Two-link Robot Arm Research Articles

Fault Detection based on Orthotopic Set Membership Identification for Robot Manipulators

Abstract In this article a fault detection algorithm for capturing structural and/or sensor failures in robot manipulators is presented. The robot dynamics is linearizable with respect to a certain parameter. Using this linearizable representation, common faults in robot arms, such as failures of actuators or faulty sensor measurements, can be identified as variations encountered in the parameter vector. The proposed algorithm uses an Orthotopic Set Membership Identifier that defines the feasible parameter set and the parameters’ bounds, within which the Weighted Recursive Least Square parameter estimate resides. An Uncertainty Output Predictor that generates the future region of faultless system operation. A fault is detected, when one of the following criteria below is validated: a) the WRLS parameter estimate resides out of the parameters's bounds, b) there is a sudden increase in the volume of the feasible set and c) the system's output is not within the predicted interval. Simulation studies are offered to test this fault detection methodology, customized to a two-link robot arm.

Adaptive Fuzzy Control Based on Fuzzy Neural Network for Uncertain Nonlinear Systems

Abstract In this paper, an adaptive fuzzy controller based on fuzzy neural network is proposed for uncertain nonlinear systems. The main advantages are the simple design, no requirement of system model, and release of fixed universal range of fuzzy output. A fuzzy neural network is applied to on-line identify the control system and provide sufficient information of the adaptive laws for the proposed fuzzy controller. Finally, experimental results of a two-link robotic arm are given to verify the effectiveness of the proposed approach.

LMI-based stability design of fuzzy controller for nonlinear systems

The tracking control of nonlinear systems based on the fuzzy-model-based approach has been presented. A fuzzy controller was designed to drive the system states of the nonlinear system to follow those of a reference model. Stability conditions were derived to guarantee the system stability. The finding of the parameters of fuzzy controller was formulated as a generalised eigenvalue problem. An application example on applying the proposed approach to a two-link robot arm was given.

Liapunov stability for a fuzzy PID controlled flexible-joint manipulator

This paper presents Liapunov stability analyses for flexible-joint robotic manipulators controlled by a fuzzy proportional-integral-derivative (PID) controller that was developed by the present authors. This new fuzzy PID controller preserves the simple linear structure of its conventional counterpart yet enhances its self-tuning control capability, thereby significantly improving tracking control performance. This fuzzy PID controller is extended to a MIMO configuration for the multiple link robotic manipulator. Simulation results on a two-link flexible-joint robot arm are shown to demonstrate superior performance.

A GAIN SCHEDULING CONTROL OF NONLINEAR SYSTEMS ALONG A REFERENCE TRAJECTORY

This paper presents a gain scheduling control of a nonlinear system in which the reference trajectory is given in advance. Multiple frozen operating times are chosen on the reference trajectory and a linear time invariant model is obtained at each operating time. A linear parameter varying model is then constructed by interpolating the region between the neighbor frozen operating times. A gain scheduling state feedback law is designed by a linear matrix inequality formulation. The effectiveness is demonstrated in a numerical simulation of a tracking control of a two-link robot arm.

Residual vibration reduction control after catching a falling steel sphere by a two-link catching flexible robot arm

This study deals with the residual vibration reduction control after catching a falling steel sphere by a two-link catching flexible robot arm. The two-link catching flexible robot arm consists of a first rigid link, a second flexible link and a cup mounted to catch the falling steel sphere. The flexibility of the second flexible link is effectively utilized to reduce the shock owing to the contact between the falling steel sphere and the cup. Then, the equation of motion of the two-link catching flexible robot arm is obtained, and the cost function for the residual vibration reduction control after catching the falling steel sphere is defined as a function of the parameters of the second joint angular velocity profile. By making the contour map of the cost function, the optimal parameters of the second joint angular velocity profile is obtained. The residual vibration reduction control is implemented by the feedforward control based on the second joint angle trajectory with the optimal parameters. Furthermore, the numerical calculations and the experiments have been carried out, and it is confirmed that the residual vibrations of the second flexible link after catching the falling steel sphere can be extremely reduced.

