Robot arm force control through system linearization by nonlinear feedback

Parallel manipulators with less than six degrees of freedom (DOF) have been increasingly used in high-speed hybrid machine tools. The structural features of parallel manipulators are dynamic, a characteristic that is particularly significant when these manipulators are used in high-speed machine tools. However, normal kinematic control method cannot satisfy the requirements of the control system. Many researchers use model-based dynamic control methods, such as the dynamic feedforward control method. However, these methods are rarely used in hybrid machine tools because of the complex dynamic model of the parallel manipulator. In order to study the dynamic control method of parallel manipulators, the dynamic feedforward control method is used in the dynamic control system of a 3-PSP (prismatic-spherical-prismatic) 3-DOF spatial parallel manipulator used as a spindle head in a high-speed hybrid machine tool. Using kinematic analysis as basis and the Newton-Euler method, we derive the dynamic model of the parallel manipulator. Furthermore, a model-based dynamic feedforward control system consisting of both kinematic control and dynamic control subsystems is established. The dynamic control subsystem consists of two modules. One is used to eliminate the influence of the dynamic characteristics of high-speed movement, and the other is used to eliminate the dynamic disturbances in the milling process. Finally, the simulation model of the dynamic feedforward control system of the 3-PSP parallel manipulator is constructed in Matlab/Simulink. The simulations of the control system eliminating the influence of the dynamic characteristics and dynamic disturbances are conducted. A comparative study between the simulations and the normal kinematic control method is also presented.The simulations prove that the dynamic feedforward control method effectively eliminates the influence of the dynamic disturbances and dynamic characteristics of the parallel manipulator on high-speed machine tools, and significantly improves the trajectory accuracy. This is the first attempt to introduce the dynamic feedfordward control method into the 3-PSP spatial parallel manipulator whose dynamic model is complex and provides a study basis for the real-time dynamic control of the high-speed hybrid machine tools.

Multiple coordinated robot arms are modeled by considering the arms as closed kinematic chains and as a force-constrained mechanical system working on the same object simultaneously. In both formulations, a novel dynamic control method is discussed. It is based on feedback linearization and simultaneous output decoupling technique. By applying a nonlinear feedback and a nonlinear coordinate transformation, the complicated model of the multiple robot arms in either formulation is converted into a linear and output decoupled system. The linear system control theory and optimal control theory are used to design robust controllers in the task space. The first formulation has the advantage of automatically handling the coordination and load distribution among the robot arms. In the second formulation, it was found that by choosing a general output equation it became possible simultaneously to superimpose the position and velocity error feedback with the force-torque error feedback in the task space. >

The surface following by a robot arm is investigated in this paper. The goal is to present control strategies so that the arm can follow a surface at a given speed with desired contact force. First, a discussion on the use of direct-drive manipulators with decoupled and invariant dynamics is given. These are shown to be suitable for such force control applications. In this case, the controller design in either joint space or end effector space would involve nonlinearities due to kinematics only. This would reduce the computation burden and allows for high performance since the kinematic parameters can be estimated with better accuracies than dynamic parameters. Second, to have a better understanding of some fundamental characteristics of force control, such as the effects of actuator dynamics, environment/sensor stiffness on the performance, experiments were done using a one degree-of-freedom direct-drive arm. The use of a high gain inner velocity loop is shown to give the force control good command following and disturbance rejection characteristics. The direct-drive manipulator shows a superior performance over conventional systems as a result of fast actuator dynamics, low friction and no mechanical backlash. The experiments are conducted to investigate the force speed of response and steady state behavior, impact control and surface following performance.

New results on dynamic output state feedback stabilization of some class of time-varying nonlinear Caputo derivative systems

Legged mobile manipulators are receiving much more attention. Mobile platforms can infinitely expand the workspace of robotic arms, providing more possibilities for robot application scenarios. Compared with wheeled mobile manipulators, legged mobile manipulators have higher requirements for cooperative control of legged robots and robotic arms. This work decouples the control of the robotic arm and the legged robot. On the legged robot side, we explicitly estimate the wrench exerted by the robotic arm on the base and bring it into the legged robot’s dynamics, and then use a nonlinear model predictive controller (NMPC) to control the legged robot. On the robotics arm side, we adopt an impedance controller to realize the end-effector’s force control, and the introduction of impedance control has improved the safety and interactivity of legged mobile manipulators. We conducted experiments on physical robot to compare the differences between decoupled control and independent control, and the results show that the stability and robustness of robot systems have improved using decoupled control.

