Additive-Decomposition-Based Output Feedback Tracking Control for Systems with Measurable Nonlinearities and Unknown Disturbances

In this paper, a new control scheme, called as additive-decomposition-based tracking control, is proposed to solve the output feedback tracking problem for a class of systems with measurable nonlinearities and unknown disturbances. By the additive decomposition, the output feedback tracking task for the considered nonlinear system is decomposed into three independent subtasks: a pure tracking subtask for a linear time invariant (LTI) system, a pure rejection subtask for another LTI system and a stabilization subtask for a nonlinear system. By benefiting from the decomposition, the proposed additive-decomposition-based tracking control scheme i) can give a potential way to avoid conflict among tracking performance, rejection performance and robustness, and ii) can mix both design in time domain and frequency domain for one controller design. To demonstrate the effectiveness, the output feedback tracking problem for a single-link robot arm subject to a sinusoidal or a general disturbance is solved respectively, where the transfer function method for tracking and rejection and backstepping method for stabilization are applied together to the design.Comment: 23 pages, 6 figure

Biped robot with unconventional kinematics

The article deals with the design of a robot with an unconventional kinematic structure, which is able to vertically stabilize the position of the robot base for the placement of sensors and handling superstructures. The robot concept was designed to have as few actuators as possible. The robot's kinematics was solved for the purpose of simulating the robot's movement and implementation into the robot's control system.Web of Science20225824581

Decentralized adaptive partitioned approximation control of high degrees-of-freedom robotic manipulators considering three actuator control modes

International audiencePartitioned approximation control is avoided in most decentralized control algorithms; however, it is essential to design a feedforward control term for improving the tracking accuracy of the desired references. In addition, consideration of actuator dynamics is important for a robot with high-velocity movement and highly varying loads. As a result, this work is focused on decentralized adaptive partitioned approximation control for complex robotic systems using the orthogonal basis functions as strong approximators. In essence, the partitioned approximation technique is intrinsically decentralized with some modifications. Three actuator control modes are considered in this study: (i) a torque control mode in which the armature current is well controlled by a current servo amplifier and the motor torque/current constant is known, (ii) a current control mode in which the torque/current constant is unknown, and (iii) a voltage control mode with no current servo control being available. The proposed decentralized control law consists of three terms: the partitioned approximation-based feedforward term that is necessary for precise tracking, the high gain-based feedback term, and the adaptive sliding gain-based term for compensation of modeling error. The passivity property is essential to prove the stability of local stability of the individual subsystem with guaranteed global stability. Two case studies are used to prove the validity of the proposed controller: a two-link manipulator and a six-link biped robot

Robust Model Predictive Control for Robot Manipulators

Inherent nonlinearities, external disturbances and model uncertainties hinder the performance of controlling real-world systems. In the present study, we proposed a robust model prediction-based virtual decomposition control method (RMP-VDC) as a modification of the VDC using the model predictive control (MPC) to offer a practical solution for the real system control problem. The proposed method deals with uncertainties and external forces, as well as constraint matters, for complex nonlinear robot manipulators. By modifying the ideas from the VDC with MPC techniques, the time-varying state feedback control law for the ancillary controller is provided. The proposed method benefits from the introduction of a prediction horizon, which induces robustness and increases accuracy. The constrained optimization problem is analytically solved online by the continuous linearization of the nonlinear model and by employing the active set method. To validate the proposed controller, we performed the implementation on a real 7-degrees-of-freedom upper body exoskeleton robot, and the results were compared with those obtained using the adaptive VDC. The experimental results revealed increased accuracy for the proposed RMP-VDC in dealing with model uncertainties and interaction forces between humans and exoskeleton robots.acceptedVersionPeer reviewe

Hydraulisen puomin voimatakaisinkytketty etäohjaus

Teleoperation has been under study from the mid 1940s, when the first mechanical master-slave manipulators were built to allow safe handling of nuclear material within a hot cell. Since then, need to operate within dangerous, out of reach, uncomfortable, or hazardous environments has then motivated researchers to study teleoperation further. In this thesis, teleoperation of a hydraulic manipulator with electrically driven master manipulator was studied. The workspace of the hydraulic slave manipulator is 5 m in height and it can reach 3 m. The master manipulator has a workspace approximating full arm movement pivoting at the shoulder. Further, the slave manipulator is capable of lifting over 1000 kg, while the master manipulator can lift only 2 kg. Objective of this thesis is to implement virtual decomposition control (VDC) type controller to the master manipulator and create communication channel for the two manipulators. The VDC approach is a subsystem model based feedforward controller. Similar controller for the slave manipulator has been implemented previously. Performance of the developed teleoperation system will be evaluated with experimental implementation measuring the free space motion tracking in two degrees of freedom motion. Results from the experimental implementation indicate accurate motion tracking between the two manipulators. Experimental results indicate less than 15 mm position error between the two manipulators, which considering the size of the HIAB can be considered promising

