This article presents a modified active-disturbance-rejection control (ADRC) combined with a sliding mode control (SMC) regarding the tracking control problems for plants with unmatched uncertainty. The proposed modified active-disturbance-rejection control with sliding mode (ADRC-SM) employs a reduced-order extended state observer (ESO) for estimating various uncertainties of system in time, including unmatched and matched uncertainties. Meanwhile, a novel reaching law of SMC was designed by using the cycloid function as the main controller of ADRC, which ensures the robustness of the uncertain system. Due to the reduced-order ESO tracking and compensating for various uncertainties in the system as a total disturbance, the upper bound of the disturbance in the SMC is relaxed. The gain coefficient of the reaching law only needs to be designed to be larger than the limit of the lumped disturbance; thus, the chattering problem is greatly reduced. The designed new reaching law of the cycloid function shortens the time for the system state’s convergence to the sliding mode’s surface. The cycloid function replaces the switching function in the traditional reaching law, making the actual control input continuous and shortening the approach time. Compared with traditional ADRC-SM, the use of multiple ESOs or intelligent algorithms to approximate plant parameters can be avoided, the design is simplified, its robustness is enhanced, computational costs are reduced, and the convergence time is reduced. The controlled object with unmatched uncertainty is transformed into a system with matched uncertainty using state-space transformation, which reduces the complexity of the controller’s design. In addition, the stability analysis of the closed-loop system is carried out based on the Lyapunov method. Simulations and experiments verify that the modified ADRC-SM has the merits of fast response, small overshoot, small steady-state error, strong anti-interference competence, and high control accuracy.

/pdf/a-modified-active-disturbance-rejection-control-with-sliding-2oq1yhnx.pdf

A Modified Active-Disturbance-Rejection Control with Sliding Modes for an Uncertain System by Using a Novel Reaching Law

Dear Editor, This letter proposes a robust control strategy for the autonomous landing of a quadrotor on a moving target. Specifically, a force command that consists of a cascade dynamics estimator and an optimal guaranteed cost control law is exploited for the position-loop tracking. Then, an orientation constraint torque command is employed for the attitude-loop tracking such that the quadrotor refrains from flipping during the landing operation. Stability analysis indicates that the overall closed-loop system is asymptotically stable. Finally, flight experiments validate and access the theoretical results. 

https://ieeexplore.ieee.org/ielx7/6570654/10057126/10057193.pdf

Moving Target Landing of a Quadrotor Using Robust Optimal Guaranteed Cost Control

This article investigates the motion planning and reinforcement learning control method for autonomous landing issue of a vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) on a moving target. A novel funnel shaped surface is first proposed to maintain the relative position within a preassigned set for precise and safe landing. An orientation constraint planning is designed to avoid the flipping over. Moreover, a data-based reinforcement learning strategy is proposed to update the learning weight online, which not only effectively relieves the typical persistent excitation condition to the finite excitation but also allows the inadmissible initial control condition. A filter-based disturbance estimator is employed to compensate the unknown terms. The stability of the overall closed-loop system is analyzed theoretically and concluded to be uniformly ultimately bounded. Simulation and flight experiment are performed to validate that UAV can land on the moving target along the preassigned trajectory.

Reinforcement Learning Control for Moving Target Landing of VTOL UAVs With Motion Constraints

Model-free tracking control methods have been developed for redundant robotic manipulators with unknown kinematic or dynamic models. However, most existing works have not considered the problems of joint physical limits and joint angular drift. Joint angular drift refers to the phenomenon that the joint angles of a redundant manipulator are different from their initial state when the end-effector of the manipulator returns to its initial position. Therefore, this article proposes a model-free scheme for the tracking control of redundant manipulators as well as the avoidance of joint physical limits and joint angular drift. The proposed method aims to overcome these challenges by formulating the inverse kinematics problem as a constrained optimization problem, which incorporates the avoidance of joint angular drift into the optimization objective and takes the joint physical limits as a constraint. At the same time, an online Jacobian estimator is designed to observe the state of the manipulator. Specifically, it can estimate the Jacobian matrix of a redundant manipulator in real-time during the operation by fully exploiting the sensory data, without knowing the analytic robot model. Then, the optimization problem is integrated with the Jacobian estimator and solved by a discrete-time algorithm. Theoretical analysis is conducted to prove the stability and convergence of the proposed method. Moreover, the efficacy, practicability and superiority of the proposed method are supported by simulations and experiments based on different redundant manipulators. 

Model-free kinematic control of redundant manipulators with simultaneous joint-physical-limit and joint-angular-drift handling.

To achieve high-accuracy manipulation in the presence of unknown dynamics and external disturbance, we propose an efficient and robust motion controller (named TvUDE) for robotic manipulators. The controller incorporates a disturbance estimation mechanism that utilizes reformulated robot dynamics and filtering operations to obtain uncertainty and disturbance without requiring measurement of acceleration. Furthermore, we design a time-varying control input gain to enhance the control system's robustness. Finally, we analyze the boundness of the control signal and the stability of the closed-loop system, and conduct a set of experiments on a six-DOF robotic manipulator. The experimental results verify the effectiveness of TvUDE in handling internal uncertainty and external static or transient disturbance. 

/pdf/motion-control-based-on-disturbance-estimation-and-time-2rj2f8vf.pdf

Motion Control based on Disturbance Estimation and Time-Varying Gain for
  Robotic Manipulators

Unknown System Dynamics Estimator for Nonlinear Uncertain Systems

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Unknown System Dynamics Estimator for Nonlinear Uncertain Systems