Compound Disturbance Observer for Flight Simulator

This article presents a new cascaded extended state observer (CESO)-based sliding-mode control (SMC) for an underactuated flexible joint robot (FJR). The control of the FJR has many challenges, including coupling, underactuation, nonlinearity, uncertainties and external disturbances, and the noise amplification especially in the high-order systems. The proposed control integrates the CESO and SMC, in which the CESO estimates the states and disturbances, and the SMC provides the system robustness to the uncertainty and disturbance estimation errors. First, a dynamic model of the FJR is derived and converted from an underactuated form to a canonical form via the Olfati transformation and a flatness approach, which reduces the complexity of the controller design. Furthermore, by taking the advantage of available measurable states, the CESO is adopted to attenuate the noises and make SMC feasible for high-order systems. Moreover, the CESO estimates the disturbances, which relaxes the upper bound of the disturbance in the SMC and reduces the chattering due to smaller switching gains. A stability analysis of the closed-loop system is presented based on the Lyapunov method. The effectiveness of the proposed control is verified in simulations and experimentally on a real-time FJR system.

This article presents an original motion control strategy for robot manipulators based on the coupling of the inverse dynamics method with the so-called second-order sliding mode control approach. Using this method, in principle, all the coupling non-linearities in the dynamical model of the manipulator are compensated, transforming the multi-input non-linear system into a linear and decoupled one. Actually, since the inverse dynamics relies on an identified model, some residual uncertain terms remain and perturb the linear and decoupled system. This motivates the use of a robust control design approach to complete the control scheme. In this article the sliding mode control methodology is adopted. Sliding mode control has many appreciable features, such as design simplicity and robustness versus a wide class of uncertainties and disturbances. Yet conventional sliding mode control seems inappropriate to be applied in robotics since it can generate the so-called chattering effect, which can be destructive for the controlled robot. In this article, this problem is suitably circumvented by designing a second-order sliding mode controller capable of generating a continuous control law making the proposed sliding mode controller actually applicable to industrial robots. To build the inverse dynamics part of the proposed controller, a suitable dynamical model of the system has been formulated, and its parameters have been accurately identified relying on a practical MIMO identification procedure recently devised. The proposed inverse dynamics-based second-order sliding mode controller has been experimentally tested on a COMAU SMART3-S2 industrial manipulator, demonstrating the tracking properties and the good performances of the controlled system.

In this paper a novel concept of event triggering control (ETC) for effective resource utilization is proposed for dc microgrid. Matched uncertainty elimination is possible through sliding mode control (SMC) itself as addressed in the literatures. This paper proposes a new approach for suppression of both matched and unmatched uncertainties in grid connected and islanded mode through an integral disturbance observer (IDO) which is designed with super twisting SMC to provide dual filtering phenomena pertaining to system perturbations. The IDO facilitates control algorithm to manage effective event counts during disturbance conditions. The proposed controller is designed in order to regulate DC bus voltage and enhance the microgrid capability to perform stable operation in presence of uncertainties. Chattering free finite time convergent SMC is designed with super twisting reaching law to obtain robust behavior of dc microgrid. Results are compared with power rate reaching SMC, Nonlinear disturbance observer (NDO) based controller and PI controller. In the proposed work event triggering condition is designed first time under super twisting reaching law. Comparative assessment is accomplished in lieu of demonstrating the superior performance of event trigger SMC through MATLAB/Simulink and Typhoon based controller hardware in loop (CHIL) platform.