Virtual Decomposition Control of a Hydraulic Manipulator

The controller design and modelling of hydraulically driven robots is a challenging task. This comes inter alia due to inherent nonlinear dynamics associated with hydraulic actuators, highly nonlinear characteristic of the robot dynamics and various uncertainties and disturbances of mathematical models. In this master’s thesis a new control theory, namely Virtual Decomposition Control (VDC), is studied. The VDC approach is developed especially for precision control of complex robots. In VDC approach the robotic system to be controlled is first virtually decomposed into subsystems. Then, the subsystems dynamics based control can be applied, to make each subsystem qualified to be virtually stable. Finally, the virtual stability of every subsystem results in the stability and convergence of entire robot. An effectiveness of this approach comes from the fact that no matter how complicated a robotic system is the dynamics of the subsystems remain relatively simple with fixed dynamic structures invariant to target systems. The purpose of this thesis was to study and implement VDC into hydraulic 2-DOF manipulator actuated with hydraulic cylinders. The parameter adaptation for uncertain parameters was not studied in scope of this thesis. The objective of this thesis was also test performance of VDC-controller in practice and compare achieved results to corresponding PID-controller results. The theory of VDC approach was successfully applied into studied manipulator and the L_2 and L_∞ stability of subsystems were mathematically guaranteed leading to stability of entire system. In experimental measurements certain Cartesian motion trajectory was driven with both VDC- and PID-controller. With VDC- controller roughly 7 times better piston position tracking performance was achieved for first cylinder and about 4.4 times better performance for second cylinder was achieved. Moreover, the very same Cartesian motion trajectory was driven with twice faster and half slower execution times. The stability of PID-controller was lost in both of these cases, whereas VDC-controller managed to drive these trajectories without problems

Nonlinear control of a seven degrees-of-freedom exoskeleton robot arm

Advances in the field of robotics have allowed increasingly integrating robotic devices for rehabilitation of physical disabilities. This research work is encompassed into the field of rehabilitation robotics; it presents the development of the robot ETS-MARSE, a seven degrees-of-freedom exoskeleton designed to be worn in the human arm. The developments include the study and implementation of a relatively novel nonlinear control approach, as well as different rehabilitation schemes. One of the characteristics of a rehabilitation robot is that it deals with a wide number of patients that have different biomechanical and physiological conditions. The implementation of the nonlinear control technique known as Virtual Decomposition Control addresses this issue with its internal parameters’ adaptation that presents a robust behavior to different characteristics of the robot users. Besides, this technique simplifies the complexity of high degree-of-freedom robots by its innovative sub-systems decomposition. All of above, while ensuring the system asymptotic stability and excellent trajectory tracking. Between the different rehabilitation schemes, we can mention: passive, active-assistive and active rehabilitation. The first one follows predefined trajectories and relies on the efficiency of the controller. The two other schemes require understanding the user’s intention of movement and take an action in order to guide, restrain, correct or follow it. For this purpose, we present an approach that utilizes a force sensor as the human-robot interface in order to transform, via an admittance function, the forces that the user exert to the robot end-effector (handle), and execute active-assisted or active rehabilitation. Finally among the main developments of this work, an approach is presented in which the need of a force sensor to perform some active rehabilitation tasks is removed. By means of a nonlinear observer, the interaction forces are estimated and the user’s intention of movement followed. Experimental results show the effectiveness of all the proposed approaches. All the tests involving humans were tested with healthy subjects. Trajectory tracking of the robot is executed in joint space; some trajectories are given in Cartesian space and transformed to joint space by means of the pseudoinverse of the Jacobian technique. However this option is limited; a mandatory next step to improve many functionalities of the robot is to solve its inverse kinematics. Between other progresses that are in development, is an approach to process electromyographic signals in order to obtain information from the robot’s users. First results on this methodology are presented. Teleoperation and haptic capabilities are also in the initial stage of development

Nonlinear control of multiple mobile manipulator robots transporting a rigid object in coordination

This doctoral thesis proposes and validates experimentally nonlinear control strategies for a group of mobile manipulator robots transporting a rigid object in coordination. This developed approach ensures trajectory tracking in Cartesian space in the presence of parameter uncertainty and undesirable disturbances. The objective of the creation of robots in the early sixties was to relieve man of certain hard jobs such as: handling a heavy object, and repetitive tasks which are often tiring or even sometimes infeasible manually. Following this situation, several types of manipulator robots were created. Naturally, the need for robots having both locomotion and manipulation capabilities has led to the creation of the mobile manipulators. Typical examples of mobile manipulators, more or less automated, are the cranes mounted on trucks , the satellite arms, the deep-sea exploration submarines, or extra-planetary exploration vehicles. Some operations requiring the handling of a heavy object are difficult to achieve by a single mobile manipulator. These operations require a coordination of several mobile manipulators to move or transport a heavy object in common. However, this complicates the robotic system as its control design complexity increases greatly. The problem of controlling the mechanical system forming a closed kinematic chain mechanism lies in the fact that it imposes a set of kinematic constraints on the coordination of the position and velocity of the mobile manipulator. Therefore, there is a reduction in the degrees of freedom for the entire system. Further, the internal forces of the object produced by all mobile manipulators should be controlled. This thesis work was focused on developing a consistent control technique for a group of mobile manipulator robots executing a task in coordination. Different nonlinear controllers were simulated and experimentally applied to multiple mobile manipulator system transporting a rigid object in coordination. To achieve all objectives of this thesis, as a first step, an experimental platform was developed and mounted in the laboratory of GREPCI-ETS to implement and validate the different designed control laws. In the second step, several adaptive coordinated motion/force tracking control laws were applied, ensuring that the desired trajectory can excellently tracked under uncertainties parameters and disturbances