A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A Multi-Purpose Dynamic Simulation and run-time Control platform includes a virtual process environment coupled to a physical process environment, where components/nodes of the virtual and physical process environments cooperate to dynamically perform run-time process control of an industrial process plant and/or simulations thereof. Virtual components may include virtual run-time nodes and/or simulated nodes. The MPDSC includes an I/O Switch which delivers I/O data between virtual and/or physical nodes, e.g., by using publish/subscribe mechanisms, thereby virtualizing physical I/O process data delivery. Nodes serviced by the I/O Switch may include respective component behavior modules that are unaware as to whether or not they are being utilized on a virtual or physical node. Simulations may be performed in real-time and even in conjunction with run-time operations of the plant, and/or simulations may be manipulated as desired (speed, values, administration, etc.). The platform simultaneously supports simulation and run-time operations and interactions/intersections therebetween.

A rotary microtome and a control method therefore are provided. The rotary microtome includes: a specimen holder, configured to hold a specimen; a handwheel drive system, including a handwheel and a handwheel axis, and configured to receive a user operation via the handwheel and to move the specimen holder up and down via the handwheel axis based on the user operation; a damping component, connected to the handwheel axis, and configured to generate damping for rotation of the handwheel axis; a knife; a section motor, connected to the knife and configured to drive the knife to cut the specimen; and a control device, connected to the damping component and the section motor respectively, and configured to obtain an operation parameter of the section motor, and to adjust the damping generated by the damping component according to the operation parameter, such that the user feels a material hardness of the specimen.

A control system 1 includes a first controller, and a second controller. The second controller includes a program storage module that stores two or more coordinate conversion programs, and a control processing module 240 that acquires program designation information for designating one of two or more coordinate conversion programs from the first controller. Additionally, the control processing module may acquire a first operation command in the coordinate system for the first controller from the first controller, and convert the first operation command to an operation target value of two or more joint axes of a multi-axis robot using the coordinate conversion programs according to the program designation information. Driving power according to the operation target value may be output to the joint axes.

A dynamic environment (e.g., an automated industrial process) has multiple conditions in response to which corresponding actions are required, and comprises various equipment, control device(s) to control the equipment, and one or more sensors to generate input signal(s) representing a monitored condition of the environment. A control system for the environment comprises a master processor and one or more co-processors, wherein the master processor configures a given co-processor to evaluate only a first subset of conditions expected to occur in the environment within a specified time period (e.g., less than a response time of the master processor), and to provide first control information representing an action to be taken if a particular condition of the first subset is satisfied. The co-processor receives the input signal(s) representing the monitored condition, processes the input signal(s) so as to determine if the particular condition of the first subset is satisfied, and provides the first control information to the control devices so as to control the equipment. Exemplary applications include dynamic environments in which machine vision techniques and/or equipment are employed.

A novel piezo-driven cell injection system with force feedback overcomes the unsatisfied force interaction between the pipette needle and embryos in conventional position control. By integrating semiconductor strain-gage sensors for detecting the cell penetration force and the micropipette relative position in real time, the developed cell microinjection system features high operation speed, confident success rate, and high survival rate. The effectiveness of the developed cell injection system is experimentally verified by penetrating zebrafish embryos. The injection of 100 embryos are conducted with separate position control and force control. Results indicate that the force control enables a survival rate of 86%, which is higher than the survival rate of 82% produced by the position control in the same control environment. The experimental results quantitatively demonstrate the superiority of force control over conventional position control for the first time.