This dissertation presents a comprehensive approach to addressing the challenges associated with the control and navigation of Unmanned Aerial Vehicles (UAVs), specifically focusing on robustness under GPS-denied, turbulent, and dark indoor conditions with various disturbances. Initial efforts involved designing and theoretically validating Sliding Mode Controllers (SMC) with Disturbance Observers using MATLAB/SIMULINK, optimized using offline Particle Swarm Optimization (PSO). In order to evaluate their performance, a lightweight simulator was developed to simulate both quadcopter and hexacopter configurations under the PX4 architecture. This simulator served to validate and compare the optimized SMC against PSO-optimized PID controllers. The results of these comparisons demonstrated the superior adaptability of the SMC, especially in environments characterized by significant sensor noise and disturbances. Subsequent practical indoor tests were conducted with real quadcopters, which provided additional verification of the robustness and reliability of the enhanced control theory with the actual UAVs under dynamic disturbances. To further evaluate the compatibility and adaptability of the SMC, this dissertation establishes a framework for interfacing with high-performance STMH7 chips, serving as the UAV microcontroller unit (MCU). This framework facilitates the connection of various sensors and provides guidance for constructing different quadcopter frames. Moreover, it enables the comparison of different flight controllers on distinct air-frames. Concurrently, the optimized SMC allows for remote dynamic parameter tuning during flight. In pursuit of improved localization capacity, the dissertation also explores the integration of an Intel Realsense D435i camera with an Inertial Measurement Unit (IMU) for Visual-Inertial Odometry (VIO) fusion within the Robot Operating System (ROS) environment. This integration employs an onboard companion computer for real-time VIO estimation and flight command. The effectiveness of the VIO algorithm is verified through both simulations and real-world experiments, highlighting its ability to enhance UAV localization and navigation. Additionally, a visual inertial odometry method for UAV Simultaneous Localization and Mapping (vSLAM) is tested and validated in both simulated and real drone environments. Furthermore, the dissertation introduces an innovative hybrid filtered multi-directional radar inertial odometry solution denoted as Hybrid-MRIO. This Error State Extended Kalman Filter (ES-EKF) based Radar Inertial Odometry (RIO) approach is implemented within the open-source PX4 autopilot system, enhancing UAV navigation accuracy and performance, and serves as a robust navigation alternative, particularly in challenging environments where traditional navigation systems prove ineffective, such as dark or smoky conditions. This solution integrates data from multiple software synchronized high-resolution Frequency-Modulated Continuous-Wave (FMCW) mmWave radars with an IMU. A subsequent 4D (x, y, z, doppler) mmWave radar SLAM (rSLAM) system has been developed, including three modules: front-end, loop detection module, and back-end. In the front-end, radar ego-velocity is utilized for states estimation and dynamic object removal, and a point cloud registration-based approach known as APDGICP (Adaptive Probability Distribution-GICP) is employed for keyframe detection. The loop detection module utilizes the intensity scan context to identify potential loop closure candidates. In the back-end, a pose graph is constructed, integrating RIO estimated odometry and identified loop closures for better localization. To develop fully-autonomous UAVs with their decision making modules, this dissertation details the development of a custom AI-powered fully-autonomous quadcopter equipped with companion computers and stereo IR cameras. Additionally, this dissertation discusses a swarm of small Unmanned Aerial Systems (SUAS) interconnected through a software-defined communications network. These drones demonstrated their capacity to independently/collaboratively execute a wide range of tasks, including target search, detection, identification, classification, tracking, and following, both in simulated and real-world scenarios. The system exhibits advanced collision avoidance capabilities and the ability to strategically respond to dynamic scenarios, such as changes in target behavior, highlighting its effectiveness in managing dynamic and challenging situations without the need for continuous human intervention.--Author's abstract

Multi-axis motion system is widely applied in commercial industrial machines such as precision CNC machine tools, Robot manipulator and laser cutting machines, etc. Contour accuracy plays a major role for the multi-axis servo motion system. The contour machining accuracy is related to the synthesis of single-axis position accuracy and multi-axis linkage accuracy. Only improving the single-axis tracking performance cannot effectively guarantee the machining accuracy of multi-axis system. The primary objective of this study was to design a contour control method to improve single-axis tracking accuracy and multi-axis contour accuracy. A control strategy that combines a sliding mode tracking controller, a disturbance observer and an adaptive fuzzy PID cross coupled controller is proposed. Sliding mode control is simple and has strong robustness to parameter changes and disturbance, which is especially suitable for control of such as non-linear multi-axis motion system. Besides, disturbance is inevitable in practical application, which degrades the motion accuracy. In order to eliminate the influence of external disturbance and uncertainty, disturbance observer is adopted to accurately estimate external disturbance and reduce the chattering phenomenon of sliding mode control, then improve the single-axis tracking accuracy. In order to further consider the coordination between different motion axes and improve the contour accuracy, the PID cross coupled control is used. Owing to conventional PID control cannot satisfy the multi-axis servo motion system with nonlinearity and uncertainty, an adaptive fuzzy method with on-line real-time PID parameters adjustment is proposed. The three-axis motion platform driven by PMLSM is used as the control object, to analysis the influence of disturbance observer on sliding mode control signal and analysis adaptive fuzzy PID cross coupled control performance respectively. The disturbance observer is used to observe the disturbance signal and estimate the disturbance well. The chattering of the sliding mode control signal is obviously improved. Next, compared with the conventional PID-CCC control, adaptive fuzzy PID- CCC control can significantly reduce the tracking error, the contour accuracy is also obviously improved. The disturbance observer can effectively eliminate the influence of external disturbance, reduce the chattering of sliding mode control, and ensure the single-axis accurate tracking. The self-adaptive fuzzy PID cross coupled controller can eliminate the influence of the dynamic characteristics mismatching and parameter difference of each axis, and improve contour accuracy. The simulation results clearly demonstrate the effectiveness of the proposed control method.

