Adaptive Nonlinear PD Controller of Two-Wheeled Self-Balancing Robot with External Force

This paper proposes an adaptive nonlinear proportional-derivative(ANPD)controller for a two-wheeled self-balancing robot(TWSB)modeled by the Lagrange equation with external forces.The proposed control scheme is designed based on the combination of a nonlinear proportional-derivative(NPD)controller and a genetic algorithm,in which the proportional-derivative(PD)parameters are updated online based on the tracking error and the preset error threshold.In addition,the genetic algorithm is employed to adaptively select initial controller parameters,contributing to system stability and improved control accuracy.The proposed controller is basic in design yet simple to implement.The ANPD controller has the advantage of being computationally lightweight and providing high robustness against external forces.The stability of the closed-loop system is rigorously analyzed and verified using Lyapunov theory,providing theoretical assurance of its robustness.Simulations and experimental results show that the TWSB robot with the proposed ANPD controller achieves quick balance and tracks target values with very small errors,demonstrating the effectiveness and performance of the proposed controller.The proposed ANPD controller demonstrates significant improvements in balancing and tracking performance for two-wheeled self-balancing robots,which has great applicability in the field of robot control systems.This represents a promising solution for applications requiring precise and stable motion control under varying external conditions.

A Closed-Loop Dynamic Controller for Active Vibration Isolation Working on A Parallel Wheel-Legged Robot

Serving the Stewart mechanism as a wheel-legged structure,the most outstanding superiority of the proposed wheel-legged hybrid robot(WLHR)is the active vibration isolation function during rolling on rugged terrain.However,it is difficult to obtain its precise dynamic model,because of the nonlinearity and uncertainty of the heavy robot.This paper presents a dynamic control framework with a decentralized structure for single wheel-leg,position tracking based on model predictive control(MPC)and adaptive impedance module from inside to outside.Through the Newton-Euler dynamic model of the Stewart mechanism,the controller first creates a predictive model by combining Newton-Raphson iteration of forward kinematic and inverse kinematic calculation of Stewart.The actuating force naturally enables each strut to stretch and retract,thereby realizing six degrees-of-freedom(6-DOFs)position-tracking for Stewart wheel-leg.The adaptive impedance control in the outermost loop adjusts environmental impedance parameters by current position and force feedback of wheel-leg along Z-axis.This adjustment allows the robot to adequately control the desired support force tracking,isolating the robot body from vibration that is generated from unknown terrain.The availability of the proposed control methodology on a physical prototype is demonstrated by tracking a Bezier curve and active vibration isolation while the robot is rolling on decelerate strips.By comparing the proportional and integral(PI)and constant impedance controllers,better performance of the proposed algorithm was operated and evaluated through displacement and force sensors internally-installed in each cylinder,as well as an inertial measurement unit(IMU)mounted on the robot body.The proposed algorithm structure significantly enhances the control accuracy and vibration isolation capacity of parallel wheel-legged robot.

The Modeling Strategies for Open Software Architecture of Robot Controller

Although the modeling technologies for open robot controllers have been discussed widely, not much literature is devoted to the actual general modeling principles and strategies. The reason is that many researches focus on specific application fields. This paper accommodates for this lacuna and provides some general modeling principles and strategies. At last, the actual new modeling method Hierarchical Object Oriented Petri net (HOONet) which has been proved to be an effective modeling methodology, is used to illustrate the modeling strategies.

Modeling Open Software Architectures of Robot Controllers: A Brief Survey of Modeling Methods and Developing Methods

Openness is one of the features of modern robot controllers. Although many modeling technologies have been discussed to model and develop open robot controllers, the focus is always on modeling methodology. The relation between the former and the latter is usually ignored. According to the general software architecture of open robot controllers, this paper discusses modeling and developing methods. And the relation between the typical ones is analyzed.

A Back-stepping Based Trajectory Tracking Controller for a Non-chained Nonholonomic Spherical Robot

Spherical robot has good static and dynamic stability, which provides it with strong viability in hostile environment, but the lack of effective control methods has hindered its application and development. This article deals with the dynamic trajectory tracking problem of the spherical robot BHQ-2 designed for unmanned environment exploration. The dynamic model of the spherical robot is established with a simplified Boltzmann-Hamel equation, based on which a trajectory tracking controller is designed by using the back-stepping method. The convergence of the controller is proved with the Lyapunov stability theory. Numerical simulations show that with the controller the robot can globally and asymptotically track desired trajectories, both linear and circular.

