56 results about "Random systems" patented technology

A device for measuring a mechanical property of a tissue includes a probe configured to perturb the tissue with movement relative to a surface of the tissue, an actuator coupled to the probe to move the probe, a detector configured to measure a response of the tissue to the perturbation, and a controller coupled to the actuator and the detector. The controller drives the actuator using a stochastic sequence and determines the mechanical property of the tissue using the measured response received from the detector. The probe can be coupled to the tissue surface. The device can include a reference surface configured to contact the tissue surface. The probe may include a set of interchangeable heads, the set including a head for lateral movement of the probe and a head for perpendicular movement of the probe. The perturbation can include extension of the tissue with the probe or sliding the probe across the tissue surface and may also include indentation of the tissue with the probe. In some embodiments, the actuator includes a Lorentz force linear actuator. The mechanical property may be determined using non-linear stochastic system identification. The mechanical property may be indicative of, for example, tissue compliance and tissue elasticity. The device can further include a handle for manual application of the probe to the surface of the tissue and may include an accelerometer detecting an orientation of the probe. The device can be used to test skin tissue of an animal, plant tissue, such as fruit and vegetables, or any other biological tissue.

An apparatus and method for estimation of a system having state variables representing the state of the system comprising predicting the estimate of the state variables along with the uncertainties in the state variables; observing a measurement of at least one state variable corrupted with some amount of error; updating the estimates of the state variables using a weighted average, with more weight being given to estimates with higher certainty; and providing an estimator input to update the estimates of the state variables, the estimator input operating to provide asymptotic convergence of the mean estimation error in all of the state variables in the presence of persistent excitation or disturbance that is not asymptotically decaying to zero.

A simulation system obtains multiple random number vectors and a parameter vector and calculates realized values of the behavior of a stochastic system corresponding to each obtained random number vector. Based on each obtained random number vector, on the obtained parameter vector, and on a weight function, the system calculates the weight of each obtained random number vector regarding each of the parameters in the obtained parameter vector, and calculates an evaluation value of the behavior of the stochastic system corresponding to each obtained random number vector. Based on the calculated behavior evaluation value corresponding to each obtained random number vector and on the weight of each obtained random number vector regarding the parameter selected from the obtained parameter vector, the system calculates the sensitivity of an expected value for the behavior evaluation value of the stochastic system with regard to the selected parameter.

The invention discloses a random system-based fuzzy control algorithm for a single-link manipulator under limited output and time-lag input, which is composed of a fuzzy adaptive controller, a visual sensor, a manipulator control armature and an end dexterous hand. The present invention uses the fuzzy logic system to design a fuzzy adaptive controller for a manipulator system model with random disturbances and a high degree of nonlinearity, and designs a corresponding adaptive algorithm to make it suffer from the controller input delay when performing network control In the case of limited and output signals and various torque random disturbances, it can still accurately track the reference signal and operate the target.

The invention belongs to the technical field of position tracking control of permanent magnet synchronous motors, and specifically discloses a fuzzy self-adaptive control method for random systems of permanent magnet synchronous motors based on state constraints. In view of the problem that the traditional backstepping method cannot constrain the state quantity of the permanent magnet synchronous motor and the random disturbance in the system, a constrained Lyapunov function is constructed to ensure that the state quantities such as the rotor angular velocity and the stator current of the permanent magnet synchronous motor random system are always in the Within a given state interval; the method of the invention adopts a fuzzy logic system to approximate unknown random nonlinear items in the system. The simulation results show that the method of the present invention can not only realize the ideal position tracking control effect, but also can constrain the state quantities such as rotor angular velocity and stator current within a given constraint interval, avoiding safety problems caused by violating state constraints, and effectively Ensure safety specifications and system performance.

The invention discloses a method for examining the fairness of a random selection system. The method comprises the steps of simulation modeling, clustering analysis and result examination, wherein firstly, a simulation model is established after a result generated by the selection system is processed through simulation modeling; secondly, clustering analysis is conducted on the established simulation model, and a clustering result is formed; finally, poisson distribution comparison is conducted on the clustering result, and the fairness of the selection system is examined. Meanwhile, a distributed type storage system Hadoop and a distributed calculation mode Map / Reduce are adopted, the calculation amount is reduced, and the examination speed is greatly increased; poisson distribution which is generally followed by standard random systems is introduced to the method to be used as a comparison basis, accuracy and reliability are achieved, and the fairness of the random selection system is effectively examined.