Optimal Control Of Robotic Manipulators Research Articles

Optimal dimensioning of elastic-link manipulators regarding lifetime estimation

Resourceful operation and design of robots is key for sustainable industrial automation. This will be enabled by lightweight design along with time and energy optimal control of robotic manipulators. Design and control of such systems is intertwined as the control must take into account inherent mechanical compliance while the design must accommodate the dynamic requirements demanded by the control. As basis for such design optimization, a method for estimating the lifetime of elastic link robotic manipulators is presented. This is applied to the geometry optimization of flexible serial manipulators performing pick-and-place operations, where the optimization objective is a combination of overall weight and vibration amplitudes. The lifetime estimation draws from a fatigue analysis combining the rainflow counting algorithm and the method of critical cutting plane. Tresca hypothesis is used to formulate an equivalent stress, and linear damage accumulation is assumed. The final robot geometry is selected from a Pareto front as a tradeoff of lifetime and vibration characteristic. The method is illustrated for a three degrees of freedom articulated robotic manipulator.

ADP-Based H∞ Optimal Control of Robot Manipulators With Asymmetric Input Constraints and Disturbances

ADP-Based H_∞ Optimal Control of Robot Manipulators With Asymmetric Input Constraints and Disturbances

Min-Max Optimal Control of Robot Manipulators Affected by Sensor Faults.

This paper is concerned with the control law synthesis for robot manipulators, which guarantees that the effect of the sensor faults is kept under a permissible level, and ensures the stability of the closed-loop system. Based on Lyapunov's stability analysis, the conditions that enable the application of the simple bisection method in the optimization procedure were derived. The control law, with certain properties that make the construction of the Lyapunov function much easier-and, thus, the determination of stability conditions-was considered. Furthermore, the optimization problem was formulated as a class of problem in which minimization and maximization of the same performance criterion were simultaneously carried out. The algorithm proposed to solve the related zero-sum differential game was based on Newton's method with recursive matrix relations, in which the first- and second-order derivatives of the objective function are calculated using hyper-dual numbers. The results of this paper were evaluated in simulation on a robot manipulator with three degrees of freedom.

Minimum-time optimal control of robotic manipulators based on Hamel’s integrators

In this paper, we develop a framework of time optimization path planning for robotic manipulators surrounded by static obstacles. Our approach is based on the recursive dynamics method and Hamel’s integrators. We adopt the linear programming techniques to solve the problem of the collision avoidance expressed as state constraints. The resulting algorithm is simple to implement and the performance of this approach is demonstrated through two examples. Numerical results are shown to validate the efficiency of the proposed algorithm.

Embedded Optimal Control of Robot Manipulators with Passive Joints

This paper studies the optimal control problem for planar underactuated robot manipulators with two revolute joints and brakes at the unactuated joints in the presence of gravity. The presence of a brake at an unactuated joint gives rise to two operating modes for that joint: free and braked. As a consequence, there exist two operating modes for a robot manipulator with one unactuated joint and four operating modes for a manipulator with two unactuated joints. Since these systems can change dynamics, they can be regarded as switched dynamical systems. The optimal control problem for these systems is solved using the so-called embedding approach. The main advantages of this technique are that assumptions about the number of switches are not necessary, integer or binary variables do not have to be introduced to model switching decisions between modes, and the optimal switching times between modes are not unknowns of the optimal control problem. As a consequence, the resulting problem is a classical continuous optimal control problem. In this way, a general method for the solution of optimal control problems for switched dynamical systems is obtained. It is shown in this paper that it can deal with nonintegrable differential constraints.

Stochastic adaptive optimal control of under-actuated robots using neural networks

Stochastic adaptive optimal control of robotic manipulators with a passive joint which has neither an actuator nor a brake is investigated. Firstly, the under-actuated system is decomposed into two subsystems with the first n−1 joints subsystem fully actuated while the second one unactuated. Secondly, a reference model for the first subsystem is derived by using the Linear Quadratic Regulator (LQR) optimization approach which guarantees the motion tracking and achieves the minimized moving accelerations. Instead of leaving the unactuated joint dynamics uncontrolled, the reference trajectory for the last joint is designed to indirectly affect the movements such that the desired trajectory can be achieved. Radial Basis Function neural networks (RBFNNs) have been employed to design the adaptive reference control and to construct a reference trajectory generator for the last joint. The stability and the optimal tracking performance in finite time have been rigorously established by theoretic analysis. Simulation studies show the effectiveness of the proposed control approach.

The motion editor and high precision integration for optimal control of robot manipulators in dynamic structural systems

The paper presents the motion editor for the robotic movement in the study. The Motion Editor can edit all motions which we want to need. This method is easy when the beginners edit to motions of robots. And let them have interesting in robot control. This paper proposes two methods to edit movements. First, we edit the robot's movement in VB environment, and then we use the Motion Editor to make it. Finally, we compared merit and defect with two methods. Indeed, it is convenient when we use the Motion Editor.