A New Method for Adaptive Control of Non-Linear Plants Using Type-2 Fuzzy Logic and Neural Networks

We describe in this paper adaptive model-based control of non-linear plants using type-2 fuzzy logic and neural networks. First, the general concept of adaptive model-based control is described. Second, the use of type-2 fuzzy logic for adaptive control is described. Third, a neuro-fuzzy approach is proposed to learn the parameters of the fuzzy system for control. A specific non-linear plant was used to simulate the hybrid approach for adaptive control. The specific plant was also used as test bed in the experiments. The non-linear plant that was considered is the “Pendubot”, which is a non-linear plant similar to the two-link robot arm. The results of the type-2 fuzzy logic approach for control were good, both in accuracy and efficiency.

Optimal and Stable Fuzzy Controllers for Nonlinear Systems Based on an Improved Genetic Algorithm

This paper addresses the optimization and stabilization problems of nonlinear systems subject to parameter uncertainties. The methodology is based on a fuzzy logic approach and an improved genetic algorithm (GA). The TSK fuzzy plant model is employed to describe the dynamics of the uncertain nonlinear plant. A fuzzy controller is then obtained to close the feedback loop. The stability conditions are derived. The feedback gains of the fuzzy controller and the solution for meeting the stability conditions are determined using the improved GA. In order to obtain the optimal fuzzy controller, the membership functions are further tuned by minimizing a defined fitness function using the improved GA. An application example on stabilizing a two-link robot arm will be given.

On-line optimal tracking control of continuous-time systems

An on-line optimal tracking control with a quadratic performance index is developed for nonlinear continuous-time systems under control constraints. The systems are represented by a linear sequential model which is derived by using the orthogonal functions. This approach permits the linear feedback control law to be applied to nonlinear continuous-time systems. The on-line optimal tracking control of a two-link robot arm system with control constraints is presented to illustrate the considerable promise that the proposed method exhibits.

Analysis and control of a two-link and three-joint elastic robot arm

A robot system composed of two-link arm and three-joint is considered in this paper. An evolution equation corresponding to the robot system formulated by partial differential equations with initial and boundary conditions is established in an appropriate Hilbert space. The spectral properties of the main operator of the evolution equation is first discussed, and then its semigroup generation is presented based on the resulting spectral properties of. Finally, an asymptotical behavior of the robot system under a designed feedback control is shown in terms of semigroup approach.

Variable structure control for a two-link robot arm

In this paper, a variable structure control method for a two-link robot arm with/without look-up tables is proposed. The stability of the control system is proven. Robustness against parametric variation and external disturbance is achieved. Suitable controller gains are picked up from the angle-related tables to fulfill the control law. The proposed method retains the benefit of variable structure control and further curtails computation time. An additional advantage is that it is not necessary to measure or observe joint angular velocities.

752 電磁吸着ハンドを取り付けた二関節ロボットアームによる鋼球の放り投げ操作

752 電磁吸着ハンドを取り付けた二関節ロボットアームによる鋼球の放り投げ操作

Hierarchical Control of a Space-Based Deployable Manipulator Using Fuzzy Logic

Application of the fuzzy logic intelligent control of space-based systems has received relatively less attention compared to conventional control procedures. Basic concepts involved in development of a hierarchical control system using fuzzy logic are explained. Next, fuzzy logic is applied to control a novel two-link robotic arm, composed of revolute and prismatic joints, supported by a mobile base traversing along an orbiting platform. The control system that is developed has three levels. A conventional controller, consisting of the feedback linearization technique combined with proportional-derivativecontrol is used in the bottom level of the hierarchical system, to control the servomotors of the robot. A second layer consists of a servo-expert that preprocesses the high-resolution information coming from joint encoders and extracts the status of the system. A third, intelligent layer is added at the top of the hierarchy to complete the control structure. The main purpose of the top level is to tune the parameters of the crisp (conventional) controller to improve the response of the system. A decision table is developed of ine, for tuning the parameters of the crisp (nonfuzzy) controller, which considerably reduces the real-time computational effort. Typical pick-and-place results from the robot are presented that show that extra tuning can signiŽ cantly improve the performance of the manipulator.

Calculating the Optimum Two-Link Robot Arm with Respect to Movement Time

The use of a projection-iteration method for determining the response time of a nonlinear dynamic system is examined. The method is based on the idea of a finite difference approximation for the corresponding boundary value problem based on the principle of the maximum of a set of finely divided grids, followed by a solution of the grid equations using a shooting approach with the aid of a gradient method.

