Active Disturbance Rejection Control Design Using the Optimization Algorithm for a Hydraulic Quadruped Robot

Abstract

To increase the robustness and control precision of a hydraulic quadruped robot and simultaneously enhance the dynamic and steady characteristic of the hydraulic system, an active disturbance rejection controller (ADRC) tuned using the Lévy-flight beetle antennae search algorithm (LBAS) was proposed. Moreover, the designed controller was used in the hydraulic quadruped robot to enhance the control performance and restrain the disturbances. The use of the Lévy-flight trajectory in the advanced algorithm can help increase the search speed and iteration accuracy. In the LBAS-ADRC, the parameter tuning method is adopted to develop the active disturbance rejection controller enhanced using the beetle antennae search algorithm. When implemented in the hydraulic quadruped robot, the LBAS-ADRC can ensure satisfactory dynamic characteristics and stability in the presence of external interference. In particular, in the proposed method, the ADRC parameter search problem is transformed to a sixteen-dimensional search problem, the solution of which is identified using the Lévy-flight beetle antennae search algorithm. Moreover, three different algorithms are implemented in the active disturbance rejection controller tuning problem to demonstrate the control performance of the proposed controller. The analysis results show that the proposed controller can achieve a small amplitude overshoot under complex and changeable environments.

Active Disturbance Rejection Control for Robot Manipulator

“…The ADRC is based on an extension of the system model with an additional and fictitious state variable, representing those elements of the system dynamics that the user does not include in the mathematical description of the plant. These virtual states (sum of internal and external disturbances, sometimes denoted as a total disturbance) are estimated online and used in the control loop to decouple the system from the actual perturbation acting on the plant (10) [34], [35], [36], [37], [38], [39] as…”

“…The principle in the ADRC has supported consists of the estimation and later cancellation of 𝑓. Assuming that 𝑓 is derivable, the (10) of the system can be represented in (11) as an extended state form [6], [10], [33], [34], [35], [36], [37], [38], [39], [40], [41].…”

“…The point on the reference path, nearest to point 𝑃 and part of the equivalent group, is given by: 𝑃 𝑟𝑒𝑓 = (𝑃 𝑥𝑟𝑒𝑓 , 𝑃 𝑦𝑟𝑒𝑓 ). The CPE graph shows the minimal distances between points 𝑃 and 𝑃 𝑟𝑒𝑓 for all samples of the actual path (26) [30], [33], [38], [51].…”

Tuning Method in the Implementation Fuzzy ADRC Controllers for a Mass-Spring-Damper System: An approach

“…The ADRC uses the tracking characteristics of the extracted differential signal to formulate the signal transition arrangement between the input and differential signals. When the signal response changes abruptly, the tracking differentiator (TD) can promptly provide the smooth signal as the input signal to the controlled system, thereby ensuring that a large overshoot due to the mutations is not incurred and the system stability is enhanced in [2].…”

A Quadruped Robot with Three-Dimensional Flexible Legs

“…Another design method is to use the spring to achieve joint flexibility, which provides shock absorption and reduces the bottom impact through the passive compliance of the spring [ 16 , 17 ]. Additionally, the spring and connecting rod can be used to make a flexible leg directly [ 18 , 19 , 20 ]. The spring is used as a joint damper [ 21 ].…”