This paper proposes a small structure of robust controller to control robotic arm's joints where exist some uncertainties and unmodelled dynamics. Robotic arm is widely used now in the era of Industry 4.0. Nevertheless, the cost for an industry to migrate from a conventional automatic machine to industrial robot still very high. This become a significant challenge to middle or small size industry. Development of a low cost industrial robotic arm can be one of good solutions for them. However, a low-cost manipulator can bring more uncertainties. There might be exist more unmodelled dynamic in a low-cost system. A good controller to overcome such uncertainties and unmodelled dynamics is robust controller. A low-cost robotic arm might use small or medium size embedded controller such as Arduino. Therefore, the control algorithm should be a small order of controller. The synthesized controller was tested using MATLAB and then implemented on the real hardware to control a robotic manipulator. Both the simulation and the experiment showed that the proposed controller performed satisfactory results. It can control the joint position to the desired position even in the presence of uncertainties such as unmodelled dynamics and variation of loads or manipulator poses.
This paper proposed a control algorithm that guarantees gait tracking performance for quadruped robots. During dynamic gait motion, such as trotting, the quadruped robot is unstable. In addition to uncertainties of parameters and unmodeled dynamics, the quadruped robot always faces some disturbances. The uncertainties and disturbances contribute significant perturbation to the dynamic gait motion control of the quadruped robot. Failing to track the gait pattern properly propagates instability to the whole system and can cause the robot to fall. To overcome the uncertainties and disturbances, structured specified mixed sensitivityH∞robust controller was proposed to control the quadruped robot legs’ joint angle positions. Before application to the real hardware, the proposed controller was tested on the quadruped robot’s leg planar dynamic model using MATLAB. The proposed controller can control the robot’s legs efficiently even under uncertainties from a set of model parameter variations. The robot was also able to maintain its stability even when it was tested under several terrain disturbances.
Purpose The purpose of this paper is to introduce a quadruped robot strategy to avoid tipping down because of side impact disturbance and a control algorithm that guarantees the strategy can be controlled stably even in the presence of disturbances or model uncertainties. Design/methodology/approach A quadruped robot was developed. Trot gait is applied so the quadruped can be modelled as a compass biped model. The algorithm to find a correct stepping position after an impact was developed. A particle swarm optimization-based structure-specified mixed sensitivity (H2/H∞) robust is applied to reach the stepping position. Findings By measuring the angle and speed of the side tipping after an impact disturbance, a point location for the robot to step or the foothold recovery point (FRP) was successfully generated. The proposed particle swarm optimization-based structure-specified mixed sensitivity H2/H∞ robust control also successfully brought the legs to the desired point. Practical implications A traditional H∞ controller synthesis usually results in a very high order of controller. This makes implementation on an embedded controller very difficult. The proposed controller is just a second-order controller but it can handle the uncertainties and disturbances that arise and guarantee that FRP can be reached. Originality/value The first contribution is the proposed low-order robust H2/H∞ controller so it is easy to be programmed on a small embedded system. The second is FRP, a stepping point for a quadruped robot after receiving side impact disturbance so the robot will not fall.
Gravity causes non-linearity in position control of an articulated industrial robotic arm. Especially for a joint position control of a robot's shoulder and elbow that works parallel with the gravity direction. To overcome the problem, Computed Torque Control algorithm was implemented. This algorithm linearized the feedback, so a regular linear Proportional Derivative controller can be implemented. The contribution of this research is to find an effective controller to control a heavy weight low-cost robotic arm link/body using low-cost controller such as Arduino. A Computed Torque Control was implemented to control the shoulder joint of an articulated robotic arm. This joint is the most affected joint by the gravity. It works along the vertical plane, and loaded by the rest of the arm and the robot's load. The proposed controller was compared to a Proportional Integral Derivative (PID) Controller and a Cascade PID Controller. The experiment showed that the Computed Torque Controller can control the position of the arm properly both in the direction along or against the gravity. A linear PID controller could not bring the arm to the set point when it moves against the gravity, but it works well when the arm moves in the opposite direction. A Cascade PID controller has an overshot when the arm moves along the gravity. But it works properly when it moves up against the gravity. A Computed Torque Control works well in both directions even in the presence of gravity force because it includes the gravity on its algorithm.
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