Time Delay Control of a High-DOF Robot Manipulator Through Feedback Linearization Based Predictor

Author(s):  
Mostafa Bagheri ◽  
Peiman Naseradinmousavi ◽  
Miroslav Krstić

Abstract We formulate a predictor-based controller for a high-DOF manipulator to compensate a time-invariant input delay during a pick-and-place task. Robot manipulators are widely used in tele-manipulation systems on the account of their reliable, fast, and precise motions while they are subject to large delays. Using common control algorithms on such delay systems can cause not only poor control performance, but also catastrophic instability in engineering applications. Therefore, delays need to be compensated in designing robust control laws. As a case study, we focus on a 7-DOF Baxter manipulator subject to three different input delays. First, delay-free dynamic equations of the Baxter manipulator are derived using the Lagrangian method. Then, we formulate a predictor-based controller, in the presence of input delay, in order to track desired trajectories. Finally, the effects of input delays in the absence of a robust predictor are investigated, and then the performance of the predictor-based controller is experimentally evaluated to reveal robustness of the algorithm formulated. Simulation and experimental results demonstrate that the predictor-based controller effectively compensates input delays and achieves closed-loop stability.

Author(s):  
Mostafa Bagheri ◽  
Miroslav Krstić ◽  
Peiman Naseradinmousavi

In this paper, a predictor-based controller for a 7-DOF Baxter manipulator is formulated to compensate a time-invariant input delay during a pick-and-place task. Robot manipulators are extensively employed because of their reliable, fast, and precise motions although they are subject to large time delays like many engineering systems. The time delay may lead to the lack of high precision required and even catastrophic instability. Using common control approaches on such delay systems can cause poor control performance, and uncompensated input delays can produce hazards when used in engineering applications. Therefore, destabilizing time delays need to be regarded in designing control law. First, delay-free dynamic equations are derived using the Lagrangian method. Then, we formulate a predictor-based controller for a 7-DOF Baxter manipulator, in the presence of input delay, in order to track desirable trajectories. Finally, the results are experimentally evaluated.


2006 ◽  
Vol 129 (1) ◽  
pp. 41-55 ◽  
Author(s):  
Matthew D. Baumgart ◽  
Lucy Y. Pao

Web-winding systems, such as tape drives, are often modeled as linear and time-invariant, but at least two nonlinearities are common in these systems. First, the reel radii and moments of inertia change as web media spools from one reel to another. Second, friction can draw a thin layer of air between the layers of web media wrapped on the take-up reel, making the system’s spring and damping characteristics nonlinear by allowing a greater length of media to vibrate freely. In addition to these nonlinearities, there is often uncertainty in the motor parameters. In the first part of this paper, feedback linearization ideas motivate state feedback and changes of variables that transform the system into decoupled and intuitively meaningful tension and velocity loops. For the case where tension measurements are available, Lyapunov redesign techniques are then used to develop control laws that are robust with respect to these nonlinearities and uncertainties. The second part of this paper then develops an observer-based controller for the case where no tension measurements are available. Performance is established analytically for both the measurement-based and observer-based schemes. Simulations illustrate this performance.


Author(s):  
Elizabeth A. Bennett

Cannabis (marijuana) is the most commonly consumed, universally produced, and frequently trafficked psychoactive substance prohibited under international drug control laws. Yet, several countries have recently moved toward legalization. In these places, the legal status of cannabis is complex, especially because illegal markets persist. This chapter explores the ways in which a sector’s legal status interacts with political consumerism. The analysis draws on a case study of political consumerism in the US and Canadian cannabis markets over the past two decades as both countries moved toward legalization. It finds that the goals, tactics, and leadership of political consumerism activities changed as the sector’s legal status shifted. Thus prohibition, semilegalization, and new legality may present special challenges to political consumerism, such as silencing producers, confusing consumers, deterring social movements, and discouraging discourse about ethical issues. The chapter concludes that political consumerism and legal status may have deep import for one another.


Author(s):  
Withit Chatlatanagulchai ◽  
Peter H. Meckl

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.


Automatica ◽  
2010 ◽  
Vol 46 (12) ◽  
pp. 2000-2007 ◽  
Author(s):  
Baozhu Du ◽  
James Lam ◽  
Zhan Shu

Robotica ◽  
2010 ◽  
Vol 29 (3) ◽  
pp. 461-470 ◽  
Author(s):  
Levent Gümüşel ◽  
Nurhan Gürsel Özmen

SUMMARYIn this study, modelling and control of a two-link robot manipulator whose first link is rigid and the second one is flexible is considered for both land and underwater conditions. Governing equations of the systems are derived from Hamilton's Principle and differential eigenvalue problem. A computer program is developed to solve non-linear ordinary differential equations defining the system dynamics by using Runge–Kutta algorithm. The response of the system is evaluated and compared by applying classical control methods; proportional control and proportional + derivative (PD) control and an intelligent technique; integral augmented fuzzy control method. Modelling of drag torques applied to the manipulators moving horizontally under the water is presented. The study confirmed the success of the proposed integral augmented fuzzy control laws as well as classical control methods to drive flexible robots in a wide range of working envelope without overshoot compared to the classical controls.


2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Xinyu Wen

This paper is concerned with disturbance-observer-based control (DOBC) for a class of time-delay systems with uncertain sinusoidal disturbances. The disturbances are decomposed as precise and uncertain parts using nonlinear disturbance observer (DO) after appropriate coordinate transformation. And then the two parts can be compensated by corresponding controller, respectively, such that the classic DOBC method is extended to uncertain disturbance rejection. One novel feature of the proposed method is that even if the precise disturbance parameters are inaccessible, the merits of DOBC can be inherited. By integrating the disturbance observers with feedback control laws with time delay, the disturbances can be rejected and the desired dynamic performances can be guaranteed. Finally, simulations for a flight control system are given to demonstrate the effectiveness of the results.


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