Posters
A patterning strategy for large area arrays of high density nanostructures
A production-worthy method to implement high density arrays of sub-micron nanostructures at a wafer scale is proposed. It is based on a co-optimization of the layout design, the e-beam lithography exposure and the intermediate SiO2 hard mask used for the final silicon etch process. The great complexity of the e-beam lithography exposure required at this scale to directly obtain the desired geometries has been reduced by introducing an intermediate hard mask to get independent control of some of the pattern parameters through the fabrication process. Rather than using e-beam lithography to create a resist mask for the etch process, which results in unaffordable exposure times for complex geometries (large patterns of curved structures), a simplified e-beamlithography step has been developed to attain a primary resist mask with needed shape and periodicity, but smaller size.
Papers
Active EMI Noise Cancellation
Active EMI noise cancellation can be an effective way to reduce the cost, volume and weight for filtering with motion control systems at both supply and load side. The amount of EMI noise power generated is typically less than 10% of the nominal motion power converted. Direct (analog) feedback systems are limited by latency and therefore limited in cancellation bandwidth. Motion control systems have three main frequency components for disturbances: the power mains frequency, the pulse width modulated frequency (PWM) i.e. sampling frequency and the motion frequency, all with their (inter-)related harmonics. Digital signal processing compensation techniques offer alternatives but have restrictions too. In this paper, these noise compensation bounds will be explored, and some solutions will be given.
Vibration Characterisation for Fault Detection and Isolation in Linear Synchronous Motor based Conveyor Systems
Linear synchronous motor (LSM) based transport systems are increasingly deployed in automated manufacturing environments. The aim of the study is to establish the feasibility of employing low power and low-cost vibration sensing cyber physical systems to perform near real-time fault detection and isolation for passive LSM vehicles. Empirical data capture was conducted on an LSM test-bed where vehicle velocity was varied to determine how changes in velocity would impact the vibration profile of the LSM vehicle. The recorded data was analyzed, and peak accelerations were examined for each of the velocities under study. Frequency domain analysis was conducted on the collated accelerometer data and frequencies of interest were identified. The findings are shown to concur with the manufacturer's operating specifications (0-30 Hz). A relationship between LSM vehicle speed and vibration frequency was established. The results presented provide the basis for the establishment of low-cost condition based preventative maintenance, deployed to a LSM based transport system for high volume manufacturing.
Gaussian Process Repetitive Control for Suppressing Spatial Disturbances: With Application to a Substrate Carrier System
Motion systems are often subject to disturbances such as, cogging, commutation errors, gearings and imbalances, which are position-dependent disturbances, ie, induced by an underlying cause in the spatial domain. In the case that a rotary system operates with a constant operating velocity, or a linear system performs a repetitive motion task, these disturbances appear periodic in the time domain. However, if the operating conditions deviate, the disturbances appears a-periodic in the time domain while being periodic in the spatial domain.
On the use of Wireless Sensor Networks in Preventative Maintenance for Industry 4.0
The goal of this paper is to present a literature study on the use of Wireless Sensor Networks (WSNs) in Preventative Maintenance applications for Industry 4.0. Requirements for industrial applications are discussed along with a comparative of the characteristics of the existing and emerging WSN technology enablers. The design considerations inherent to WSNs becoming a tool to drive maintenance efficiencies are discussed in the context of implementations in the research literature and commercial solutions available on the market.
A closed-loop automatic tuning method for velocity control of oscillatory mechatronic systems
In this paper a closed loop automatic tuning procedure for the velocity control of oscillatory mechatronic systems is proposed. The transfer function of the system is estimated relying only on the measurements on the motor side, resonances are identified and biquadratic filters and the PID controller are tuned in order to improve the pre-existing control system by reducing the oscillations on the load side. Experimental results obtained with a Hardware-In-the-Loop setup show the effectiveness of the method.
Comparison of Linear and Nonlinear MPC on Operator-In-the-Loop Overhead Cranes
Model Predictive Control has been proved to enhance the control performance of overhead cranes. However, in Operator-In-the-Loop (OIL) overhead cranes the trajectory of the payload strongly depends on the runtime decisions of the user and can not be predicted beforehand. Simple assumptions on the future references evolution have therefore to be made. In this paper we investigate the applicability of linear and nonlinear MPC strategies to the case of OIL overhead cranes, based on different assumptions on the future evolution of the length of the hoisting cable.
