Repetitive processes are a distinct class of 2D linear systems with applications in areas ranging from long-wall coal cutting and metal rolling operations through to iterative learning control schemes. The main featur...
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Cerberus is one of the four new teams in the RoboCup Tournament, Legged Robot Category. The team is a joint effort of Boǧaziçi University (Turkey) and Technical University of Sofia, Branch Plovdiv (Bulgaria). We ...
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Different types of nonlinear controllers are designed and compared for a simple continuous bioreactor operating near optimal productivity. This operating point is located close to a fold bifurcation point. Nonlinear a...
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In this paper we present the optimized design of the 6 degree-of-freedom (DOF) haptic display VISHARD6, which is directed towards modularity, universal applicability, and high force capability. To investigate the perf...
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In this paper we present the optimized design of the 6 degree-of-freedom (DOF) haptic display VISHARD6, which is directed towards modularity, universal applicability, and high force capability. To investigate the performance regarding force, velocity, and acceleration a generic method for output performance analysis of haptic interfaces is proposed. The device is evaluated according to these measures and experimental results are presented.
A computational approach to generate real-time, optimal trajectories for a flight control experiment is presented. Minimum time trajectories are computed for hover-to-hover and forward flight maneuvers. Instantaneous ...
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A computational approach to generate real-time, optimal trajectories for a flight control experiment is presented. Minimum time trajectories are computed for hover-to-hover and forward flight maneuvers. Instantaneous changes in the trajectory constraints that model obstacles and threats are also investigated. Experimental results using the Nonlinear Trajectory Generation software package show good closed-loop performance for all maneuvers. Success of the algorithm demonstrates that high-confidence real-time trajectory generation is achievable in spite of the highly nonlinear and non-convex nature of the problem.
Model predictive control (MPC) is applied to the Caltech ducted fan, a thrust-vectored flight experiment. A real-time trajectory generation software based on spline theory and sequential quadratic programming is used ...
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Model predictive control (MPC) is applied to the Caltech ducted fan, a thrust-vectored flight experiment. A real-time trajectory generation software based on spline theory and sequential quadratic programming is used to implement the MPC controllers. Timing issues related to the computation and implementation of repeatedly updated optimal trajectories are discussed. Results show computational speeds greater than 10 Hz, 2.5 times that of the actuator dynamics. The MPC controllers successfully stabilize a step disturbance applied to the ducted fan and compare favorably to LQR methods.
This paper presents an investigation into classifying myoelectric signals using a new fuzzy clustering neural network architecture for control of multifunction prostheses. Moreover, a comparative study of the classifi...
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This paper presents an investigation into classifying myoelectric signals using a new fuzzy clustering neural network architecture for control of multifunction prostheses. Moreover, a comparative study of the classification accuracy of myoelectric signals using multi-layer perceptron with back-propagation algorithm, and the new fuzzy clustering neural network (FCNN) is presented. The myoelectric signals considered are used to classify four upper-limb movements, which are elbow flexion, elbow extension, wrist pronation and wrist supination, grasp, and resting. The results suggest that FCNN can generalise better than the multi-layer perceptron without requiring extra computational effort. The proposed neural network algorithm allows the user to learn better and faster.
In this paper, a virtual factory using the manufacturing message specification (MMS) companion standard is implemented. The MMS companion standard (9506-3/spl sim/9506-7) and virtual machines are designed and implemen...
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In this paper, a virtual factory using the manufacturing message specification (MMS) companion standard is implemented. The MMS companion standard (9506-3/spl sim/9506-7) and virtual machines are designed and implemented for robot, numerical controller (NC), programmable logic controller (PLC), and process control (PC). Finally, the MMS Internet monitoring system (MIMS) is developed for the testing system.
The growing demand in system reliability and survivability under failures has urged ever-increasing research effort on the development of fault diagnosis and accommodation. In this paper, the on-line fault tolerant co...
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The growing demand in system reliability and survivability under failures has urged ever-increasing research effort on the development of fault diagnosis and accommodation. In this paper, the on-line fault tolerant control problem for dynamic systems under unanticipated failures is investigated from a realistic point of view without any specific assumption on type of system dynamical structure or failure scenarios. The sufficient condition for system on-line stability under catastrophic failures has been derived using the discrete-time Lyapunov stability theory. Based upon the existing control theory and the modern intelligent techniques, an on-line fault accommodation control strategy is proposed to deal with the desired trajectory-tracking problems for systems suffering from various unknown and unanticipated catastrophic failures. To investigate the feasibility of the developed technique for unanticipated fault accommodation in real hardware under the real-time environment, an on-line fault tolerant control test bed has been constructed to validate the proposed technology. Both on-line simulations and the real-time experiment show encouraging results and promising futures of on-line real-time fault tolerant control based solely upon insufficient information of the system dynamics and the failure modes.
In this paper a hierarchical architecture that combines a high degree of reconfigurability and long-term memory is proposed as a fault tolerant control algorithm for complex nonlinear systems. Dual heuristic programmi...
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In this paper a hierarchical architecture that combines a high degree of reconfigurability and long-term memory is proposed as a fault tolerant control algorithm for complex nonlinear systems. Dual heuristic programming (DHP) is used for adapting to faults as they occur for the first time in an effort to prevent the build up of a general failure and also as tuning device after switching to a known scenario. A dynamical database, initialized with as much information of the plant as available, oversees the DHP controller. The decisions of which environments to record, when to intervene and where to switch are autonomously taken based on specifically designed quality indexes. The results of the application of the complete algorithm to a proof-of-the-concept numerical example help to illustrate the fine interrelations between each of its subsystems.
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