Kinematics/Fuzzy Logic Combined Controller for Formation Control of Mobile Robots

A kinematics and fuzzy logic combined formation controller was proposed for leader-follower based formation control using backstepping method in order to accommodate the dynamics of the robot.The kinematics controller generates desired linear and angular velocities for follower robots,which make the configuration of follower robots coverage to the desired.The fuzzy logic controller takes dynamics of the leader and followers into consideration,which is built upon Mamdani fuzzy model.The force and torque acting on robots are described as linguistic variables and also 25 if-then rules are designed.In addition,the fuzzy logic controller adopts the Centroid of Area method as defuzzification strategy and makes robots’actual velocities converge to the expected which is generated by the kinematics controller.The innovation of the kinematics and fuzzy logic combined formation controller presented in the paper is that the perfect velocity tracking assumption is removed and realtime performance of the system is improved.Compared with traditional torque-computed controller,the velocity error convergence time in case of the proposed method is shorter than traditional torque-computed controller.The simulation results validate that the proposed controller can drive robot members to form the desired formation and formation tracking errors which can coverage to a neighborhood of the origin.Additionally,the simulations also show that the proposed method has better velocity convergence performance than traditional torque-computed method.

Metaheuristics Algorithm for Tuning of PID Controller of Mobile Robot System

Robots in the medical industry are becoming more common in daily life because of various advantages such as quick response,less human interference,high dependability,improved hygiene,and reduced aging effects.That is why,in recent years,robotic aid has emerged as a blossoming solution to many challenges in the medical industry.In this manuscript,meta-heuristics(MH)algorithms,specifically the Firefly Algorithm(FF)and Genetic Algorithm(GA),are applied to tune PID controller constraints such as Proportional gain Kp Integral gain Ki and Derivative gain Kd.The controller is used to control Mobile Robot System(MRS)at the required set point.The FF arrangements are made based on various pre-analysis.A detailed simulation study indicates that the proposed PID controller tuned with Firefly Algorithm(FF-PID)for MRSis beneficial and suitable to achieve desired closed-loop system response.The FF is touted as providing an easy,reliable,and efficient tuning technique for PID controllers.The most suitable ideal performance is accomplished with FF-PID,according to the display in the time response.Further,the observed response is compared to those received by applying GA and conventional off-line tuning techniques.The comparison of all tuning methods exhibits supremacy of FF-PID tuning of the given nonlinear Mobile Robot System than GA-PID tuning and conventional controller.

Development of a Multi-DOF Robotic Controller for Academic Purposes

This article presents the development of a robotic controller for technical training, academic teaching, and research. The controller was designed to interact from 1 to 6 DOF （degrees of freedom） serial robotic arms, actuated by brushed DC （direct current） servomotors equipped with incremental encoders. Controller architecture is based on four components： a processor, a reconfigurable FPGA （field-programmable gate array）, measurement I/O hardware and software. Functionality of the robotic controller has been proved by means of the interaction with an SCARA （selective compliance assembly robot arm）. The proposed controller presents the potential to teach technical courses （like robotics, control, electronics and programming） and to implement and validate advanced control algorithms.

Trajectory tracking control based on linear active disturbance rejection controller for 6-DOF robot manipulator

The trajectory tracking control for a 6-DOF robot manipulator with multiple inputs and outputs,non-linearity and strong coupling is studied.Firstly,a dynamical model for the 6-DOF robot manipulator is designed.From the view point of practical engineering,considering the model uncertainties and external disturbances,the robot manipulator is divided into 6 independent joint subsystems,and a linear active disturbance rejection controller(LADRC)is developed to track trajectory for each subsystem respectively.LADRC has few parameters that are easy to be adjusted in engineering.Linear expansion state observer(LESO)as the uncertainty observer is able to estimate the general uncertainties effectively.Eventually,the validity and robustness of the proposed method adopted in 6-DOF robot manipulator are demonstrated via numerical simulations and 6-DOF robot manipulator experiments,which is of practical value in engineering application.

Wall Follower Autonomous Robot Development Applying Fuzzy Incremental Controller

This paper presents the design of an autonomous robot as a basic development of an intelligent wheeled mobile robot for air duct or corridor cleaning. The robot navigation is based on wall following algorithm. The robot is controlled using fuzzy incremental controller (FIC) and embedded in PIC18F4550 microcontroller. FIC guides the robot to move along a wall in a desired direction by maintaining a constant distance to the wall. Two ultrasonic sensors are installed in the left side of the robot to sense the wall distance. The signals from these sensors are fed to FIC that then used to determine the speed control of two DC motors. The robot movement is obtained through differentiating the speed of these two motors. The experimental results show that FIC is successfully controlling the robot to follow the wall as a guidance line and has good performance compare with PID controller.

Design of trotting controller for the position-controlled quadruped robot

This work presents a controller designed for position-controlled quadrupedal dynamic locomotion,aiming at simple and robust trotting control. The controller takes the torso attitude angles and velocities into planning foot trajectories. Firstly design of the servo motor actuated quadruped robot is introduced and the kinematic equations are deduced. Then a scheme is presented for controlling the robot torso attitude based on the virtual leg model. Furthermore,it demonstrates the design of the controller which enables the robot to have a wide range of trotting gaits and omni-directional motions. Finally,results of robust trotting in various speeds,path tracking and push recovery in simulation are reported,and results of trotting on real quadruped robots will be studied.