On the potential for Electromagnetic Energy Harvesting for a Linear Synchronous Motor based Transport System in Factory Automation
Transport systems incorporating linear synchronous motors (LSMs) enable linear motion at high speed for emerging factory automation applications. The goal of this work is to determine the feasibility of harvesting energy directly from an operational LSM transport system employed in high volume manufacturing. Microelectromechanical (MEMs) based sensor technology, deployed as part of a wireless cyber physical system (CPS), perform near real-time magnetic field measurement for a mobile LSM vehicle. The vehicle under study is purposed for mobile factory automation and is not wired for communications nor does it have an onboard power source. A series of experiments were designed and conducted to establish the magnetic profile of the system. Empirical data capture was conducted on a cycled LSM test-bed comprising of 2 shuttles and 2 x 3 meter lengths of LSM track (MagneMotion QuickStick®100). Varying vehicle speeds were incorporated in the experimental regime to determine how changes in velocity would impact the magnetic profile of the vehicle. The recorded magnetic field data was analysed and a relationship between LSM vehicle speed and magnetic field frequency was established. The study highlights the potential to employ a single receiving coil to enable energy recovery which in turn could power a cyber-physical system (CPS) tasked with performing condition based monitoring of the LSM transport vehicles. This in turn can form the basis for the development of a predictive maintenance system, deployed to an LSM based transport layer in high volume manufacturing environments.
I-MECH – Smart System Integration for Mechatronic Applications
Emerging mechatronic applications aim to work at limit performance and reliability while their size and operational space is getting restricted more and more. To reach those targets, often fast integration of customized components is necessary, either electronic systems, SW modules, sensors or actuators. Such diverse set of components needs special tool-chains and methods for fast customization and optimization respecting MBSE (model based system engineering) principles. Large-scale I-MECH project is a natural, fully industry driven initiative trying to follow those demands. The purpose of this paper is to describe its core scientific content, report initial milestones and show a variety of application where I-MECH components, so called building blocks, are being applied.
Essential challenges in motion control education
Smart mechatronic systems and applications with actively controlled moving elements face increasing demands on size, motion speed, precision, adaptability, self-diagnostic, connectivity, new cognitive features, etc. Fulfillment of these requirements is essential for building smart, safe and reliable production complexes. This, however, implies completely new demands on control curricula of master degree students. The aim of this paper is to identify main gaps in motion control education and industrial practice with specific focus on multi-disciplinarity, i.e., contribute to a STEM education ecosystem.
Vibration damping in gantry crane systems: Finite horizon optimal control approach
The paper deals with the problem of anti-sway control in human-operated gantry cranes. The goal is to design a suitable algorithm aiming at minimization of unwanted transient and residual oscillations of the manipulated load. A finite horizon optimization is adopted for the derivation of an optimal open-loop control strategy. The novelty of the proposed approach comes from the combination of model-based predictive control and zero-vibration input shaping methods. This allows utilizing some key advantages from both fields in terms of performance, robustness, constraints definition and simplicity of implementation. Experimental case study demonstrates the proposed approach and compares it to conventional input-shaping method.
Acceleration Feedback in PID Controlled Elastic Drive Systems
This paper deals with the use of a load acceleration feedback to overcome fundamental performance limitations of elastic servo drive systems that occur when employing a standard PI velocity controller. Structured H-infinity optimization approach is used to develop an optimal control strategy consisting of a PI controller and a static acceleration feedback. Qualitative and quantitative analysis of potential benefits for the case of a two-mass system is provided. Effects of higher resonance modes is studied as well. Experimental results demonstrate the application of the proposed methodology to a flexible arm manipulator.
Modular Signal Processing Unit for Motion Control Applications Based on System-on-Chip with FPGA
Motion control systems with distributed architecture where multiple input/output devices are connected to the upper layer controller by fast digital communication (fieldbus) became an industrial standard. This paper presents design of a modular input/output device which can process signals from multiple sensors, drive multiple actuators and act as a Slave or Master node in EtherCAT fieldbus network. User-defined algorithms can be easily implemented to preprocess input signals, combine multiple signals or close local control loops with extremely high sampling rates which makes the difference to standard off-the-shelf solutions. To meet these requirements and simplify hardware design, our device is based on System-on-Chip with both programmable logic (FPGA) and classic processor (CPU) ARM cores. Data processing including user algorithms can be done entirely in FPGA which provides very low latency and no jitter, and also on CPU for more complex computations with advantage of tight integration between FPGA and CPU. In this paper we provide description of hardware design, system architecture and typical applications.
