AN IMPEDANCE CONTROL APPROACH FOR FLEXIBLE JOINTS ROBOT MANIPULATORS

1995 ◽  
Vol 19 (3) ◽  
pp. 212-226
Author(s):  
A.T. Massoud ◽  
H.A. ElMaraghy
Keyword(s):  
Impedance Control ◽  
Robot Manipulators ◽  
Position Vector ◽  
Control Input ◽  
Nonlinear Feedback ◽  
Flexible Joints ◽  
Flexible Joint ◽  
Control Approach ◽  
Point Position ◽  
End Point

A nonlinear feedback impedance control approach is presented to control the position and/or force of flexible joints robot manipulators interacting with a compliant environment. A feedback linearizable fourth order model of the flexible joint robots interacting with that environment is constructed. In this model, the control input is related directly to the link position vector and its derivatives. A desired target Cartesian impedance is then specified for the end point of the flexible joints robot. A nonlinear feedback control law is derived to linearize the system and to impose the target impedance for the end point of the robot in the Cartesian space. The same controller is used when the robot is free (unconstrained) and when it interacts with an environment. Also, the input to the system, in both unconstrained and constrained motions, is the end point position and its derivatives. When in free motion, the robot will track the desired end-point position, but while in constrained motion, the desired end point position is used to obtain a desired force according to the specified impedance. An experimental two-link flexible joint robot manipulator, constrained by a straight wall, is used to evaluate the impedance control algorithm.

scholarly journals Chattering-Suppressed Sliding Mode Control for Flexible-Joint Robot Manipulators

Actuators ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 288
Author(s):  
Xin Cheng ◽  
Huashan Liu ◽  
Wenke Lu
Keyword(s):  
Tracking Control ◽  
Sliding Mode ◽  
Robot Manipulators ◽  
Dynamic Performance ◽  
Singular Perturbation Theory ◽  
External Disturbances ◽  
Flexible Joint ◽  
Control Approach ◽  
Control Objective ◽  
Saturation Factor

In this paper, sliding mode tracking control and its chattering suppression method are investigated for flexible-joint robot manipulators with only state measurements of joint actuators. First, within the framework of singular perturbation theory, the control objective of the system is decoupled into two typical tracking aims of a slow subsystem and a fast subsystem. Then, considering lumped uncertainties (including dynamics uncertainties and external disturbances), a composite chattering-suppressed sliding mode controller is proposed, where a smooth-saturation-function-contained reaching law with adjustable saturation factor is designed to alleviate the inherent chattering phenomenon, and a radial basis function neural network (RBFNN)-based soft computing strategy is applied to avoid the high switching gain that leads to chattering amplification. Simultaneously, an efficient extended Kalman filter (EKF) with respect to a new state variable is presented to enable the closed-loop tracking control with neither position nor velocity measurements of links. In addition, an overall analysis on the asymptotic stability of the whole control system is given. Finally, numerical examples verify the superiority of the dynamic performance of the proposed control approach, which is well qualified to suppress the chattering and can effectively eliminate the undesirable effects of the lumped uncertainties with a smaller switching gain reduced by 80% in comparison to that in the controller without RBFNN. The computational efficiency of the proposed EKF increased by about 26%.

Active Vibration Isolation for A Parallel Wheel-legged Robot Based on Dynamic Model

2020 ◽  
Author(s):  
Fei Guo ◽  
Shoukun Wang ◽  
Binkai Yue ◽  
Junzheng Wang
Keyword(s):  
Dynamic Model ◽  
Vibration Isolation ◽  
Force Feedback ◽  
Impedance Control ◽  
Inverse Kinematic ◽  
Control Input ◽  
Control Approach ◽  
Active Vibration ◽  
Robot Body ◽  
Active Vibration Isolation

Abstract Serving Stewart plat as wheel-legged construction, the most outstanding superiority of proposed wheel-legged hybrid robot (WLHR) is active vibration isolation during rolling on rugged terrain. This paper presents a force-driven control approach based on model predictive control (MPC) to design optimal control input for Stewart parallel wheel-leg that locomotes using swing foot trajectory. Adding adaptive impedance control in outermost loop, controlling framework prevents robot body horizontal and from vibration over rolling motion. Through dynamic model of Stewart mechanism, controller first creates predictive model by combining Newton-Euler equation, Newton-Raphson iteration of forward kinematic solving for current configuration, inverse kinematic calculation of Stewart obtaining desired joint position, and Gain/Integration module determining reference torque. With minimizing control deviation and input as objective function, a novel control optimization formulation generates optimum input for each control duration. These actuating force naturally enables each strut stretching and retracting used to realize six degree-of-freedom (6DOF) motion for Stewart wheel-leg. We exploit the variable-adapting method to reasonably adjust environmental impedance parameters by current position, velocity, force feedback of wheel-leg. This allow us to adequately acknowledge the desired support force tracking, isolating robot from isolation that is generated from unknown terrain. We demonstrate the validation of our control methodology on physical prototype by tracking a Bezier curve and active vibration isolation while the robot is rolling on decelerate strip. Respectively given PI controller and a sort of traditional impedance controller as comparison, a better performance of proposed algorithm was operated and evaluated through displacement and force sensors internally-installed in each cylinder, as well as IMU mounted on robot body.

