derivative (PID) controller, while the orientation control is achieved through a model-based controller. The proposed controller is combined with a power reduction methodology, which includes a controller-gains tuning stage using the cuckoo search algorithm, and a minimum jerk trajectory design stage. The performance of the new controller is assessed in a free-disturbance case and under the effect of parametric uncertainty and aero-dynamical disturbances. The new controller is compared against two linear PID controllers and a nonlinear sliding mode-based controller. Numerical simulations demonstrate the superiority of the proposed scheme as well as its robustness against different types of perturbations. Also, it is proven that the power demanded by any controller is reduced when using the power reduction methodology.

Learning-Based Robust Tracking Control of Quadrotor With Time-Varying and Coupling Uncertainties

In this paper, a learning-based robust tracking control scheme is proposed for a quadrotor unmanned aerial vehicle system. The quadrotor dynamics are modeled including time-varying and coupling uncertainties. By designing position and attitude tracking error subsystems, the robust tracking control strategy is conducted by involving the approximately optimal control of associated nominal error subsystems. Furthermore, an improved weight updating rule is adopted, and neural networks are applied in the learning-based control scheme to get the approximately optimal control laws of the nominal error subsystems. The stability of tracking error subsystems with time-varying and coupling uncertainties is provided as the theoretical guarantee of learning-based robust tracking control scheme. Finally, considering the variable disturbances in the actual environment, three simulation cases are presented based on linear and nonlinear models of quadrotor with competitive results to demonstrate the effectiveness of the proposed control scheme.

Disturbance suppression for quadrotor UAV using sliding-mode-observer-based equivalent-input-disturbance approach

This paper presents a new control scheme for quadrotor unmanned aerial vehicle attitude control and disturbance suppression. A quadrotor dynamic model is divided into two subsystems: fully-actuated and under-actuated. While the PID method is used to control the fully-actuated subsystem, a sliding-mode-observer-based equivalent-input-disturbance approach is used to control the under-actuated subsystem. The system design is simple, and it is globally uniformly ultimately bounded. Simulations and comparisons demonstrate the effectiveness of the method.

Avoiding obstacles in cooperative load transportation

This work deals with load transportation by quadrotors, when the load is attached to the vehicles through flexible cables. More specifically, two quadrotors are used to carry a single load, which is attached to both vehicles, through such kind of cables. The idea of using two quadrotors working cooperatively to carry the load is adopted to suppress any load oscillation in the direction of movement, what would happen if just one UAV were used. As a consequence of using two UAVs (or more than two) it can happen collisions between the vehicles when carrying the load, caused by the forces the load exert on the two vehicles, whose tendency is to bring the vehicles closer one to the other when they accelerate forward. The paper proposes a strategy to avoid such collisions and any collision with obstacles eventually present in the working space as well. Simulated results are shown and discussed, using two AR.Drone^®2.0 quadrotor to carry the load, which validate the proposed strategy.

Robust H∞ attitude tracking control of a quadrotor UAV on SO(3) via variation-based linearization and interval matrix approach

This paper deals with the attitude tracking control of quadrotor unmanned aerial vehicles (UAV) with uncertainties and external disturbances. The control system is expressed on the special orthogonal group, SO(3), to avoid singularities and ambiguities associated with Euler angles and quaternions respectively. It is also the basis for achieving large angle tracking and complex UAV maneuver. Meanwhile, it greatly reducing the complexity of the controller design via variation-based linearization. And the approach of interval matrix is introduced to solve problems of controller online calculation and reduced control accuracy caused by uncertain parameters in model. The proposed robust H_∞ control system can exponential asymptotically follow a desired attitude trajectory in the presence of unstructured bounded disturbances. Finally, several simulation results are provided to validate the effectiveness, advantages and robustness of the proposed method.

Finite-time trajectory tracking control for a 12-rotor unmanned aerial vehicle with input saturation

Finite-time trajectory tracking problem for a novel 12-rotor unmanned aerial vehicle (UAV) with input saturation is investigated in this paper. The UAV is divided into outer loop (altitude system and translational system) and inner loop (attitude system), and hierarchical structure is adopted to design the control scheme. In order to ensure finite-time convergence property and compensate input saturation impact simultaneously, a finite-time backstepping control strategy combined with a finite-time auxiliary system is proposed for the outer loop. Additional signals are generated to prevent control performance degradation caused by input saturation. The finite-time stability for outer loop is rigorously proved via Lyapunov theory. For inner loop, linear active disturbance rejection control is employed for attitude controllers design to enhance the robustness against the lumped disturbances. Finally simulation experiments illustrate the effectiveness and superiority of the proposed algorithm.

Decentralized coordinated control of elastic web winding systems without tension sensor

In elastic web winding systems, precise regulation of web tension in each span is critical to ensure final product quality, and to achieve low cost by reducing the occurrence of web break or fold. Generally, web winding systems use load cells or swing rolls as tension sensors, which add cost, reduce system reliability and increase the difficulty of control. In this paper, a decentralized coordinated control scheme with tension observers is designed for a three-motor web-winding system. First, two tension observers are proposed to estimate the unwinding and winding tension. The designed observers consider the essential dynamic, radius, and inertial variation effects and only require the modest computational effort. Then, using the estimated tensions as feedback signals, a robust decentralized coordinated controller is adopted to reduce the interaction between subsystems. Asymptotic stabilities of the observer error dynamics and the closed-loop winding systems are demonstrated via Lyapunov stability theory. The observer gains and the controller gains can be obtained by solving matrix inequalities. Finally, some simulations and experiments are performed on a paper winding setup to test the performance of the designed observers and the observer-base DCC method, respectively.