PI Plus Repetitive Control Design: H-infinity Regions Approach
M. Goubej and M. Schlegel, "PI Plus Repetitive Control Design: H-infinity Regions Approach," 2019 22nd
International Conference on Process Control (PC19), Strbske Pleso, Slovakia, 2019, pp. 62-67.
doi: 10.1109/PC.2019.8815312
The paper deals with a class of plug-in type repetitive controllers intended for servo systems which follow periodic reference signals or compensate periodic exogenous disturbances. Proportional-integral (PI) feedback controller is complemented by an internal model of a generic periodic signal aiming at perfect asymptotic tracking or disturbance rejection. A novel design method is proposed allowing a simultaneous tuning of the PI controller and the repetitive control part. The design requirements can be formulated in the frequency domain as proper loop-shaping inequalities defining constraints on important closed-loop sensitivity functions. These constraints are translated directly into the parametric plane of the controller allowing to derive a complete set of admissible controllers. The proposed method is demonstrated in a case study of a flexible motion system.
Data-Driven Feedforward Control for Mechatronic Systems: Analysis, New Approach and Application
Learning control enables substantial performance improvement in control applications. For instance in mechatronicsystems substantial performance enhancements are envis-aged, e.g., learning is a key aspects of I-MECH. Typical learning algorithms are batch-wise, disconnecting time-domain and iteration-domain. Recently, learning control methods are extended with basis functions, i.e., learningfeedforward parameter instead of a specific signal enablingtask flexibility. Indeed, flexibility is essential in mechatronicsystems and one of the reasons that hampers industrial deployment.
Iterative learning control in high-performance motion systems: from theory to implementation
Iterative learning control (ILC) enables a perfect compensation for systems that perform the same task over and over again. The aim of this paper is to demonstrate practical applicability of two various state-of-the-art ILC algorithms to point-to-point positioning systems. A simple Frequency domain ILC approach is exploited focusing on systems with exactly repeating motion tasks. Furthermore, flexible ILC is employed to enable learning also for non-repeating tasks. Particular steps providing a seamless transfer from theory and algorithms to practical implementation in a real-time environment by means of industrial-grade SW and HW are given. They may serve as a practical example of a workflow suitable for a wide range of motion control applications. Potential benefits of the learning-type control in comparison with conventional feedback and feedforward control are discussed as well.
An autotuning procedure for motion control of oscillatory mechatronic systems
In this paper an automatic tuning procedure for a cascade position control architecture of general mechatronic systems is presented. The proposed procedure firstly estimates the transfer function of the system by analysing its open-loop response to a signal specifically designed in order to satisfy the system position, velocity and torque constraints. Then, if present, oscillatory behaviours are detected by finding the (anti)resonances of the frequency response. Parametric tuning rules are eventually defined for the PID controllers and for the biquadratic filters. Results obtained by implementing the procedure on a Hardware In the Loop setup demonstrate the effectiveness of the method.
Application of Impedance Control in Robotic Manipulators for Spacecraft On-orbit Servicing
On-orbit satellite servicing is a technology that is expected to transform the space sector in the coming years. Space robotics is a promising approach to refuel, repair, update, and transport satellites on orbit. However, safe and reliable docking with the client satellite, needed as part of most servicing operations, is still considered a challenge. This paper presents an autonomous robot-based approach for this purpose. An impedance control strategy is added to the controller of a conventional robotic manipulator to allow compliant and safe manipulation of a spacecraft docking mechanism. This setup is expected to facilitate autonomous docking and manipulation operations with cooperative and non-cooperative on-orbit serviced satellites. Platform-art©, a dynamic test bench for hardware-in-the-loop validation of space GNC technologies is used to test the proposed approach.
Feedforward Motion Control: From Batch-to-Batch Learning to Online Parameter Estimation
Feedforward control is essential in high-performance motion control. The aim of this paper is to develop a unified framework for automatic feedforward optimization from both batch-wise data sets as well as real-time data. A statistical analysis is employed to analyze the effect of noise, i.e., an iteration varying disturbance, on feedforward controller performance. This provides new insights, both potential advantages as well as possible hazards of real-time estimation are considered. Finally, a case study confirms and illustrates the results.
Design and performance evaluation of smart vibration sensor for industrial applications with built-in MEMS accelerometers
Paper deals with design and experimental evaluation of performance of a smart vibration sensor for industrial applications based on two built-in MEMS accelerometers and signal pre-processing using a low power microcontroller. The smart sensor is intended for measurements of overall vibration velocity in frequency range defined in ISO standard up to 1 kHz while applications above ISO frequency range up to 10 kHz for acceleration measurement used in bearing diagnostics are also expected.
