Robust Motion Control for Mobile Manipulator Using Resolved Acceleration and Proportional-Integral Active Force Control

A resolved acceleration control (RAC) and proportional-integral active force control (PIAFC) is proposed as an approach for the robust motion control of a mobile manipulator (MM) comprising a differentially driven wheeled mobile platform with a two-link planar arm mounted on top of the platform. The study emphasizes on the integrated kinematic and dynamic control strategy in which the RAC is used to manipulate the kinematic component while the PIAFC is implemented to compensate the dynamic effects including the bounded known/unknown disturbances and uncertainties. The effectivenss and robustness of the proposed scheme are investigated through a rigorous simulation study and later complemented with experimental results obtained through a number of experiments performed on a fully developed working prototype in a laboratory environment. A number of disturbances in the form of vibratory and impact forces are deliberately introduced into the system to evaluate the system performances. The investigation clearly demonstrates the extreme robustness feature of the proposed control scheme compared to other systems considered in the study

Intelligent active torque control for vibration reduction of a sprayer boom suspension system

The most usual way of protecting crop from diseases is by using chemical method whereby mixture of chemicals and water are sprayed onto crop via nozzles. These nozzles are located consistently along a boom structure oriented perpendicular to the direction of motion to cover large areas. The most important factor on spray distribution pattern is spray boom vibration. Thus, suspension control aims to attenuate the unwanted vibration and should provide improvements in term of distribution uniformity. In this study, a combination of passive and active suspension was considered to create superior performance. A passive suspension was employed to control undesired vertical motion of sprayer boom structure while the roll movement of spray boom was reduced via active suspension. The active suspension system of sprayer was implemented by applying robust active torque control (ATC) scheme that integrates artificial intelligence (AI) methods plus another feedback control technique utilizing proportional-integral-derivative (PID) control. The proposed control system basically comprises of two feedback control loops; an innermost loop for compensation of the disturbances using ATC strategy and an outermost loop for the computation of the desired torque for the actuator using a PID controller. Two AI methods employing artificial neural network (ANN) and iterative learning (IL) were proposed and utilized to compute the estimated inertial parameter of the system through the ATC loop. The research proposes two main control schemes; the first is a combination of ATC and ANN (ATCANN) while the other is ATC and IL (ATCAIL). The suspension system was first modeled and a number of farmland terrains were simulated as the main disturbance components to verify the robustness of the system and sprayer boom dynamic performance related to distribution uniformity. The simulation results both in frequency and time domains show the effectiveness of the proposed ATC schemes in reducing the disturbances and other loading conditions. The control schemes were further implemented experimentally on a developed laboratory spray boom suspension test rig

Application of active force control and iterative learning in a 5-link biped robot

This paper investigates the efficacy of the implementation of the conventional Proportional-Derivative (PD) controller and different Active Force Control (AFC) strategies to a 5-link biped robot through a series of simulation studies. The performance of the biped system is evaluated by making the biped walk on a horizontal flat surface, in which the locomotion is constrained within the sagittal plane. Initially, a classical PD controller has been used to control the biped robot. Then, a disturbance elimination method called Active Force Control ( AFC) schemes has been incorporated. The effectiveness and robustness of the AFC as "disturbance rejecter" has been examined when a conventional crude approximation (AFCCA), and an intelligent active force control scheme, which is known as Active Force Control and Iterative Learning (AFCAIL) are employed. It is found that for both of the AFC control schemes proposed, the system is robust and stable even under the influence of disturbances. An attractive feature of the AFCAIL scheme is that inertia matrix tuning becomes much easier and automatic without any degradation in the performan

Application of active force control and iterative learning in a 5-link biped robot

This paper investigates the efficacy of the implementation of the conventional Proportional-Derivative (PD) controller and different Active Force Control (AFC) strategies to a 5-link biped robot through a series of simulation studies. The performance of the biped system is evaluated by making the biped walk on a horizontal flat surface, in which the locomotion is constrained within the sagittal plane. Initially, a classical PD controller has been used to control the biped robot. Then, a disturbance elimination method called Active Force Control (AFC) schemes has been incorporated. The effectiveness and robustness of the AFC as �disturbance rejecter� has been examined when a conventional crude approximation (AFCCA), and an intelligent active force control scheme, which is known as Active Force Control and Iterative Learning (AFCAIL) are employed. It is found that for both of the AFC control schemes proposed, the system is robust and stable even under the influence of disturbances. An attractive feature of the AFCAIL scheme is that inertia matrix tuning becomes much easier and automatic without any degradation in the performance