In case the sophisticated use of robots is considered, it is preferable that the robot has intelligent and flexible abilities according to the environmental variation. Also the easy expansion of the system structure i...
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In case the sophisticated use of robots is considered, it is preferable that the robot has intelligent and flexible abilities according to the environmental variation. Also the easy expansion of the system structure is required. Then the conventional centralized approaches are strictly limited to construct the controller because the system expansion is difficult without the complicated calculation and procedure. To improve the above issue, this paper proposes a hierarchical structure of the controller based on virtual impedance. The validity of the proposed strategy is confirmed by several numerical results.
An experiment in practical implementation of simulated time-optimal control in a laboratory cart-pendulum system is described. The simulation results are compared with two types of measured trajectories of the real sy...
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An experiment in practical implementation of simulated time-optimal control in a laboratory cart-pendulum system is described. The simulation results are compared with two types of measured trajectories of the real system: generated by an implementation of the time-optimal control, and generated by a rule-based algorithm. The technologies of rapid prototyping, real-time simulation and hardware-in-the-loop simulation are used for direct synthesis of control algorithms. The feasibility of construction of time-optimal controller in the real system has been pointed out.
Nonlinear model-based predictive controller with new features including range control, multirate sampling and two degrees of freedom control for PVC batch control/optimization is introduced. The lumped uncertainty des...
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Nonlinear model-based predictive controller with new features including range control, multirate sampling and two degrees of freedom control for PVC batch control/optimization is introduced. The lumped uncertainty design of semi-empirical batch model based on data-mining technologies is described. The controller is complemented by an inferential sensor to reduce the uncertainty about the reactivity of the batch. The knowledge of reactivity is used for batch time optimization under constraints given by shared cooling resources of the plant.
This paper presents a new real-time architecture for motion control of industrial robots. The new controlsystem obtained has two main advantages: first it provides a total open control architecture, and second it is ...
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This paper presents a new real-time architecture for motion control of industrial robots. The new controlsystem obtained has two main advantages: first it provides a total open control architecture, and second it is the simplicity and the interactivity of the platform developed. Experimental evaluation of a passivity-based control scheme shows the benefits of the architecture which is unique in the sense that open and advanced control can be combined with built-in safety logic as required in industrial applications.
Many manufacturing devices must execute motions as quickly as possible to achieve profitable high-volume production. This paper develops shaped torque inputs that minimize move time while avoiding overshoot and oscill...
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Many manufacturing devices must execute motions as quickly as possible to achieve profitable high-volume production. This paper develops shaped torque inputs that minimize move time while avoiding overshoot and oscillation. These inputs are applied to an actual semiconductor manufacturing machine, utilizing both feedforward and feedback strategies for minimizing the degree of vibration generated during fast motions.
This paper formulates the problem of generating structural design constraints for spaceborne precision pointing systems as a robust performance problem. This problem is relevant during the initial requirement flow-dow...
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This paper formulates the problem of generating structural design constraints for spaceborne precision pointing systems as a robust performance problem. This problem is relevant during the initial requirement flow-down and preliminary design phase for these types of systems. Using a nominal controller design, which satisfies the performance requirements on a nominal plant model, frequency dependent uncertainty weights are chosen such that a compromise between simplicity in control architecture and feasibility of mechanical design are made. The analysis problem is formulated as a structural singular value test. The procedure is demonstrated on a single-axis model of a gimbal inertial pointing system when the inertial measurement device is either on or off gimbal.
Methods for estimating the aerospace system parameters and controlling them through two neural networks are presented in this study. We equate the energy function of Hopfield neural network to integral square of error...
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Methods for estimating the aerospace system parameters and controlling them through two neural networks are presented in this study. We equate the energy function of Hopfield neural network to integral square of errors in the system dynamics and extract the parameters of a system. Parameter convergence is proved. For control, we equate the equilibrium status of a `modified' Hopfield neural network to the steady state Ricatti solution with the system parameters as inputs. Through these two networks, we present the online identification and control of an aircraft using its nonlinear dynamics.
This paper gives an empirical study in controlling a typical chemical processes: distillation column, where the equations governing the system are unknown. The neural networks are on-line trained to model the process ...
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This paper gives an empirical study in controlling a typical chemical processes: distillation column, where the equations governing the system are unknown. The neural networks are on-line trained to model the process at various operating points and then employed as nonlinear predictors for use in model predictive control. An explicit control laws are derived by using the Clark's GPC performance index and linearization technique. The experimental results show that the proposed neural control strategies have good practical potential for processes control.
The output tracking control problem of MIMO systems, both minimum and nonminimum phase, is here discussed in sliding mode terms. The first goal of the paper is to address the problem of designing an error feedback con...
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The output tracking control problem of MIMO systems, both minimum and nonminimum phase, is here discussed in sliding mode terms. The first goal of the paper is to address the problem of designing an error feedback controller able to achieve the asymptotic tracking of an exosystem-generated reference trajectory. To this end two design techniques are illustrated. A second goal is to address the robustness of the proposed control scheme against parameter uncertainties and external disturbances.
This research explores the synthesis of feedback controllers for gas-source molecular beam epitaxy, and related processes, using spectroscopic ellipsometry as a sensor technology. The objective in these processes is t...
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This research explores the synthesis of feedback controllers for gas-source molecular beam epitaxy, and related processes, using spectroscopic ellipsometry as a sensor technology. The objective in these processes is to deposit a spatially uniform film that has certain properties with respect to thickness. We approach this objective of synchronizing film properties with thickness as a relaxation of tracking with a natural separation in the feedback design. This paper surveys some of the key issues associated with the modeling, tracking, and synchronization of this system. Simulations indicate previously ungrowable structures, such as quaternary films with arbitrary graded compositions, can be realized.
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