Decentralized adaptive compliance control of robot manipulators

Robotica ◽  
1995 ◽  
Vol 13 (5) ◽  
pp. 485-498 ◽  
Author(s):  
R. Colbaugh ◽  
K. Glass
Keyword(s):  
Contact Force ◽  
Robot Manipulators ◽  
Adaptive Controller ◽  
Control Input ◽  
End Effector ◽  
Joint Torques ◽  
Control Approach ◽  
Dynamic Relationship ◽  
Position Controller ◽  
Parameter Values

SummaryThis paper presents two adaptive schemes for controlling the end-effector compliance of robot manipulators. Each controller possesses a decentralized structure, in which the control input for each configuration degree-offreedom (DOF) is computed based on information concerning only that DOF. The first scheme is developed using an adaptive impedance control approach and consists of two subsystems: a simple “filter” which modifies the end-effector position trajectory based on the sensed contact force and the desired dynamic relationship between the position and force, and an adaptive controller that produces the joint torques required to track this modified trajectory. The second compliant motion control strategy is an adaptive admittance controller for position-controlled manipulators. In this scheme a desired contact force is specified and then position setpoints for the “inner-loop” position controller are generated which ensure that this desired force is achieved. The proposed controllers are extremely simple computationally, do not require knowledge of the manipulator dynamic model or parameter values of the manipulator or the environment, and are implemented in decentralized form.

scholarly journals Extended and Unscented Kalman Filtering Applied to a Flexible-Joint Robot with Jerk Estimation

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Mohammad Ali Badamchizadeh ◽  
Iraj Hassanzadeh ◽  
Mehdi Abedinpour Fallah
Keyword(s):  
Initial Conditions ◽  
Covariance Matrices ◽  
Flexible Joints ◽  
Velocity Measurements ◽  
Lagrange Equations ◽  
Robust Nonlinear Control ◽  
Flexible Joint ◽  
Flexible Joint Robots ◽  
Simulation Results

Robust nonlinear control of flexible-joint robots requires that the link position, velocity, acceleration, and jerk be available. In this paper, we derive the dynamic model of a nonlinear flexible-joint robot based on the governing Euler-Lagrange equations and propose extended and unscented Kalman filters to estimate the link acceleration and jerk from position and velocity measurements. Both observers are designed for the same model and run with the same covariance matrices under the same initial conditions. A five-bar linkage robot with revolute flexible joints is considered as a case study. Simulation results verify the effectiveness of the proposed filters.

Model-Independent Control of a Flexible-Joint Robot Manipulator

2009 ◽  
Vol 131 (4) ◽  
Author(s):  
Withit Chatlatanagulchai ◽  
Peter H. Meckl
Keyword(s):  
Neural Networks ◽  
Open Problem ◽  
High Performance ◽  
Robot Manipulator ◽  
Intrinsic Property ◽  
Variable Structure ◽  
System Model ◽  
Control Input ◽  
Control Laws ◽  
Flexible Joint

Flexibility at the joint of a manipulator is an intrinsic property. Even “rigid-joint” robots, in fact, possess a certain amount of flexibility. Previous experiments confirmed that joint flexibility should be explicitly included in the model when designing a high-performance controller for a manipulator because the flexibility, if not dealt with, can excite system natural frequencies and cause severe damage. However, control design for a flexible-joint robot manipulator is still an open problem. Besides being described by a complicated system model for which the passivity property does not hold, the manipulator is also underactuated, that is, the control input does not drive the link directly, but through the flexible dynamics. Our work offers another possible solution to this open problem. We use three-layer neural networks to represent the system model. Their weights are adapted in real time and from scratch, which means we do not need the mathematical model of the robot in our control algorithm. All uncertainties are handled by variable-structure control. Backstepping structure allows input efforts to be applied to each subsystem where they are needed. Control laws to adjust all adjustable parameters are devised using Lyapunov’s second method to ensure that error trajectories are globally uniformly ultimately bounded. We present two state-feedback schemes: first, when neural networks are used to represent the unknown plant, and second, when neural networks are used to represent the unknown parts of the control laws. In the former case, we also design an observer to enable us to design a control law using only output signals—the link positions. We use simulations to compare our algorithms with some other well-known techniques. We use experiments to demonstrate the practicality of our algorithms.