Robotic systems have significantly transformed the landscape of minimally invasive surgery, offering enhanced precision, reduced recovery times, and improved patient outcomes. These systems have evolved from simple mechanical tools to sophisticated platforms integrating advanced control algorithms and real-time feedback mechanisms. This paper provides a comprehensive overview of the role of robotic systems in minimally invasive surgery, exploring the various benefits, inherent risks, and the challenges associated with their adoption and development. We examine the technical aspects of robotic control systems, such as kinematics, force control, and haptic feedback, which enable greater surgical accuracy. Despite these advantages, challenges such as system complexity, high costs, and ethical concerns remain significant barriers to widespread adoption. The future of robotic surgery lies in overcoming these obstacles, with advancements in system miniaturization and further refinement of control systems poised to enhance the efficacy and accessibility of robotic platforms. This paper explores the role of robotic systems in minimally invasive surgery, focusing on three key areas: bronchoscopy and ureteroscopy. By reviewing the benefits, risks, case studies, and future directions of these technologies, the paper seeks to provide an in-depth understanding of how robotic systems are shaping the future of surgery. Key words: Robotic Surgery, Minimally Invasive Surgery, Robotic Control Systems, Surgical Precision, PID Control, Kinematics, Inverse Kinematics, Forward Kinematics, Dynamic Control, Force Control, Impedance Control, Surgical Robotics, Haptic Feedback, Robotic Arm, Robotic Surgery Benefits, Robotic Surgery Risks, Robot-Assisted Surgery, Surgeon Console, Real-Time Feedback, Surgical Training, Robotic System Development, System Testing, Clinical Trials, Surgical Robot Performance, Robotics in Urology, Telepresence Surgery, Robotic Surgery Cost, Robotic Surgery Future Directions.

A new track tracking control method based on Lagrange dynamic equation is proposed. Firstly, the kinetic energy equation and potential energy equation of the left and right robotic arms are derived and calculated based on Lagrange function and the robot dynamics equation in the generalized coordinate system. The friction model of the left and right robotic arms is designed based on the Stribeck model, and the Lagrangian dynamic equation of the dual-arm mechanism for the hatch docking is established. Secondly, based on the Lagrange dynamic model, the collaborative control system of the docking mechanism is designed, and the backstepping sliding mode controller is designed and analyzed. A fuzzy backstepping sliding mode controller is designed to control the gain matrix β of the backstepping sliding mode controller by adjusting the output of the system with fuzzy logic, which further improves the robustness of the control system. Finally, the effectiveness of the design, dynamic modeling and control algorithm design of the cabin docking mechanism is verified by software simulation and real experiment. The experimental results show that the control method can realize the accurate tracking and control of the motion trajectory and velocity trajectory of the dual-arm mechanism, and has good robustness. The maximum absolute error and standard deviation of the axis Angle of the mobile cabin after docking are 0.501° and 0.004°, which can meet the requirements of the actual production process.

With the advancement of technology in Global era, robotics is anticipated as one of the emerging field of science. Robots are gradually replacing humans and are performing complex tasks which humans are unable to perform. Robotic arm has its importance in heavy industry and in manufacturing processes for optimum results. The main task is to design a system that is capable of controlling a mechanical arm and is able to apply appropriate force to grab the targeted object. The entire robotic arm hardware setup is controlled with National Instruments myRIO-1900 kit in LabVIEW environment. Serial linked robot ED7220C is a five-joints and six degrees of freedom, robotic arm with rigid links. Object detection and classification is performed through a USB camera on LabVIEW in real time. First, the object is detected then according to its dynamic algorithm which classify the shape of object into circular, rectangular and elliptical shapes. Then the coordinate of these objects are provided as input to the robotic arm which can track the object based on the extracted information. Force control is also an essential part in the robot’s control design. Without control a robot may damage the object when it comes in contact with it. A force sensor is used to control the force exerted on the object. Force Sensitive Resistor (FSR) is used to determine the force or pressure that can be applied to the object. The experiments are connected with NI-myRIO-1900 and the FSR mounted inside the gripper of the robotic arm.

For the single machine connected to infinite bus power system with uncertainties, one nonlinear coordinated control scheme for Static Synchronous Compensator (STATCOM) and excitation is proposed in this paper. Firstly, in order to avoid solving the differential algebraic equations (DAEs) model of system, we simplify the DAEs into the classical differential equations, and then a new nonlinear parameter strict feedback model is given. Secondly, in order to make the system achieve the desired results, the controller is designed in two parts based on improved dynamic surface control method (IDSC) and passive control techniques. The theoretical analysis shows that the derived controller can not only attenuate the influences of external disturbances, but also has strong robustness for system parameters variety. The control law obtained is more effective and the system globally and uniformly ultimately bounded can be achieved using full nature of nonlinear dynamic. Lastly, the further simulation results indicate that the proposed controller can ensure transient stability of the power system under large sudden fault.

