Class Of Robot Manipulators Research Articles

Passivity-based filtering for networked semi-Markov robotic manipulators with mode-dependent quantization and event-triggered communication

In this article, the networked filtering problem for a class of robotic manipulators with semi-Markov type parameters is investigated under the passivity framework. In particular, the mode-dependent quantization and event-triggered communication scheme are both proposed for increasing the network transmission efficiency. Sufficient stability conditions are first derived by choosing mode-dependent Lyapunov–Krasovskii functionals. Then, the mode-dependent filter gains and the event-triggering parameters are further designed with the help of matrix convex optimization. In the end, a simulation example is provided such that the effectiveness of the proposed filtering method can be well demonstrated.

A Sliding Mode Control Using Brain Limbic System Control Strategy for a Robotic Manipulator

This paper presents a robust bio-inspired sliding mode control approach, designed to achieve a favourable tracking performance in a class of robotic manipulators with uncertainties. To this end, brain emotional learning-based intelligent control (BELBIC) is applied, to adaptively adjust the control input law in the sliding mode control. The combined form provides an adjustment of the control input law that effectively alleviates the chattering effects of the sliding mode control. Specifically, the online parameters computed from the parameter uncertainties and external disturbances help to improve the system robustness. The simulation results demonstrate that the proposed bio-inspired control strategy is very successful at tracking the given trajectories with less chattering as compared to both the conventional and fuzzy sling mode control schemes.

Robust Adaptive Tracking Control of a Class of Robot Manipulators with Model Uncertainties

A robust tracking controller for robot manipulators measuring only the angular positions and considering model uncertainties is presented. It is considered that the model is uncertain; that is, the system parameters, nonlinear terms, external perturbations, and the friction effects in each robot joint are considered unknown. The controller is composed by two parts, a linearizing-like control feedback and a high-gain estimator. The main idea is to lump the uncertain terms into a new state which represents the dynamics of the uncertainties. This new state is then estimated in order to be compensated. In this way the resulting controller is robust. A numerical example for a RR robot manipulator is provided, in order to corroborate the results.

A Filtered Repetitive Controller for a Class of Nonlinear Systems

In this note, a filtered repetitive controller (FRC) is designed to compensate for periodic disturbances in a class of nonlinear systems. First, a new model of periodic disturbances is proposed. By this model, the FRC is designed and the resulting closed-loop error dynamics are analyzed with the help of a Lyapunov-Krasovskii functional. Finally the method is applied to periodic disturbance rejection in a class of robotic manipulators. Compared with repetitive controllers, the FRC provides the flexibility to choose filter parameters to achieve a tradeoff between tracking performance and stability. More importantly, FRC can deal with small input delay while the corresponding RC cannot.

Some Estimates of Performance for PID-Like Control of Robotic Manipulators

A class of robotic manipulators having prismatic and revolute joints is considered. It is supposed that feedback control laws have proportional-integral-differential ( PID ) or PID -like forms. It ensures the astatism property of the closed-loop systems. The following results are presented and proved. There are simple inequalities for feedback gains ensuring exponential stability of a desired position under all initial deviations which are small enough. The stability domain can be estimated as well as the stability degree. Under a coordinated growth of coefficients, the stability region is enlarged but the stability degree goes down. The main properties of PID regulated system are not changed if a "dirty" derivatives are used instead of pure ones. PID regulators ensure the tracking with a bounded error under any desired movements which are changed slowly enough.

A two-level control strategy for robot manipulators

This paper deals with the hierarchical control of a class of robot manipulators. A two-level hierarchical control concept for robot manipulators is proposed. The controller is formulated based on a deterministic approach. In synthesizing the controller, it is assumed that the upper bounds on the nonlinearities, couplings and uncertainties present in the system are available. It is shown through computer simulations that the proposed control strategy is capable of withstanding the expected variations and uncertainties in the system, and will render the robot manipulator able to track a prescribed trajectory to within a small ultimate boundedness set.

Decentralized and Hierarchical Control of a Class of Robot Manipulators

This paper is concerned with the design of robust controllers for uncertain non-linear robot manipulators based on a deterministic approach. A decentralized tracking controller is presented in which the controller is designed for each subsystem based only on its local states. For the cases in which the interconnection functions between the subsystems are large, a two-level hierarchical control strategy is proposed. In designing the controllers, only the bounds on the system uncertainties are assumed to be known. It is shown theoretically and through computer simulations that the proposed controllers guarantee uniform ultimate boundedness of the error between the reference trajectory and the system output.

Tracking and force control for a class of robotic manipulators

The increasing utilization of robotic manipulators in industrial tasks, such as assembly, forming or shaping of surfaces, as well as the handling of hazardous materials depends greatly on available hybrid force and position control schemes. Since the robot as well as its environment are often subject to parameter uncertainties which can not be neglected, it is necessary to design controllers which are robust with respect to these uncertainties. In addition, the dynamics of the robot are nonlinear requiring consideration of nonlinear control concepts. Another aspect to be taken into account is the relative stiffness of the robot, the force sensor and the manipulated surface. That is, the behavior of the system normal to the surface is relatively stiff while that tangential to the surface is relatively free. Separation of the controller for these two directions is therefore indicated. We propose a controller design which accounts for this point of view and demonstrate its efficacy with respect to robustness and accuracy of position and force tracking by means of numerical simulations. The design is based on the control concept of [CORLESS, LEITMANN 1989]. The example, considered is a Manutecr3 robot with three degrees of freedom. In addition, we account for the dynamics of the actuator which also possesses three degrees of freedom. The considered parameter uncertainties are friction moments in the links, friction between the end effector and the manipulated object, as well as nonlinear dynamics which are difficult to characterize.

Decentralized adaptive control scheme for control of a multi-arm-type robot

This paper deals with the problem of decentralized stabilization for a class of unknown large-scale dynamic systems formed of interconnected subsystems under constant disturbances. A decentralized adaptive control scheme is proposed based on the Lyapunov direct method and a condition of asymptotic stability is derived. Then the decentralized adaptive control scheme is applied for a class of robot manipulators to track the desired trajectory as closely as possible despite a wide range of manipulator motions and parameter uncertainties of links and payload.