A new haptic interface device capable of continuous-time impedance display within sampling-period: application to hard surface display

2002 ◽  
Author(s):  
M. Kawai ◽  
T. Yoshikwa
Keyword(s):  
Continuous Time ◽  
Surface Display ◽  
Sampling Period ◽  
Haptic Interface ◽  
Hard Surface ◽  
Interface Device

scholarly journals Haptic Interface Device Using Cable Tension Based on Ultrasonic Phased Array

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 162880-162891
Author(s):  
Liqiang Fan ◽  
Aiguo Song ◽  
Haochen Zhang
Keyword(s):  
Phased Array ◽  
Haptic Interface ◽  
Cable Tension ◽  
Ultrasonic Phased Array ◽  
Interface Device

STATE-SPACE SELF-TUNING CONTROL FOR NONLINEAR STOCHASTIC AND CHAOTIC HYBRID SYSTEMS

2001 ◽  
Vol 11 (04) ◽  
pp. 1079-1113 ◽  
Author(s):  
SHU-MEI GUO ◽  
LEANG-SAN SHIEH ◽  
CHING-FANG LIN ◽  
JAGDISH CHANDRA
Keyword(s):  
State Space ◽  
Hybrid Systems ◽  
Continuous Time ◽  
Digital Control ◽  
Stochastic Systems ◽  
Moving Average ◽  
Computation Time ◽  
Sampling Period ◽  
Noise Model ◽  
Self Tuning

This paper presents a new state-space self-tuning control scheme for adaptive digital control of continuous-time multivariable nonlinear stochastic and chaotic systems, which have unknown system parameters, system and measurement noises, and inaccessible system states. Instead of using the moving average (MA)-based noise model commonly used for adaptive digital control of linear discrete-time stochastic systems in the literature, an adjustable auto-regressive moving average (ARMA)-based noise model with estimated states is constructed for state-space self-tuning control of nonlinear continuous-time stochastic systems. By taking advantage of a digital redesign methodology, which converts a predesigned high-gain analog tracker/observer into a practically implementable low-gain digital tracker/observer, and by taking the non-negligible computation time delay and a relatively longer sampling period into consideration, a digitally redesigned predictive tracker/observer has been newly developed in this paper for adaptive chaotic orbit tracking. The proposed method enables the development of a digitally implementable advanced control algorithm for nonlinear stochastic and chaotic hybrid systems.

Experimental Study of NMP Sample and Hold Input Using an Inverted Pendulum

2018 ◽  
Author(s):  
Yingxu Wang ◽  
Guoming G. Zhu ◽  
Ranjan Mukherjee
Keyword(s):  
Discrete Time ◽  
Continuous Time ◽  
Inverted Pendulum ◽  
Linear Quadratic Regulator ◽  
Sampling Period ◽  
Minimum Phase ◽  
Discrete Time System ◽  
Linear Quadratic ◽  
Sample And Hold ◽  
Control Configuration

Early research showed that a zero-order hold is able to convert a continuous-time non-minimum-phase (NMP) system to a discrete-time minimum-phase (MP) system with a sufficiently large sampling period. However the resulting sample period is often too large to adequately cover the original NMP system dynamics and hence not suitable for control application to take advantage of a discrete-time MP system. This problem was solved using different sample and hold inputs (SHI) to reduce the sampling period significantly for MP discrete-time system. Three SHIs were studied analytically and they are square pulse, forward triangle and backward triangle SHIs. To validate the finding experimentally, a dual-loop linear quadratic regulator (LQR) control configuration is designed for the Quanser single inverted pendulum (SIP) system, where the SIP system is stabilized using the Quanser continuous-time LQR (the first loop) and an additional discrete-time LQR (the second loop) with the proposed SHIs to reduce the cart oscillation. The experimental results show more than 75% reduction of the steady-state cart displacement variance over the single-loop Quanser controller and hence demonstrated the effectiveness of the proposed SHI.

