Softsensors: key component of property control in forming technology

The constantly increasing challenges of production technology for the economic and resource-saving production of metallic workpieces require, among other things, the optimisation of existing processes. Forming technology, which is confronted with new challenges regarding the quality of the workpieces, must also organise the individual processes more efficiently and at the same time more reliably in order to be able to guarantee good workpiece quality and at the same time to be able to produce economically. One way to meet these challenges is to carry out the forming processes in closed-loop control systems using softsensors. Despite the many potential applications of softsensors in the field of forming technology, there is still no definition of the term softsensor. This publication therefore proposes a definition of the softsensor based on the definition of a sensor and the distinction from the observer, which on the one hand is intended to stimulate scientific discourse and on the other hand is also intended to form the basis for further scientific work. Based on this definition, a wide variety of highly topical application examples of various softsensors in the field of forming technology are given

Parametrische Modellordnungsreduktion für hierarchische selbstoptimierende Systeme

Parametric model-order reduction for the reduction of Pareto optimal systems is presented in this paper. The developed method can be used to simplify complex models which describe the dynamical behavior of self-optimizing systems. The close interrelation of parametric model-order reduction with both hierarchical optimization as well as hierarchical modelling of mechatronic systems is an outstanding feature of the proposed method. A brief overview of the approach is given and a test rig of an active suspension system serves as an application example

Umsetzung einer echtzeitfähigen modellprädiktiven Trajektorienplanung für eine mehrachsige Hybridkinematik auf einer Industriesteuerung

In context of lot-size 1 flexible manufacturing systems have to adjust their motion behaviour automatically to different workpieces. Therefore advanced control strategies are needed, often based on optimization. Offline calculation is usually not sufficient because of the dynamic sequence of different workpieces. The key challenge is to design a real-time self-optimizing control strategy and implement it on an industrial control hardware which executes the optimization online.In the present contribution a real-time model predictive control strategy is introduced which is implemented on a programmable logic controller (PLC). This control strategy is used to calculate minimum-time trajectories for an application-specific redundant hybrid-kinematic mechanism moving between discrete processing positions. The objective function as well as the used models are presented. Moreover, an analysis of the required calculation time, the results achieved and their dependency on optimization parameters are discussed

A model extended temperature and strain controller modulated with PWM for precision position control of shape memory alloy actuators

This paper presents a novel control strategy for precision position control of Shape Memory Alloy (SMA) actuators by using a combination of large and small signal controllers. The large signal controller, responsible for coarse positioning, is an NPID temperature controller that gets its desired temperature value online from a computationally efficient stress-strain and phase kinetics SMA model that accounts for time varying stresses. The small signal controller, responsible for fine positioning, is an NPID position (strain) controller. The control signals are modulated with PWM to generate a series of current pulses that heat the SMA. The control strategy is tested on an SMA wire, first, with various constant loads and then with varying loads. The results show robust and precise tracking control with exceptional disturbance rejection

Precision control of SMA actuators with a real time model-based controller and extended VSC

This paper presents a novel control strategy for precision position control of Shape Memory Alloy (SMA) actuators by using a combination of large and small signal controllers. The large signal controller, responsible for course positioning, is an NPID temperature controller that gets its desired temperature value online from a computationally efficient stress-strain and phase kinetics SMA model that accounts for time varying stresses. The small signal controller, responsible for fine positioning, is an extended variable structure controller that uses an asymmetrical boundary layer to prevent over-heating of the wire and whose control signals adapt to the dynamic load on the wire. The control strategy is tested on an SMA wire, first, with various constant loads and then with varying loads. The results show robust and precise tracking control within 0.03% strain with exceptional disturbance rejection

Continuous objective-based control for self-optimizing systems with changing operation modes

Self-optimization enables technical systems to adapt their behavior to varying environmental conditions and changing operation modes. Objective functions serve as evaluation criteria for the system behavior. In this paper we present a novel approach of an objective-based controller. This controller is based on Pareto sets, which are solutions of multiobjective optimization problems and computed offline. The controller can be used to continuously adjust the system behavior by computing optimal configurations out of the Pareto sets without solving an optimization problem at runtime. The goal of the controller is to drive the objective values toward a desired relative weighting. Furthermore, the controller is able to cope with varying operation modes, which arise in case of component faults, for example. For each operation mode an entire Pareto set is computed separately. For designing the objective-based controller we use a simplified model of the closed-loop system. The objective values are approximated at runtime by means of a lowpass filter. An active suspension system affected by unknown track excitations serves as an application example. We use a particular control reconfiguration approach in case of an actuator fault as a change of the operation mode. Finally, simulations with a nonlinear model of the system validate our approach

A HRRN based scheduling for FMS and RMS with networked control and product-intelligence

In the area of product-based control of manufacturing processes, the potential to integrate intelligent products in process control has been recognized several times. However, the integration of greatly varying intelligent products on the job scheduling and networked control of distributed cell-based manufacturing processes have not been investigated. This paper begins with definitions of product-intelligence and a so called distributed data and interface model. Based on this, a cell-based manufacturing process with networked control architecture with different intelligent products as a function of varying product properties is presented. In addition, the product-intelligence and a highest response ratio next based job scheduling approach for flexible and reconfigurable manufacturing systems is presented. Through simulation results from a flexible candle manufacturing demonstrator scenario, it has been shown that the extended highest response ratio next scheduling approach represents a further module in the realization of product-intelligence based cyber-physical production systems with variable lot sizes and product-individual requirements

Development and design of intelligent product carriers for flexible networked control of distributed manufacturing processes

In the area of product-based control of manufacturing processes, the potential to integrate intelligent products in process control has been recognized several times. However, the requirements of greatly varying intelligent products on the networked control and hybrid system dynamics of the distributed individual (sub-) processes have not been investigated. This paper begins with definitions of product-intelligence and distributed data and interface model. Based on this, a networked decentralized control structure with different intelligent products as a function of varying product properties is presented. In addition, the requirements for the design of intelligent products are presented. Through the implementation, it has been shown that the intelligent workpiece carrier represents a further module in the realization of cyber-physical production systems (CPPS) through comprehensive analysis and synthesis of a highly flexible distributed control