Optimal control of robot manipulators with a new two-level gradient-based approach

In this paper, a new approach for optimal control of robot manipulators is presented. For this purpose, the system is considered as a two-level large-scale system where a gradient-based coordination strategy is used to coordinate the overall system. This is achieved within a decomposition–coordination framework, where the robot manipulator is first decomposed into several sub-systems at the first level, and then, the coordination is done at the second level. The solution is based on Interaction Prediction Principle, where in the first level, the optimization is done by a gradient method and in the second level, the coordination is done by a new method based on the gradient of interaction errors. This approach provides a new scheme for hierarchical control of robot manipulators with high degree of freedom.The results fairly illustrate the effectiveness of the proposed coordination strategy.

A dynamic programming approach to optimal control of robotic manipulators

A dynamic programming approach to optimal control of robotic manipulators

High precision integration for dynamic structural systems with holonomic constraints

This paper presents a high precision integration method for the dynamic response analysis of structures with holonomic constraints. A detail recursive scheme suitable for algebraic and differential equations (ADEs) which incorporates generalized forces is established. The matrix exponential involved in the scheme is calculated precisely using <TEX>$2^N$</TEX> algorithm. The Taylor expansions of the nonlinear term concerned with state variables of the structure and the generalized constraint forces of the ADEs are derived and consequently, their particular integrals are obtained. The accuracy and effectiveness of the present method is demonstrated by two numerical examples, a plane truss with circular slot at its tip point and a slewing flexible cantilever beam which is currently interesting in optimal control of robot manipulators.

Optimal control of robotic manipulators in the presence of obstacles

AbstractIn this article, the optimal control problem for (rigid) robotic manipulators in the presence of obstacles is considered. First, two methods for the modeling of obstacles are considered. Through these methods, closed‐form approximations of obstacles in terms of the generalized coordinates of the manipulator are obtained. These expressions are then used to formulate an optimal control problem with state space constraints. The resulting optimal control problem is then solved numerically.

Practical method for optimal control of robot manipulators. 1st Report. Control law and digital simulation.

Optimal control strategies are very useful in manipulation problems of robots. However, most optimal controls are highly sensitive to plant-parameter variations and disturbances because optimal controls try to pick up exact information from the mathematical models in order to realize the best performance. We recognize that difficulties are involved in exact modeling of plants and prevention of disturbances. Therefore, we need a optimal control method with low sensitivity. The ideas of closed-loop control system design using LQG/TR techniques (linear quadratic Gaussian control with transfer recovery) are discussed in this paper. We combine optimal controls and LQG/TR control into two-degrees-of-freedom control systems to reduce the sensitivities of optimal control strategies. In digital simulations, we obtained excellent results of a two-link manipulator in an optimal time control problem using our method. Some modeling errors and considerable disturbances are allowed in the method. Thus, we can realize good performances in practical manipulation problems using our method.

Optimal Trajectory Generation for Robotic Manipulators Using Dynamic Programming

The problem of optimal control of robotic manipulators is dealt with in two stages: (1) optimal trajectory planning, which is performed off-line and results in the prescription of the position and velocity of each link as a function of time along a “given” path and (2) on-line trajectory tracking, during which the manipulator is guided along the planned trajectory using a feedback control algorithm. In order to obtain a general trajectory planning algorithm which could account for various constraints and performance indices, the technique of dynamic programming is adopted. It is shown that for a given path, this problem is reduced to a search over the velocity of one moving manipulator link. The design of the algorithm for optimal trajectory planning and the relevant computational issues are discussed. Simulations are performed to test the effectiveness of this method. The use of this algorithm in conjunction with an on-line controller is also presented.

Optimal Control of Robotic Manipulators by a Software Servo Device

In recent years the advanced micro-electronics techniques are contributing to the progress of industrial robotic manipulators. Direct digital control of manipulators is one of the most promising applications of a new generation of computers. Improved control techniques are required for the digital control to attain a fine performance of manipulators. This paper proposes a software servo control system for linear quadratic optimal control with I-action (LQI control) for a good performance over a wide range of motions and payloads. The effectiveness of this control system is demonstrated in several simulations and experimental results.

Optimal control of robotic manipulators by a software servo device.

In recent year the advanced micro-electronics techniques leads to the progress of industrial robotic manipulators. Direct digital control of manipulators is one of the most promising applications of this new generation of computers. Improved control techniques are required for the digital control to attain a fine performance on manipulators. This paper proposes a software servo control system for linear quadratic optimal control with I-action (LQI control) for a good performance over a wide range of motion and payloads. The effectiveness of this control system is demonstrated in several simulation and experimental results.