This paper presents design and force-tracking impedance control of 2-degree-of-freedom (DOF) wall-cleaning manipulator equipped with disturbance observer (DOB) and sliding mode control (SMC). In order to keep in contact with various shapes of walls, the proposed manipulator is designed to ensure 2-DOF motions of translation and tilting by using ball screws. The position-based force tracking impedance control (FTIC) is first adopted for the proposed manipulator not only to interact with walls in a desired dynamic behavior but also to maintain a constant contact force. Also, to improve the force tracking capability of proposed manipulator against different walls and brushes for manipulator, the FTIC is combined with the disturbance observer (DOB) and the sliding mode control (SMC). Extensive experiments prove that although different brushes used for manipulator rotate against varying shapes of walls, the proposed manipulator can keep a constant contact force within a bound of ± 4.5 N by virtue of the proposed FTIC equipped with the DOB and the SMC.

The work presented here is concerned with the robust control problem for the inverted pendulum with mismatched disturbances via a non-linear disturbance observer (NDO)-based sliding mode control (SMC) method. The NDO-based SMC method provides a solution to the main limitation of conventional first-order sliding mode controllers that is the presence of high frequency oscillations in the control input known as chattering while retaining the nominal performance. To show the effectiveness of NDO-based SMC, both the conventional SMC and the integral SMC (I-SMC) methods are employed in the simulation studies for the purpose of comparison studies and results demonstrate the merits of NDO-based SMC.

Two wheel mobile manipulator has the potential to become multi-skilled robot in the field of robotics engineering and it is already implemented by using inverted pendulum control. Centre of gravity position is controlled to achieve the balancing of robot. Due to the unbalanced nature and the nonholonomic property of the two-wheel mobile manipulator, balancing is challenging task. On the other hand sliding mode control is a good candidate to address the nonlinear/under actuated system. This paper presents the control methods for balancing of two-wheel mobile manipulator. This paper proposes a novel second order sliding mode controller using twisting algorithm, disturbance observer and dynamics of double inverted pendulum. Dynamics of double inverted pendulum is used to design the control equation of sliding mode controller. Twisting algorithm is used to design the control input. Disturbance observer is compensated model uncertainties and external disturbances. Posture of two wheel mobile manipulator can successfully stabilized by this novel controller.

This paper proposes a sliding mode control with a disturbance estimation for an underwater robot. The mobility performance of an underwater robot is influenced by modeling error, observation noise, and several disturbances such as ocean current and tidal current. Therefore, a robust control system is needed for precise motion control of an underwater robot. This paper uses a sliding mode control, which is one of the robust control methods. In a sliding mode control, chattering tends to occur, if the switching gain is set to a high value. On the other hand, it is desirable to set the switching gain high from the viewpoint of robustness. Therefore, there is a trade-off between the switching gain and robustness. In the proposed method, the disturbance is estimated in real-time, and this estimated value is added to the control input. Most of the disturbances are compensated by this estimated value, and the sliding mode control is used for the rest of the disturbances. As a result, the robust control system is achieved by using the proposed method, even if the switching gain is set to a low value. The validity of the proposed method was confirmed from the simulation and experimental results.