An adaptive fuzzy sliding-mode controller

This paper deals with a new adaptive fuzzy sliding-mode controller and its application to a robot manipulator arm. The theory for this approach and for the heuristics-based linguistic adaptation is presented, and a mathematical description is derived. Furthermore, an application of this adaptive controller for a two-link robot arm is shown. The obtained results show the high efficiency of the new controller type.

A dynamical-systems model for Parkinson's disease.

The juxtaposition of hypokinetic and hyperkinetic symptoms in Parkinson's disease (PD) presents a challenge in modeling the basal ganglia. We propose a model of the striatum that can account for the mixture of symptoms seen in PD. In the model, the problem of motor planning is cast in terms of a particle in a potential, where potentials are generated internally in striatal modules, subject to afferent control. Planned movement is governed by Hamilton's equations, where potential energy is supplied by potentials expressed in the striatum. To test the model in realistic situations, a dynamic simulation of a two-link robot arm was used. Normal movement is modeled and shown to exhibit observed experimental properties. Symptoms of PD are reproduced by modeling hypothetical consequences of PD pathology.

Simultaneous optimization of a two-link flexible robot arm

Integrated structurecontrol design of a two-link flexible robot arm is investigated in this article. The whole arm consists of two flexible links, a fixed joint, a moving joint, and a tip load. The arm is driven by the torque motors at the two joints to reach predefined tip positions and to suppress residual flexural vibrations. The links of the arm are modeled using the finite element method and the cross-sectional dimensions of the beam elements are used as structural design variables. A sliding mode controller and a linear stabilizer are used to regulate the arm position. The structural and the control parameters of the whole arm system are optimized simultaneously using a genetic algorithm and the performance is compared with that of an arm with uniform links and an optimized control system. The simulation result shows that faster regulation and less weight of the arm system can be achieved by simultaneous optimization. 2001 John Wiley & Sons, Inc.

Experimental Investigation of Vibration Suppression Control for 2 Link Flexible Robot Arm by Sliding Mode Control.

A reduced order output feedback control algorithm based on a low order modeling methodology for suppressing the vibration and obtaining the high speed, high precision positioning of flexible robot arm is proposed and discussed. The proposed low order modeling methodology gives no modal truncation error and makes it possible to vary the mode shapes of the link according to the change of the boundary conditions due to the feedback gains and the payload at the tip of the arm. Furthermore, this methodology can take into account not only the flexibility of links but also the flexibility of joints. The reduced order output feedback control algorithm is designed by the combination of sliding mode controller and suboptimal output feedback controller so as to achieve both the damping of the system vibration and the stabilization at the same time. The results of numerical simulation and of experiment for a two-link robot arm model are compared. And they prove that the proposed modeling methodology is able to describe the dynamic behaviors of the arm, and the controller designed applying the suboptimal output feedback sliding mode control is able to control the arm quite well.

Vibration Suppression Control of 2 Link Flexible Robot Arm by Sliding Mode Control.

A low order modeling methodology and a reduced order output feedback control algorithm for suppressing the vibration and obtaining the high speed, high precision positioning of flexible robot are presented and discussed. The low order modeling methodology gives no modal truncation error and make it possible to vary the mode shapes of the link according to the change of the boundary conditions due to the feedback gains and the payload at the tip of the arm. The reduced order output feedback sliding mode control algorithm is designed by the combination of sliding mode controller and suboptimal output feedback controller so as to achieve both the damping of the system vigration and the stabilization at the same time. According to the presented method, the vibration suppression control of the two-link robot arm is realized by only 6 sensors, that is, this robot arm model is reduced to 6 output and 2 control input noncollocated system in spite of 34 state variables system.

Stable fuzzy logic design of point-to-point control for mechanical systems

An approach for the development of fuzzy point-to-point control laws for second-order mechanical systems is presented. Asymptotic stability of the resulting closed-loop system is proved using Lyapunov stability theory. Closed-loop performance and robustness are quantified in terms of the parameters of membership functions. As opposed to most existing fuzzy control laws, the closed-loop stability of the proposed controller does not depend on the knowledge of the entire dynamics. Moreover, the approach does not require the plant to be open-loop stable. The proposed approach is demonstrated on design and simulation study of a fuzzy controller for a two-link robotic arm.