Concepts for Sensor Matching in Mechatronic Systems

A typical mechatronic system consists of a multitude of components,and the sensors belong to an important and crucial class of such components.Optimal matching of the system components is implicit in the current definition of a mechatronic system.The focus of the present paper is the optimal matching of sensors with other hardware in the system.Sensor matching may be based on several concepts such as the operating frequency range(operating bandwidth),speed of response(and the corresponding rate of data sampling in digital conversion),the device sensitivity(or gain or data amplification),and the effect of component acc uracy on the overall accuracy of the system.The present paper explores all these concepts and presents suit able approaches for sensor matching through those criteria.The relevant procedures are illustrated using case studies.

Improving the Efficiency of Mechatronic Systems in Order to Ensure Intensive Reform“Industry-4.0”

The presented work will show the highest relevance of solving all the issues related to this problem and present the results of the analysis of the main expected potential problems,which may occur in the implementation of the INDUSTRY-4.0 reform.It is proved that the pace and level of development of this reform will be determined to a large extent by the effectiveness of the individual nodes used and the entire mechatronic system.It has also been established that as a result of systematic miniaturization of the nodes of radio-electronic equipment and microelectronic equipment and microelectronic technology,the main problem of these reforms and the implementation of complex technological processes is instrumental and technological support,especially with cutting micro-tools and equipment.Therefore,on the example of these investigations,methods for improving their performance are shown.

Mechatronic Modeling and Domain Transformation of Multi-physics Systems

The enhanced definition of Mechatronics involves the four underlying characteristics of integrated,unified,unique,and systematic approaches.In this realm,Mechatronics is not limited to electro-mechanical systems,in the multi-physics sense,but involves other physical domains such as fluid and thermal.This paper summarizes the mechatronic approach to modeling.Linear graphs facilitate the development of state-space models of mechatronic systems,through this approach.The use of linear graphs in mechatronic modeling is outlined and an illustrative example of sound system modeling is given.Both time-domain and frequency-domain approaches are presented for the use of linear graphs.A mechatronic model of a multi-physics system may be simplified by converting all the physical domains into an equivalent single-domain system that is entirely in the output domain of the system.This approach of converting(transforming)physical domains is presented.An illustrative example of a pressure-controlled hydraulic actuator system that operates a mechanical load is given.

Minimal Realization of Linear Graph Models for Multi-physics Systems

An engineering system may consist of several different types of components,belonging to such physical"domains"as mechanical,electrical,fluid,and thermal.It is termed a multi-domain(or multi-physics)system.The present paper concerns the use of linear graphs(LGs)to generate a minimal model for a multi-physics system.A state-space model has to be a minimal realization.Specifically,the number of state variables in the model should be the minimum number that can completely represent the dynamic state of the system.This choice is not straightforward.Initially,state variables are assigned to all the energy-storage elements of the system.However,some of the energy storage elements may not be independent,and then some of the chosen state variables will be redundant.An approach is presented in the paper,with illustrative examples in the mixed fluid-mechanical domains,to illustrate a way to recognize dependent energy storage elements and thereby obtain a minimal state-space model.System analysis in the frequency domain is known to be more convenient than in the time domain,mainly because the relevant operations are algebraic rather than differential.For achieving this objective,the state space model has to be converted into a transfer function.The direct way is to first convert the state-space model into the input-output differential equation,and then substitute the time derivative by the Laplace variable.This approach is shown in the paper.The same result can be obtained through the transfer function linear graph(TF LG)of the system.In a multi-physics system,first the physical domains have to be converted into an equivalent single domain(preferably,the output domain of the system),when using the method of TFLG.This procedure is illustrated as well,in the present paper.

Controlling Tendons to Modulate Stiffness of a Planar-to-Spatial Tendon-Driven Continuum Manipulator Under External Uncertain Forces

Continuum manipulators(CM)are soft and flexible manipulators with large numbers of degrees of freedom and can perform complex tasks in an unstructured environment.However,their deformability and compliance can deviate distal tip under uncertain external interactions.To address this challenge,a novel tension-based control scheme has been proposed to modulate the stiffness of a tendon-driven CM,reducing the tip position errors caused by uncertain external forces.To minimize the tip position error,a virtual spring is positioned between the deviated and the desired tip positions.The proposed algorithm corrects the manipulator deviated tip position,improving tension distribution and stiffness profile,resulting in higher stiffness and better performance.The corresponding task space stiffness and condition numbers are also computed under different cases,indicating the effectiveness of the tension control scheme in modulating the manipulator's stiffness.Experimental validation conducted on an in-house developed prototype confirms the practical feasibility of the proposed approach.