Active disturbance rejection motion control of spherical robot with parameter tuning

Abstract

Purpose The characteristics of spherical robots, such as under-drive, non-holonomic constraints and strong coupling, make it difficult to establish its motion control model accurately. To improve the anti-interference performance of spherical robots in practical engineering, this paper proposes a spherical robot motion controller based on auto-disturbance rejection control (ADRC) with parameter tuning. Design/methodology/approach This paper considers the influences of the spherical shell, internal frame and pendulum on the movement of the spherical robot during the rotation to establish the multi-body dynamics model of the XK-I spherical robot. Due to the serious coupling problem of the dynamic model, the motion control state equation is constructed using linearization and decoupling. The XK-I spherical robot PSO-ADRC motion controller with parameter tuning function is designed by combining the state equation with the particle swarm optimization (PSO) algorithm. Finally, experiments are performed to evaluate the feasibility of PSO-ADRC in an actual case compared to ADRC, PSO-PID and PID. Findings By analyzing the required time to reach the expected value, the control stability and the fluctuation range of the standard deviation after reaching the expected value, the superiority of PSO-ADRC to ADRC, PSO-PID and PID is demonstrated in terms of the speed and anti-interference ability. Practical implications The proposed method can be applied to the robot control field. Originality/value A parameter-tuning method for auto-disturbance-rejection motion control of the spherical robot is proposed. According to the experimental results, the anti-interference ability of the spherical robot moving on uneven ground is improved. Therefore, it provides a foundation for the autonomous environmental monitoring of the spherical robot equipped with sensors.

Design and validation of a novel adaptive motion control for a pendulum spherical robot

“…( 16) can be rewritten as Eq. (20). Since the reference model is an ideal control system, ρ and η are ideal tuning parameters, and Eq.…”

“…( 20) is a desired control law. Additionally, since the error term is not included in the control law (20), it is challenging to eliminate the error by adjusting the parameters. Therefore, the actual control law of the XK-I robot's linear motion under complex road conditions is considered as follows:…”

“…(12). According to the method of [4, 8, 20], the XK-I SR’s rolling and steering motion control can be separated; that is, the driving force produced by a group of motors makes the XK-I move in a straight line. If the XK-I type needs steering motion during linear motion, it is only necessary to input control signals to another group of motors.…”

“…Tao T. et al [18] and Lin R. et al [19] proposed an ADRC-based motion controller for SRs moving on uneven ground, which enhanced their anti-interference capability. Liu M. et al [20] designed a motion controller (PSO-ADRC) that employs particle swarm optimization (PSO) to adjust the parameters , , , and in ADRC to enhance the SRs’ anti-interference efficiency in actual motion. However, the ADRC controller has many parameters where their tuning can considerably influence the SR’s motion control efficiency.…”

Extended state observer design with fractional order Bode’s ideal cut-off filter in a linear motor motion control system

“…18 ADRC has been used widely in many applications, such as motion control, fuel cell systems, robots, and medical devices. 19,20 There is a key component of ADRC, that is, ESO. Almost all kinds of uncertainties in control systems could be estimated by the ESO as a total disturbance, such as unknown disturbances, friction, and parameter variations.…”