A lateral motion control problem of an experimental autonomous underwater vehicle (AUV) MAYA AUV is considered. In this paper, a disturbance observer based sliding mode control (DOB-SMC) scheme is proposed in the presence of parameter perturbation and disturbances. During motion, a highly uncertain ocean environment demands robust control to handle the parameter perturbations and disturbances. This problem can be directly resolved by a sliding mode control (SMC) design. The disturbance observer (DOB) is designed to approximate the equivalent control of SMC containing disturbances. To restrain the chattering, DOB is designed such that the disturbance estimation converges to disturbance exponentially and feedback switching gain converges to zero exponentially. The proposed control scheme is examined through a computational tool.

The operational condition of mass transfer imposes high-speed and high-precision requirements on the motion control of aligning platforms with in-plane four-Prismatic-Prismatic-Revolute (PPR) parallel mechanism. However, the strong nonlinear coupling among multiple kinematic chains and time-varying system uncertainties pose substantial challenges for the design of platform motion controllers. To address these issues, this article proposes a synchronization control strategy based on time-varying gain disturbance observer (DOB) and ring-coupled sliding mode control (SMC) for a 4-PPR parallel platform. The time-varying gain DOB enhances the position tracking performance of kinematic chains by feed-forward compensation for external disturbances and system uncertainties. The observer convergence under a slow-varying disturbance is also well-proven. Additionally, considering the ring-coupled errors under nonlinear speed conditions, SMC is employed to improve the motion synchronization among the axes of the platform. Finally, numerical simulations and experimental validations of tracking control are conducted on the 4-PPR parallel platform test rig. The results demonstrate that this method exhibits superior interaxis synchronization control and dynamic response performance compared to other controllers.

This article seeks to achieve high tracking performance of the hybrid automobile electro-coating conveying mechanism with disturbances and uncertainties. An integral sliding mode control scheme is first presented to eliminate the reaching phase in sliding mode control. Then, an adaptive integral sliding mode controller is designed without knowing the disturbance information. Finally, a composite strategy, referred to as nonlinear disturbance observer (NDO)-based adaptive integral sliding model control, is put forward to further reduce the switching gain. By compensating the lumped disturbances via a NDO, the switching gain is only required to be higher than upper bound of the disturbance estimation error which is much smaller than actual disturbance. The results of both numerical simulations and experiments show that the proposed approach has good control performance especially in reducing the switching gain and alleviating the chattering problem.

In order to improve the anti-disturbance performance of permanent magnet synchronous motor (PMSM) servo system, a sliding-mode control strategy using a new reaching law (NRL) is proposed. The NRL incorporates power term and switching gain term of the system state variables into the conventional exponential reaching law (CERL), which can effectively suppress the sliding-mode chattering and increase the convergence rate of system state reaching sliding-mode surface. Based on this new reaching law, a sliding-mode speed controller (SMSC) of PMSM is designed. At the same time, to solve the chattering problem caused by the large sliding-mode switching gain, an anti-disturbance sliding-mode speed controller method with an extended sliding-mode disturbance observer (ESMDO), called SMSC+ESMDO method, is developed. The sliding-mode disturbance observer is designed to accurately estimate the motor speed and external load disturbances, and the disturbance estimator is used as a feed-forward to compensate the sliding-mode speed controller (SMSC) to improve the system robustness and reduce the system chattering. Simulation and experimental results show that the proposed compound sliding-mode control strategy can effectively improve the dynamic performance and robustness of the system compared with the PI controller.

A nonlinear backstepping control is proposed for the coupled normal form of nonlinear systems. The proposed method is designed by combining the sliding‐mode control and backstepping control with a disturbance observer (DOB). The key idea behind the proposed method is that the linear terms of state variables of the second subsystem are lumped into the virtual input in the first subsystem. A DOB is developed to estimate the external disturbances. Auxiliary state variables are used to avoid amplification of the measurement noise in the DOB. For output tracking and unmatched disturbance cancellation in the first subsystem, the desired virtual input is derived via the backstepping procedure. The actual input in the second subsystem is developed to guarantee the convergence of the virtual input to the desired virtual input by using a sliding‐mode control. The stability of the closed‐loop is verified by using the input‐to‐state stable (ISS) property. The performance of the proposed method is validated via numerical simulations and an application to a vehicle system based on CarSim platform.

Improved sliding-mode control for a class of disturbed systems based on a disturbance observer