scholarly journals Event-Based Sampled-Data Average Consensus

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Hang Gong ◽  
Fangke Wu ◽  
Runzhi Liu ◽  
Xin Jin ◽  
Wei Zhou ◽  
...  
Keyword(s):  
Continuous Time ◽  
Sufficient Conditions ◽  
Sampling Period ◽  
Graph Laplacian ◽  
Systematic Investigation ◽  
Lyapunov Theory ◽  
Matrix Analysis ◽  
Sampled Data ◽  
Average Consensus ◽  
Event Triggered

This study addresses one of the most essential distributed control problems in multiagent systems, called the average consensus issue, using a new event-triggered sampling control perspective. Although the continuous-time sampling for average consensus has provided good results currently, a systematic investigation into the continuous-time agent dynamics with sampled-data control inputs under an event-triggered mechanism is critically lacking. The problem considered in this paper can be formulated into an average consensus problem of hybrid systems. The method considers three types of control schemes, among which periodic sampling is integrant. The first scheme is a classical sampling controller reinvestigated through a lemma. The second scheme realizes aperiodic control update as well as periodic communication, while the third scheme achieves both aspects aperiodically. Corresponding sufficient conditions of the aforementioned three schemes are derived such that the asymptotic stability of systems is ensured by using algebraic graph theory, matrix analysis, and Lyapunov theory. The constraints for the allowed sampling period, event parameter, and maximum eigenvalue of graph Laplacian are explicitly derived. Moreover, the potential Zeno behavior of agents due to the sampling control theory is avoided. Thus, a digitally implementable technique is provided. Finally, some numerical examples are provided to verify the effectiveness of the proposed theoretical analysis.

scholarly journals Improved Haptic Fidelity Via Reduced Sampling Period With an FPGA-Based Real-Time Hardware Platform

2009 ◽  
Vol 9 (1) ◽  
Author(s):  
Marcia K. O’Malley ◽  
Kevin S. Sevcik ◽  
Emilie Kopp
Keyword(s):  
Real Time ◽  
Sampling Rate ◽  
Sampling Period ◽  
Haptic Device ◽  
Sensor Data ◽  
Haptic Interface ◽  
Hardware System ◽  
Surface Stiffness ◽  
Simulated Environment ◽  
Field Programmable

A haptic virtual environment is considered to be high-fidelity when the environment is perceived by the user to be realistic. For environments featuring rigid objects, perception of a high degree of realism often occurs when the free space of the simulated environment feels free and when surfaces intended to be rigid are perceived as such. Because virtual surfaces (often called virtual walls) are typically modeled as simple unilateral springs, the rigidity of the virtual surface depends on the stiffness of the spring model. For impedance-based haptic interfaces, the stiffness of the virtual surface is limited by the damping and friction inherent in the device, the sampling rate of the control loop, and the quantization of sensor data. If stiffnesses greater than the limit for a particular device are exceeded, the interaction between the human user and the virtual surface via the haptic device becomes nonpassive. We propose a computational platform that increases the sampling rate of the system, thereby increasing the maximum achievable virtual surface stiffness, and subsequently the fidelity of the rendered virtual surfaces. We describe the modification of a PHANToM Premium 1.0 commercial haptic interface to enable computation by a real-time operating system (RTOS) that utilizes a field programmable gate array (FPGA) for data acquisition between the haptic interface hardware and computer. Furthermore, we explore the performance of the FPGA serving as a standalone system for communication and computation. The RTOS system enables a sampling rate for the PHANToM that is 20 times greater than that achieved using the “out of the box” commercial hardware system, increasing the maximum achievable surface stiffness twofold. The FPGA platform enables sampling rates of up to 400 times greater, and stiffnesses over 6 times greater than those achieved with the commercial system. The proposed computational platforms will enable faster sampling rates for any haptic device, thereby improving the fidelity of virtual environments.

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