Prognosis and Health Management in electric drives applications implemented in existing systems with limited data rate
Importance of the condition monitoring and predictive maintenance in motion systems is growing up as motion systems quantum and their complexity (number of axes, performance parameters) increases with increasing the automation of huge range of human activities and manufacturing processes. Probability of failures increases with the system complexity. Many faults and indication of their propagation in the electric drives would require additional sensors or hardware, higher bandwidth and sampling frequencies of feedback sensors, high computing power etc. for development of sophisticated methods to detect specific faults with good sensitivity, robustness and reliability under any operating condition. This paper presents an approach to the condition monitoring and prognosis applicable into the existing systems. These methods use the information available in the traditional electric drives - especially the information from the individual sensors in a voltage source inverter (VSI) and/or an electric motor. Condition indicators for these methods are based on application specific operating states or actions, which generates typical patterns in the signals. The condition monitoring is based on observing the deviations of these patterns between the healthy system and the system with fault propagating. The implementation strategy is described in the paper and some demonstration examples are shown as well.
Model-based Processor-in-the-loop (PIL) Framework for Composable Multi-core platforms
This paper presents a model-based PIL simulation framework targeting multi-core multi-application FPGAbased embedded platforms. The process from model-based simulations to implementing on the platform requires a targetspecified code generation, compile and execution. The presented framework is able to automatically go through this process and perform the PIL simulation starting from a model-based environment in particular Simulink. It is also able to consider the multi-application nature of the target platform, executing the PIL simulation without interfering other applications. We validate the functionality of the PIL framework by testing a control systems application, using various PIL configurations.
Evaluation Platform of Platoon Control Algorithms in Complex Communication Scenarios
S. Zhu, D. Goswami and H. Li, "Evaluation Platform of Platoon Control Algorithms in Complex Communication Scenarios," 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), Kuala Lumpur, Malaysia, 2019, pp. 1-5. doi: 10.1109/VTCSpring.2019.8746477
Cooperative Adaptive Cruise Control (CACC) extends the Adaptive Cruise Control technology with additional information exchange between vehicles over vehicle-to-everything (V2X) communications in an ad-hoc network at 5.9 GHz band (ITS-G5) in Europe. Using beyond line-of-sight information provided by V2X, the platoon control algorithms realize a shorter safe inter-vehicle distance. Nevertheless, the platoon performance (e.g., the allowable inter-vehicle distance) may be impacted by the imperfectness of wireless communications. Specifically, in congested traffic scenarios, a Decentralized Congestion Control method that regulates message rate based on congestion level (Transmit Rate Control (TRC)), may significantly reduce the platoon performance. In this work, we propose an evaluation platform for platoon control algorithms based on industrial V2X nodes operating in the ITS-G5 channels. The real car is simulated by a longitudinal vehicle dynamic model. The model-in-the-loop test results demonstrate that the performance of CACC goes down significantly when the message rate is restricted and reduced by TRC. Our evaluation results further conclude that the effect of such complex communication scenarios imposed by the existing standards should be explicitly modelled in the future platoon control algorithms.
From Batch-to-Batch to Online Learning Control: Experimental Motion Control Case Study
Data-driven feedforward control can significantly improve the positioning performance of motion systems. The aim of this paper is to exploit the concept of batch-to-batch learning control with basis function, applied in an online fashion. This enables learning within a task while maintaining task flexibility. A recursive least squares optimization is proposed on the basis of input/output data to compute the optimal feedforward parameters. The proposed method is successfully validated in simulation, and applied to a benchmark motion system leading to a major performance improvement compared to only feedback control.
Delay-based Design of Feedforward Tracking Control for Predictable Embedded Platforms
This paper presents a design technique for feedforward tracking control targeting predictable embedded platforms. An embedded control implementation experiences sensor-to-actuator delay which
in turn changes the location of the system zeros. In this work, we show that such delay changes the number of unstable zeros which influences the tracking performance. We propose a zero loci
analysis with respect to the delay and identify delay regions which potentially improve tracking performance. We utilize the analysis results to improve tracking performance of implementations
targeting modern predictable embedded architectures where the delay can be precisely regulated.We validate our results by simulation and hardware-in-the-loop (HIL) implementation considering a
real-life motion system.