Flexible-Joint Humanoid Balancing Augmentation via Full-State Feedback Variable Impedance Control

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
Emmanouil Spyrakos-Papastavridis ◽  
Jian S. Dai
Keyword(s):  
State Feedback ◽  
Position Control ◽  
Impedance Control ◽  
Humanoid Robots ◽  
Flexible Joint ◽  
Model Free ◽  
Floating Base ◽  
Full State ◽  
Full State Feedback ◽  
Series Elastic Actuators

Abstract This paper attempts to address the quandary of flexible-joint humanoid balancing performance augmentation, via the introduction of the Full-State Feedback Variable Impedance Control (FSFVIC), and Model-Free Compliant Floating-base VIC (MCFVIC) schemes. In comparison to rigid-joint humanoid robots, efficient balancing control of compliant bipeds, powered by Series Elastic Actuators (or harmonic drives), requires the design of more sophisticated controllers encapsulating both the motor and underactuated link dynamics. It has been demonstrated that Variable Impedance Control (VIC) can improve robotic interaction performance, albeit by introducing energy-injecting elements that may jeopardize closed-loop stability. To this end, the novel FSFVIC and MCFVIC schemes are proposed, which amalgamate both collocated and non-collocated feedback gains, with power-shaping signals that are capable of preserving the system's stability/passivity during VIC. The FSFVIC and MCFVIC stably modulate the system's collocated state gains to augment balancing performance, in addition to the non-collocated state gains that dictate the position control accuracy. Utilization of arbitrarily low-impedance gains is permitted by both the FSFVIC and MCFVIC schemes propounded herein. An array of experiments involving the COmpliant huMANoid reveals that significant balancing performance amelioration is achievable through online modulation of the full-state feedback gains (VIC), as compared to utilization of invariant impedance control.

Smooth Time-Optimal Path Tracking for Robot Manipulators With Kinematic Constraints

2020 ◽  
Author(s):  
Kui Hu ◽  
Yunfei Dong ◽  
Dan Wu
Keyword(s):  
Robot Manipulators ◽  
Optimal Path ◽  
Path Tracking ◽  
Control Input ◽  
Kinematic Constraints ◽  
Computation Efficiency ◽  
Planning Approach ◽  
Time Optimal ◽  
Difference Of Convex ◽  
The Difference

Abstract Previous works solve the time-optimal path tracking problems considering piece-wise constant parametrization for the control input, which may lead to the discontinuous control trajectory. In this paper, a practical smooth minimum time trajectory planning approach for robot manipulators is proposed, which considers complete kinematic constraints including velocity, acceleration and jerk limits. The main contribution of this paper is that the control input is represented as the square root of a polynomial function, which reformulates the velocity and acceleration constraints into linear form and transforms the jerk constraints into the difference of convex form so that the time-optimal problem can be solved through sequential convex programming (SCP). The numerical results of a real 7-DoF manipulator show that the proposed approach can obtain very smooth velocity, acceleration and jerk trajectories with high computation efficiency.

Robust Impedance Control of Manipulators Carrying a Heavy Payload

2010 ◽  
Vol 132 (5) ◽  
Author(s):  
Farhad Aghili
Keyword(s):  
Force Measurement ◽  
Impedance Control ◽  
Stability And Convergence ◽  
Robot Dynamics ◽  
Control Input ◽  
Heavy Load ◽  
Impedance Model ◽  
Force Moment ◽  
Loop Feedback ◽  
The Stability

A heavy payload attached to the wrist force/moment (F/M) sensor of a manipulator can cause the conventional impedance controller to fail in establishing the desired impedance due to the noncontact components of the force measurement, i.e., the inertial and gravitational forces of the payload. This paper proposes an impedance control scheme for such a manipulator to accurately shape its force-response without needing any acceleration measurement. Therefore, no wrist accelerometer or a dynamic estimator for compensating the inertial load forces is required. The impedance controller is further developed using an inner/outer loop feedback approach that not only overcomes the robot dynamics uncertainty, but also allows the specification of the target impedance model in a general form, e.g., a nonlinear model. The stability and convergence of the impedance controller are analytically investigated, and the results show that the control input remains bounded provided that the desired inertia is selected to be different from the payload inertia. Experimental results demonstrate that the proposed impedance controller is able to accurately shape the impedance of a manipulator carrying a relatively heavy load according to the desired impedance model.

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