Adaptive Control of Object Path Tracking and Finger Tip Slippage in a Multi-Fingered Robotic System

2008 ◽  
Author(s):  
Shahram Hadian Jazi ◽  
Mehdi Keshmiri ◽  
Farid Sheikholeslam
Keyword(s):  
Adaptive Control ◽  
System Dynamics ◽  
Trajectory Tracking ◽  
Adaptive Controller ◽  
Path Tracking ◽  
Control Synthesis ◽  
Parameter Uncertainties ◽  
New Approach ◽  
Finger Tip ◽  
Bounded Trajectory

Considering slippage between finger tips and an object, adaptive control synthesis of grasping and manipulating an object by a multi-fingered system is addressed in this paper. Slippage can occur due to many reasons such as disturbances, uncertainties in parameters and dynamics. In this paper, using a novel representation of friction and slippage dynamics, a new approach is introduced to analyze the system dynamics. Then an adaptive controller with a simple update rule is proposed to ensure the bounded trajectory tracking and slippage control, and at the same time to compensate for parameter uncertainties including coefficients of friction. The performance of the proposed adaptive controller is shown analytically and studied numerically.

Adaptive manipulation and slippage control of an object in a multi-robot cooperative system

Robotica ◽  
2013 ◽  
Vol 32 (5) ◽  
pp. 783-802
Author(s):  
Shahram Hadian Jazi ◽  
Mehdi Keshmiri ◽  
Farid Sheikholeslam ◽  
Mostafa Ghobadi Shahreza ◽  
Mohammad Keshmiri
Keyword(s):  
Adaptive Control ◽  
Adaptive Controller ◽  
Control Synthesis ◽  
Parameter Uncertainties ◽  
Robot System ◽  
Mass Properties ◽  
Grasping And Manipulation ◽  
Grasp Synthesis ◽  
Adaptive Control Law ◽  
Multi Robot

SUMMARYConsidering undesired slippage between manipulated object and finger tips of a multi-robot system, adaptive control synthesis of the object grasping and manipulation is addressed in this paper. Although many studies can be found in the literature dealing with grasp analysis and grasp synthesis, most assume no slippage between the finger tips and the object. Slippage can occur for many reasons such as disturbances, uncertainties in parameters, and dynamics of the system. In this paper, system dynamics is analyzed using a new presentation of friction and slippage dynamics. Then an adaptive control law is proposed for trajectory tracking and slippage control of the object as well as compensation for parameter uncertainties of the system, such as mass properties and coefficients of friction. Stability of the proposed adaptive controller is studied analytically and the performance of the system is studied numerically.

Design and flight testing of closed-loop simple adaptive control for a biplane micro air vehicle

2019 ◽  
Vol 234 (6) ◽  
pp. 677-689
Author(s):  
Shuvrangshu Jana ◽  
Mayur Shewale ◽  
Susheel Balasubramaniam ◽  
Harikumar Kandath ◽  
M Seetharama Bhat
Keyword(s):  
Adaptive Control ◽  
System Dynamics ◽  
System Performance ◽  
Closed Loop ◽  
Flight Test ◽  
Adaptive Controller ◽  
Micro Air Vehicle ◽  
Plant Performance ◽  
Superior Performance ◽  
Air Vehicle

This article presents the implementation of closed-loop simple adaptive control on fixed-wing micro air vehicle dynamics to improve flight performance characteristics. It is known that to retain the micro air vehicle system performance during the entire flight regime is difficult due to model uncertainties, large parameter variation and wind disturbances compared to flight velocity. An adaptive controller can adapt to the uncertainties but the complexity involved in their implementation is high due to unavailability of required sensor information and computational resources on a micro air vehicle platform. Lack of flight test results in the open literature incorporating adaptive control so far can be partially attributed to this complexity. In this case, adaptive control architecture is implemented in such a way that only the uncertainties in the system dynamics are taken care of by the adaptive control and desired nominal plant performance is achieved by the basic controller. The proposed adaptive controller architecture is implemented in real flight test, and improvement of tracking performance over a proportional–integral–derivative controller is demonstrated which illustrates superior performance to conventional architectures. The proposed design approach can be implemented easily to an existing system, and system performance can be enhanced in the presence of unmodelled and uncertain system dynamics.

A New Approach to Adaptive Control of Manipulators

1987 ◽  
Vol 109 (3) ◽  
pp. 193-202 ◽  
Author(s):  
H. Seraji
Keyword(s):  
Adaptive Control ◽  
A Priori ◽  
Adaptive Controller ◽  
Operating Point ◽  
Adaptation Algorithm ◽  
New Approach ◽  
Control Scheme ◽  
Auxiliary Signal ◽  
Feedforward Controller ◽  
Parameter Values

The paper presents a new approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator “inverse” as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which “behaves” as the “inverse” of the manipulator at any operating point; and the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MR AC theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. Simulation results are presented in support of the proposed adaptive control scheme. The results demonstrate that the adaptive controller performs remarkably well for different reference trajectories and despite gross variations in the payload.

