Proportional control

About: Proportional control is a research topic. Over the lifetime, 3756 publications have been published within this topic receiving 49050 citations.

Adaptive Control of Robot Manipulators in Constrained Motion

Abstract: Adaptive motion and force control of manipulators in constrained motion in the presence of parametric uncertainties both in the robot and contact surfaces is solved in this paper. A new constrained dynamic model is obtained to account for the effect of contact surface friction. An adaptive law is suggested with unknown parameters updated by both motion and force tracking errors to guarantee asymptotic motion and force tracking without any persistent excitation condition to be satisfied. The suggested controller includes a expected PI type force feedback control structure with a low proportional (P) force feedback gain. Acausality problem is analyzed by a quasi-static method to show that allowable proportional force feedback gain is severely limited in implementation. With a slight modification to the updating law, the controller also possesses robustness to bounded measurement noise and disturbances.

Control Reconfiguration of Discrete Event Systems With Dynamic Control Specifications

Abstract: This paper defines a reconfiguration method for the class of discrete-event systems (DES) that is subject to linear constraints as their control specifications. Some existing methods for enforcing these constraints make use of Petri-net P-invariants for controller synthesis. These methods are quite appealing because their computational complexity is much more tractable than most other methods for controller synthesis. However, a common limitation of all existing P-invariant-based control architectures for DES plants is the assumption that the linear constraints defining the control specification of the plant do not change over time. Here, we relax this assumption and allow the control specifications to change during controller runtime. Under certain assumptions on DES behavior, we automatically reconfigure the DES controller after the control specification is changed. In addition, if the current state of the controlled DES has become infeasible under the new control specification, we automatically generate a so-called plant reconfiguration procedure whose execution leads the system back to a feasible state. This reconfiguration procedure is optimal in that it seeks to minimize the cost of reconfiguration actions through an Integer Programming (IP) model. The objective function of the IP model can be used to generate reconfiguration solutions that meet some desired properties. Depending on the cost of each reconfiguration action, a minimum cost reconfiguration solution may use only actions contained in the current plant configuration (an internal response), or ask for a change in the plant configuration, for instance, by adding new resources (an external response), or a combination of both strategies. Finally, we illustrate our method by applying it to a hospital control system example. Note to Practitioners-This paper proposes a dynamic reconfiguration framework that can revise the operations of systems whose control requirements change over time. The proposed framework can be applied to systems that satisfy the following two assumptions. First, the behavior of the system under study is described in terms of a set of discrete states and events. Events will cause the system to transition between states. Second, the control requirements must be expressed by linear equalities and inequalities on the system states. Under these circumstances, the proposed framework can identify an optimal transition to a new control policy that satisfies the new control requirements. Moreover, the system under consideration will continue operating while this transition is taking place. One application of this method is in modifying hospital control strategies when a hospital experiences unexpected events. In this case, the hospital operations-such as patient handling, resource assignment, and procedure scheduling-can be represented by discrete state models (e.g., Petri nets). Constraints on these operations can be modeled by linear inequalities on hospital and patient state. Upon a change in the constraints, the proposed reconfiguration method revises the hospital control strategies. For example, a shift in the hospital service demands (e.g., an increase in the flow of patients to the hospital due to a mass casualty situation) can be translated to changes in the constraints. In this case, the hospital operations must be revised to accommodate the new constraints without disrupting the operation of the hospital. The reconfiguration method of this paper provides a framework for modeling the reconfiguration steps and for calculating the least cost reconfiguration solution.

Signal Processing for Proportional Myoelectric Control

Abstract: Proportional myoelectric control of powered prostheses requires the estimation of a time-varying control signal from the patient's myoelectric signal. Since the myoelectric signal is a zero-mean stochastic process, a nonlinearity is a necessary element of the estimator. Typically, a full-wave rectifier is used for this nonlinearity, followed by a low-pass filter to complete the estimation of the control signal. In this work, it is proposed to use a logarithmic nonlinearity, followed by a linear minimum mean-square error estimator. The logarithmic nonlinearity maps the myoelectric signal into an additive control signal-plus-noise domain in which the Kalman filter is employed to estimate the control signal. The theoretical performance of this estimator is obtained and verified by experiments.

Design and implementation of adaptive and repetitive controllers for mechanical manipulators

Abstract: Synthesis and implementation results for a recently developed class of adaptive and repetitive controllers used for motion control of mechanical manipulators are presented. The repetitive controller, which learns the input torque corresponding to a repetitive desired trajectory, requires no explicit knowledge of the manipulator equations of motion. The adaptive controller, on the other hand, which estimates the robot dynamic parameters online, may be used for more general trajectories but requires more detailed modeling information. Both schemes are computationally efficient and require no acceleration feedback of any kind; only standard position and velocity feedback information is utilized. The performances of the above-mentioned controllers were experimentally evaluated on an IBM 7545 robotic manipulator and the results were compared to those of a simple PD (proportional-derivative) feedback system and a compound-torque controller. The repetitive algorithm outperformed the other controllers by a significant margin in terms of the tracking accuracy. >

Experimental evaluation of position control methods for hydraulic systems

Abstract: Presents a unified and systematic assessment of ten position control strategies for a hydraulic servo system with single-ended cylinder driven by a proportional directional control valve. We aim at identifying those methods that achieve better tracking, have a low sensitivity to system uncertainties, and offer a good balance between development effort and end results. A formal approach for solving this problem relies on several practical metrics, which is introduced herein. Their choice is important, as the comparison results between controllers can vary significantly, depending on the selected criterion. Apart from the quantitative assessment, we also raise aspects which are difficult to quantify, but which must stay in attention when considering the position control problem for this class of hydraulic servo systems.