Task Space Position Control of Slider-Crank Mechanisms Using Simple Tuning Techniques Without Linearization Methods

Abstract

In this work, a position control in task space for slider-crank mechanisms is presented. In order to apply linear controllers it is required to linearize the mechanism dynamics at an equilibrium point. However, complete dynamic knowledge is needed and the linearization technique gives an oversimplified model that affects the control performance. In this work, it is proposed a novel method to design task space controllers without using the complete knowledge of the mechanism dynamics and linearization methods. From the extended dynamic model of parallel robots, it can be seen that the end-effector (slider) dynamics is expressed as a linear system that can be used directly for the control design instead of the complete mechanism linear dynamics. The approach requires a minimal knowledge of the mechanism dynamics and avoids linearization methods. To verify our approach, it is used pole placement and sliding mode controllers whose gains are tuned according to the slider dynamics. A linear sensor is mounted at the slider to measure its position and avoids considering noise and disturbances at links before the slider. Simulations and experiments are presented to validate our approach using two kinds of slider-crank mechanisms.

Constant Speed Control of Slider-Crank Mechanisms: A Joint-Task Space Hybrid Control Approach

“…It has been shown in [33] that the slider dynamics can be expressed as a linear system with a disturbance as…”

“…Such heat is generated by the plastic deformation energy that transforms itself into heat. The heat generation rate, Q (W), is given by [36] Q = 1.68af 0.15 v 0.85 (33) where a is the depth of the cut, f is the feed rate and v is the cutting speed. The cutting temperature is given by [37] Θ = v 0.5 f 0.3 (34) There is a trade-off between increasing or decreasing the cutting speed.…”

“…Hence, the cutting stroke has a negative sign, i.e., z = −1. The slider dynamics [33] written as in ( 14) is…”

A Novel Tuning Method of PD With Gravity Compensation Controller for Robot Manipulators

“…Proportional-Derivative (PD) control is one of the simplest controllers for robot manipulators control [1], [2]. When the robot is not affected by gravitational terms then the PD controller guarantees global asymptotic stability (GAS) by choosing strictly positive gains [3], [4].…”

“…To satisfy the control objectives, it has been developed different control techniques, such as PID [7]- [9], sliding mode control (SMC) [10]- [12], neural networks [13], intelligent techniques [14], [15] or even linear controllers [2], [16]. Each algorithm is capable to compensate the gravitational term and robustify the control law.…”