Trajectory tracking of under-actuated quadcopter using Lyapunov-based optimum adaptive controller

2021 ◽  
pp. 095441002110108
Author(s):  
M Navabi ◽  
Ali Davoodi ◽  
Hamidreza Mirzaei
Keyword(s):  
Trajectory Tracking ◽  
Sliding Mode ◽  
Pso Algorithm ◽  
Adaptive Controller ◽  
Closed Loop System ◽  
Parameter Uncertainties ◽  
Trajectory Tracking Control ◽  
Adaptive Sliding Mode Controller ◽  
Backstepping Controller ◽  
Flying Robot

In this article, optimum adaptive sliding mode controller (ASMC) optimized by particle swarm optimization (PSO) algorithm is designed to solve the trajectory tracking control problems of a quadcopter with model parameter uncertainties. Quadcopters have nonlinear, multi-input multi-output, coupled and under-actuated dynamics. For comparison with the designed controller, an adaptive integral backstepping controller approach is applied to compensate mass and inertia uncertainties of the flying robot. These methods guarantee stability of closed-loop system and force the states to track desired reference signals. The performance of both controllers is evaluated by numerical simulations. The obtained results demonstrate the better effectiveness of the designed PSO ASMC in stabilization of tracking particularly with parameter uncertainties.

A longitudinal trajectory tracking method with L1 adaptive control for hypersonic reentry vehicles

2019 ◽  
Vol 42 (3) ◽  
pp. 386-403
Author(s):  
GenSen Han ◽  
Jun Zhou ◽  
JianGuo Guo ◽  
Qing Lu
Keyword(s):  
Adaptive Control ◽  
Trajectory Tracking ◽  
Control Method ◽  
Linear Time ◽  
Adaptive Controller ◽  
Terminal State ◽  
Linear Quadratic ◽  
L1 Adaptive Control ◽  
Reentry Vehicles ◽  
Lqr Controller

This paper presents a longitudinal trajectory tracking scheme with [Formula: see text] adaptive control for hypersonic reentry vehicles (HRVs). A linear time-varying (LTV) multiple input multiple output (MIMO) model, in which influences of lateral states, earth rotation, and linearization are considered as model uncertainties, is derived based on state and input errors of longitudinal model. The normalization of error model is used to reduce differences of magnitude orders in state and input matrix elements which may affect the stability of [Formula: see text] adaptive controller. In order to achieve an accurate tracking performance, a linear quadratic regulator (LQR) controller is employed as the baseline controller, augmented with an [Formula: see text] adaptive controller to attenuate the matched and unmatched uncertainties. Based on the augmented controller, the optimization process is executed with the estimate of uncertainties at the same time. The simulation results of LQR controller, [Formula: see text] augmentation controller and robust [Formula: see text] controller show that the [Formula: see text] adaptive control method can reduce the terminal and integral of squared state errors validly. Terminal state errors in all simulation scenarios are less than 2.5m/s, 1e-3 and 10m, respectively, which reflects its effectiveness in increasing robustness of baseline controller.

Optimal tuned direct adaptive controller for seismic protecting of structures

2021 ◽  
pp. 1045389X2098878
Author(s):  
Amin Hosseini ◽  
Touraj Taghikhany ◽  
Milad Jahangiri
Keyword(s):  
Sensitivity Analysis ◽  
Adaptive Control ◽  
Optimization Problem ◽  
Adaptive Controller ◽  
Sensitivity Analyses ◽  
Building Structures ◽  
Building Structure ◽  
The Past ◽  
Innovative Method ◽  
Story Building

In the past few years, many studies have proved the efficiency of Simple Adaptive Control (SAC) in mitigating earthquakes’ damages to building structures. Nevertheless, the weighting matrices of this controller should be selected after a large number of sensitivity analyses. This step is time-consuming and it will not necessarily yield a controller with optimum performance. In the current study, an innovative method is introduced to tuning the SAC’s weighting matrices, which dispenses with excessive sensitivity analysis. In this regard, we try to define an optimization problem using intelligent evolutionary algorithm and utilized control indices in an objective function. The efficiency of the introduced method is investigated in 6-story building structure equipped with magnetorheological dampers under different seismic actions with and without uncertainty in the model of the proposed structure. The results indicate that the controller designed by the introduced method has a desirable performance under different conditions of uncertainty in the model. Furthermore, it improves the seismic performance of structure as compared to controllers designed through sensitivity analysis.

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