Rigid-link Electrically-driven Robot Research Articles

Task-space regulation of rigid-link electrically-driven robots with uncertain kinematics using neural networks

Extensive research efforts have been made to address the motion control of rigid-link electrically-driven (RLED) robots in literature. However, most existing results were designed in joint space and need to be converted to task space as more and more control tasks are defined in their operational space. In this work, the direct task-space regulation of RLED robots with uncertain kinematics is studied by using neural networks (NN) technique. Radial basis function (RBF) neural networks are used to estimate complicated and calibration heavy robot kinematics and dynamics. The NN weights are updated on-line through two adaptation laws without the necessity of off-line training. Compared with most existing NN-based robot control results, the novelty of the proposed method lies in that asymptotic stability of the overall system can be achieved instead of just uniformly ultimately bounded (UUB) stability. Moreover, the proposed control method can tolerate not only the actuator dynamics uncertainty but also the uncertainty in robot kinematics by adopting an adaptive Jacobian matrix. The asymptotic stability of the overall system is proven rigorously through Lyapunov analysis. Numerical studies have been carried out to verify efficiency of the proposed method.

Adaptive Sliding Mode Control of a 6-DOF RLED Robot Manipulator with Uncertain Parameters and External Disturbances

This paper addresses the end-effector position and orientation tracking problem of a 6-degrees of freedom (DOF) rigid link electrically driven (RLED) revolute joint serial robot manipulator with uncertain parameters and external disturbances. System uncertainties and external disturbances are bounded but their upper limits are unknown. The input matrix, which is always invertible and not necessarily a diagonal matrix, is also assumed to be uncertain with a certain bound. An adaptive sliding mode control (ASMC) is designed to solve the tracking problem given these uncertainties. Note that the designed control method can be applied to any RLED serial robot manipulator. No regression matrices are required and the uncertainty upper limits are not necessarily known. Furthermore, the controller computation time can be reduced by considering some parts of the system dynamics and the nth time-derivative reference signals of nth order system, in this case desired joint jerk signals, as unknown bounded uncertainties. The desired trajectory is defined in operational space while the designed ASMC works in joint space. The methods to convert the end-effector pose, velocity, acceleration, and jerk from operational space to joint space are also explained. The Lyapunov stability criterion is applied to prove the convergence of the adaptive gain of ASMC, the sliding surface, and system stability. Finally, simulation results verified ASMC performance.

Adaptive neural network algorithm for control design of rigid-link electrically driven robots

In this article, an adaptive neural network algorithm is developed for control issue of rigid-link electrically-driven (RLED) robot systems. First, an virtual control algorithm is designed to deal with the mechanical dynamics. Next, an actual neural network controller is used to handle the uncertainty in the mechanical and electrical dynamics. The stability is guaranteed by using a rigid stability proof. Finally, a simulation is given to show the effectiveness of the proposed algorithm.

Lyapunov recursive design of robust adaptive tracking control with L 2-gain performance for electrically-driven robot manipulators

This paper develops a new Lyapunov recursive design for the tracking control problem of rigid-link electrically-driven robot manipulators with uncertainty by taking a tracking performance into account. The tracking performance is evaluated by L 2-gain from a torque level disturbance signal to a penalty signal for the tracking error between outputs of the manipulator and desired trajectories. The novelty of our approach is in the strategy to construct such a Lyapunov function recursively that ensures not only stability of a tracking error system but also an L 2-gain constraint, which provides a closed-form solution for non-linear H

Comments on "Redesign of hybrid adaptive/robust motion control of rigid-link electrically-driven robot manipulators"

The original paper of Su and Stepanenko (ibid., vol.14, p.651-5, 1998) presents the design of an adaptive/robust controller for uncertain electrically-driven robots with no velocity measurements. This note shows that the claim that velocity measurements are not required for control implementation is incorrect.

A near output feedback controller for a general class of robot manipulator systems

In this paper, we propose a robust near output feedback (which refers to the fact that the control scheme uses dynamic feedback of the output but requires knowledge of the initial conditions of other states) link position tracking controller for a class of robotic systems, which includes the rigid-link flexible-joint (RLFJ) robot manipulator and the rigid-link electrically-driven (RLED) robot. The method uses a bank of dynamic filters, with the link position tracking error as the input, to generate surrogates for the unmeasurable system states. One of these generated filter states is then used in the feedback control strategy. The method is distinguished from previous results by the limited amount of modelling information required, the utilization of only link position measurements and knowledge of the initial conditions, and the overall simplicity of the controller. Even though the approach only requires link position measurements and knowledge of initial conditions, the controller exhibits good robustness properties while ensuring semiglobal uniformly ultimately bounded link position tracking.

Robust neural-network control of rigid-link electrically driven robots

A robust neural-network (NN) controller is proposed for the motion control of rigid-link electrically driven (RLED) robots. Two-layer NN's are used to approximate two very complicated nonlinear functions. The main advantage of our approach is that the NN weights are tuned on-line, with no off-line learning phase required. Most importantly, we can guarantee the uniformly ultimately bounded (UUB) stability of tracking errors and NN weights. When compared with standard adaptive robot controllers, we do not require lengthy and tedious preliminary analysis to determine a regression matrix. The controller can be regarded as a universal reusable controller because the same controller can be applied to any type of RLED robots without any modifications.