The present paper proposes, as an educational activity, the design of a system that allows the control of a robotic manipulator by using a sensory glove and an arm sleeve. The robotic manipulator features a robotic arm and hand, with a total of 10 degrees of freedom, using ten servo motors as actuators. On the other hand, the controller component features six flex sensors and two Inertial Measurement Units (IMUs). Due to the low force exerted by the motors, along with an issue regarding the reference frame of one of the IMUs, the robotic hand and wrist were detached from the robotic arm and both were tested separately. The results from real-time testing showed that the system successfully replicated the movements performed by the user. However, the system requires further improvements, mainly due to its lack of precision and limited degrees of freedom, along with other hardware issues. Regardless, an optimized design of the proposed system can have various applications, such as the manipulation of objects in hazardous conditions.

Haptic devices need to render accurate force to a human operator in order to create a virtual environment from a remote real environment. Existing end-effector type haptic devices employ parallel mechanisms to achieve force interaction in multiple degrees-of-freedom (DoF). Those parallel mechanisms have non-constant Jacobian matrices that create difficulties in the actuator and controller design for accurate haptic force interaction. This paper presents a 3-DoF translational parallel manipulator (TPM) with a constant Jacobian matrix to facilitate the force and impedance controller design. Instead of using external force sensors, series elastic actuators (SEAs) are used for the proposed device to realize the force rendering. SEAs can render more accurate output force and stiffness while the inertia and friction problems of using a gearhead can be ignored. In this paper, the modeling, design, and control of the haptic device are established to show the merits of the proposed TPM. Initial force control experiments demonstrate the accuracy and speed of SEA-based force control. We expect that this novel haptic device can serve as an alternative for robotic teleoperations requiring accurate force sensing and control.

Force controller design and evaluation for robot-assisted die and mould polishing

With online work environments and other distributed computing systems—such as cloud technologies or Internet of Things systems—becoming increasingly popular today due to the COVID-19 pandemic and general technological advances, the question of how to keep them secure has also become a pertinent concern. With this increased dependence on online systems for companies, cyberattacks have also been on the rise. To protect terminal devices, many companies have resorted to implementing a single boundary-defense model. This method has yielded positive results in securing the network from external threats, but it does not effectively protect network from internal security threats. With the vulnerabilities in the internal network security in mind, a dynamic access control method used with a zero-trust software-defined perimeter security model could be a viable solution. This study proposes a dynamic access control method using an engine with a new reward and penalty point-based system (RP Engine) and a dynamic task engine (DT Engine) for a zero-trust SDP security model.

This paper summarizes recent activities carried out for the development of an innovative anthropomorphic robotic hand called the DEXMART Hand. The main goal of this research is to face the problems that affect current robotic hands by introducing suitable design solutions aimed at achieving simplification and cost reduction while possibly enhancing robustness and performance. While certain aspects of the DEXMART Hand development have been presented in previous papers, this paper is the first to give a comprehensive description of the final hand version and its use to replicate human-like grasping. In this paper, particular emphasis is placed on the kinematics of the fingers and of the thumb, the wrist architecture, the dimensioning of the actuation system, and the final implementation of the position, force and tactile sensors. The paper focuses also on how these solutions have been integrated into the mechanical structure of this innovative robotic hand to enable precise force and displacement control of the whole system. Another important aspect is the lack of suitable control tools that severely limits the development of robotic hand applications. To address this issue, a new method for the observation of human hand behavior during interaction with common day-to-day objects by means of a 3D computer vision system is presented in this work together with a strategy for mapping human hand postures to the robotic hand. A simple control strategy based on postural synergies has been used to reduce the complexity of the grasp planning problem. As a preliminary evaluation of the DEXMART Hand’s capabilities, this approach has been adopted in this paper to simplify and speed up the transfer of human actions to the robotic hand, showing its effectiveness in reproducing human-like grasping.

Collaborative robots are being used in machining task more and more. However, they have the disadvantage of elasticity in their joints, causing position errors, vibration, and poor performance in applications where contact forces are required. The main goal of this article is to study the effect of the joint stiffness in force control tasks. For this purpose, the active stiffness of the joints has been modified according to theoretical deductions. The experiments have been achieved on a UR3 robot through an inner/ outer force control loop. A theoretical and experimental analysis shows the advantage of this type of control, which allows adjusting the active stiffness when interacting with a different environment rigidity.