Implementation of a new PC based controller for a PUMA robot

This paper describes the replacement of a controller for a programmable universal machine for assembly (PUMA) 512 robot with a newly designed PC based (open architecture) controller employing a real-time direct control of six joints. The original structure of the PUMA robot is retained. The hardware of the new controller includes such in-house designed parts as pulse width modulation (PWM) amplifiers, digital and analog controllers, I/O cards, signal conditioner cards, and 16-bit A/D and D/A boards. An Intel Pentium IV industrial computer is used as the central controller. The control software is implemented using VC++ programming language. The trajectory tracking performance of all six joints is tested at varying velocities. Experimental results show that it is feasible to implement the suggested open architecture platform for PUMA 500 series robots through the software routines running on a PC. By assembling controller from off-the-shell hardware and software components, the benefits of reduced and improved robustness have been realized.

Design of Industrial Robotic Controller Based on DSP

This paper describes the design of industrial robot controller based on the DSP technology. Robotic real time control is realized by PC and DSP motion control card and this method improves the performance of robotic controller. Finally this paper gives some experiment results and conclusion.

Design and implementation of information acquisition system architecture for multi-sensor robots

A multi-layer controller architecture based on digital signal processor （DSP） and on-chip MCU was proposed for multi-sensor information acquisition system; it consisted of a data acquisition unit and a data fusion unit, and used a host controller to connect the two units into an integrated system. Compared with architectures of traditional acquisition system, this architecture had good openness and good adaptability of algorithms in hardware. To validate its feasibility, a small-scale prototype was cleverly designed, which adopted ADμCS12, TMS320F206 and 89C51 as controllers, and had 16-channel ADC and 12- channel DAC with high accuracy of 12-bit. The interfaces between different controllers were introduced in detail. Some basic parameters of the prototype were presented by board-level tests and by comparison with other two systems. The prototype was employed to provide on-line state measurement, parameter estimation and decision-making for trajectory tracking of wheeled mobile robot. Experimental results show that the prototype achieves the goals of data acquisition, fusion and control perfectly.

Modeling a Controller for an Articulated Robotic Arm

The precise control upon each degree of freedom of a robotic arm is a great challenge in implementing industrial work. This paper aims to design a novel controller for an automated robotic arm. A discrete Proportional Integral Derivative (PID) control technique is being used to replace the complex electronic circuitry, which would greatly reduce the cost and size of the controller. DC motors will be controlled on the basis of Closed-loop System using an avr (Atmega 16/32) microcontroller. Transfer functions have been derived for mathematical modeling of the system through which the stability of the system can be evaluated prior to fabrication.

Improved hybrid position/force controller design of a flexible robot manipulator using a sliding observer

An improved hybrid position/force controller design of a flexible robot manipulator is presented using a sliding observer. The friction between the end effector and the environment is considered and compensated. For systematic reasons the controller is designed taking into consideration the rigid link subsystems and the flexible joints. The proposed control system satisfies the stability of the two subsystems and copes with the uncertainty of robot dynamics. A sliding observer is designed to estimate the time derivative of the torque applied as input to the rigid part of the robot. For the stability of the observer, it is assumed that the uncertainty of the observed system is bounded. A MRAC algorithm is used for the estimation of the friction forces at the contact point between the end effector and the environment. Finally simulation and experimental results are given, to demonstrate the effectiveness of the proposed controller.

Improved single-neuron PID controller for DC motor applied in robot system

An improved single-neuron proportional integral derivative （ PID ） controller and a new method to build the DC motor system were presented in the article. In the simulation, the robot arm is considered as an external load to DC motor. Both the motor module and the load module are crea- ted in Simulink to achieve simulation results closer to real robot system. In this way, it can well veri- fy the performance of the improved single-neuron PID controller, which is a combined controller of normal PID controller and single-neuron PID controller. Besides, an intelligent switcher can help to realize the function of choosing a better control algorithm according to motor＇ s velocity output. Sim- ulated results confirm the rapid and stable response of the improved PID controller. Moreover, the improved single-neuron PID controller has an excellent ability to overcome the load impact and su- press the jamming signals. At last, a GUI interface platform is built to make the controller easier to be applied in other robot systems.

A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.

An Adaptive Fuzzy Controller for Trajectory Tracking of Robot Manipulator

In this paper, an adaptive fuzzy control algorithm is proposed for trajectory tracking of an n-DOF robot manipulator subjected to parametric uncertainty and it is advantageous compared to the conventional nonlinear saturation controller. The asymptotic stability of the proposed controller has been derived based on Lyapunaov energy function. The design procedure is straightforward due to its simple fuzzy rules and control strategies. The simulation results show that the present control strategy effectively reduces the control effort with negligible chattering in control torque signals in comparison to the existing nonlinear saturation controller.

Tracking controller for robot manipulators viac omposite nonlinear feedback law

A composite nonlinear feedback tracking controller for motion control of robot manipulators is described. The structure of the controller is composed of a composite nonlinear feedback law plus full robot nonlinear dynamics compensation. The stability is carried out in the presence of friction. The controller takes advantage of varying damping ratios induced by the composite nonlinear feedback control, so the transient performance of the closed-loop is remarkably improved. Simulation results demonstrate the feasibility of the proposed method.