Redesign of hybrid adaptive/robust motion control of rigid-link electrically-driven robot manipulators

In Su and Stepanenko (1995), a hybrid adaptive controller for rigid-link electrically-driven robot manipulators was proposed. Semi-global asymptotic stability of the controller was established in the Lyapunov sense. However, there are two limitations in it. One is that the controller requires the joint velocity measurements, that with the required accuracy can be difficult to realize in practical applications. The other one assumes the boundedness of estimated inertia parameters of the manipulator in order to reduce the computation complexity. In this paper, we propose a modification of the hybrid adaptive controller, which eliminate the above-mentioned limitations. Hence the range of applicability of the method in the above article can be greatly broadened. The capabilities of the proposed control strategies are illustrated through computer simulation.

A hybrid learning/adaptive partial state feedback controller for RLED robot manipulators

In this paper, we present an adaptive partial state-feedback repetitive learning control algorithm for a rigid-link electrically-driven (RLED) robot manipulator actuated by brushed DC (BDC) motors. The proposed controller is designed to compensate for repeatable mechanical uncertainty via a learning control term while an adaptive control loop is used to compensate for parametric uncertainty in the electrical dynamics. The proposed controller guarantees semi-global asymptotic link position tracking while only requiring measurements of link position and electrical winding current (e.g. measurements of link velocity are not required).

An adaptive partial state-feedback controller for RLED robot manipulators

An adaptive partial state-feedback controller is designed for rigid-link electrically driven (RLED) robot manipulators. The controller is based on structural knowledge of the electromechanical dynamics of the RLED robot and measurements of link position and electrical winding current in each of the brushed DC link actuators. The proposed controller is designed to adapt for parametric uncertainty in the electromechanical dynamics while utilizing a dynamic filter to generate link velocity tracking error information. The controller, adaptation laws, and the pseudovelocity filter are designed via a Lyapunov-like approach, the benefit of which is that at the end of the design procedure the controller can be mathematically shown to produce semiglobal asymptotic link position tracking. The basic design approach can be extended to many types of multiphase motors.

Hybrid adaptive/robust motion control of rigid-link electrically-driven robot manipulators

In this paper a hybrid adaptive/robust control scheme is proposed for rigid-link electrically-driven robot manipulators in the presence of arbitrary uncertain inertia parameters of the manipulator and the electrical parameters of the actuators. In contrast to the known methods, the presented design requires at most the joint velocity feedback and does not rely on the knowledge of the bounds of complexity functions. Semi-global asymptotic stability of the adaptive/robust controller is established in the Lyapunov sense. Simulation results are included to demonstrate the tracking performance.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Position and force tracking control of rigid-link electrically-driven robots

This paper introduces a framework for the design of tracking controllers for rigid-link electrically-driven (RLED) robot manipulators operating under constrained and unconstrained conditions. We present an intuitive nonlinear control strategy that can easily be reformulated for robots performing high precision tasks. The main emphasis is placed on the development of controllers that incorporate both motion in freespace and under constrained conditions. Another novelty is the combined treatment of force control and compensation for actuator dynamics. Based on models of the robot dynamics and environmental constraints, a reduced order dynamic model is obtained for the mechanical subsystem with respect to a set of constraint variables. A design procedure for tracking controllers is then formulated for the reduced order manipulator dynamics and the DC actuator dynamics. This paper concentrates on the theoretical aspects of the problem and, hence, is based on exact knowledge of the entire system. However, we have illustrated recently in [1] that this assumption can be generously relaxed in the design of a robust controller following a similar procedure as discussed in this paper.

Hybrid adaptive control for the tracking of rigid-link electrically-driven robots

In this paper, we design a hybrid adaptive/robust tracking controller for rigid-link electrically-driven (RLED) robot manipulators. The controller is hybrid in the sense that an adaptive controller is used to compensate for parametric uncertainties in the rigid-link equation while an adaptive robust controller corrects for the typically ignored electrical actuator dynamics. That is, in spite of these detrimental uncertainties and effects, we are still able to ensure global asymptotic stability of the link position tracking error.

Tracking control of rigid-link electrically – driven robot manipulators

This paper illustrates a simple, hand-crafted approach which can be used to design tracking controllers for rigid-link electrically-driven (RLED) robot manipulators. The control methodology is intuitively simple since it is based on concepts readily identified by most control engineers. To illustrate the approach, we develop a corrective tracking controller for the RLED robot dynamics which yields global exponential stability for the link tracking error under the assumption of exact model knowledge. To compensate for the uncertainties in the rigid-link electrically-driven robot model, we then design a corrective robust tracking controller which yields global uniform ultimate bounded stability of the link tracking error. The proposed controller is robust with regard to parametric uncertainties and additive bounded disturbances while correcting for the typically ignored electrical actuator dynamics.