Feasibiltiy Study and Benchmarking of Embedded MPC for Vehicle Platoons
This paper performs a feasibility analysis of deploying Model Predictive Control (MPC) for vehicle platooning on an On-Board Unit (OBU) and performance benchmarking considering interference from other (system) tasks running on an OBU. MPC is a control strategy that solves an implicit (on-line) or explicit (off-line) optimisation problem for computing the control input in every sample. OBUs have limited computational resources. The challenge is to implement an MPC algorithm on such automotive Electronic Control Units (ECUs) with an acceptable timing behavior. Moreover, we should be able to stop the execution if necessary at the cost of performance. We measured the computational capability of a unit developed by Cohda Wireless and NXP under the influence of its Operating System (OS). Next, we analysed the computational requirements of different state-of-the-art MPC algorithms by estimating their execution times. We use off-the-shelf and free automatic code generators for MPC to run a number of relevant MPC algorithms on the platform. From the results, we conclude that it is feasible to implement MPC on automotive ECUs for vehicle platooning and we further benchmark their performance in terms of MPC parameters such as prediction horizon and system dimension.
Design and Validation of Fault-tolerant Embedded Controllers
Embedded control systems are an important and often safety-critical class of applications that need to operate reliably even in the presence of faults. We show that intermittent fault scenarios caused by wear-out effects due to a higher density and a smaller geometry of the embedded electronic components may become a reliability concern for real-time embedded control applications. To mitigate the effects of such intermittent faults, we propose a novel fault-tolerant controller design method such that the resulting controllers ensure closed loop stability (i.e., guarantee safety) with only possibly degraded performance under such fault scenarios. In order to measure the amortized performance offered by the software implementations of such fault-tolerant controllers, we provide a program analysis methodology that statically estimates the quality of control guaranteed by the C code implementation of the fault-tolerant control law. This combination of fault-tolerant controller design followed by performance feedback computed using a formal analysis is illustrated with a case study from the automotive domain.
Hybrid Automotive In-Vehicle Networks
The design of automotive in-vehicle networks is influenced by several factors like bandwidth, real-time properties, reliability and cost. This has led to a number of protocols and communication standards like CAN, MOST, FlexRay and more recently the use of Ethernet. In the future, wireless in-vehicle communication might also become a possibility. In all of these cases, often hybrid schemes such as the combination of time-triggered (TT) and event-triggered (ET) paradigms have been considered to be useful. Thus, hybrid protocols like FlexRay and TTEthernet, offering advantages of TT and ET communications, are becoming more popular. However, until now the hybrid nature of the protocols has not been exploited in application design. In this paper, we will discuss design strategies for automotive control applications that exploit the hybrid nature of the underlying communication architecture on which they are mapped. Towards this, we will consider a mix of time- and event-triggered schemes as well as a combination of reliable and unreliable communication. Correspondingly, we will show how appropriate abstractions of these hybrid schemes could be lifted to the application design stage.
Analytical Characterization of End-to-End Communication Delays with Logical Execution Time
Modern automotive embedded systems are composed of multiple real-time tasks communicating by means of shared variables. The effect of an initial event is typically propagated to an actuation signal through sequences of tasks writing/reading shared variables, creating an effect chain (EC). The responsiveness, performance and stability of the control algorithms of an automotive application typically depend on the propagation delays of selected ECs. Indeed, task jitter can have a negative impact on the system potentially leading to instability. The logical execution time (LET) model has been recently adopted by the automotive industry as a way of reducing jitter and improving the determinism of the system. In this paper, we provide a formal analysis of the LET model for real-time systems composed of periodic tasks with harmonic and nonharmonic periods, analytically characterizing the control performance of LET ECs. We also show that by introducing tasks offsets, the real-time performance of nonharmonic tasks may improve, getting closer to the constant end-to-end latency experienced in the harmonic case. Further, we present a heuristic algorithm to obtain a set of offsets that might reduce end-to-end latencies, improving LET communication determinism. Finally, we apply this technique to an industrial case study consisting of an automotive engine control system.
Comparing Platform-Aware Control Design Flows For Composable and Predictable TDM-Based Execution Platforms
We compare three platform-aware feedback control design flows that are tailored for a composable and predictable Time Division Multiplexing (TDM)-based execution platform. The platform allows for independent execution of multiple applications. Using the precise timing knowledge of the platform execution, we accurately characterise the execution of the control application (i.e., sensing, computing, and actuating operations) to design efficient feedback controllers with high control performance in terms of settling time. The design flows are derived for Single-Rate (SR) and Multi-Rate (MR) sampling schemes. We show the applicability of the design flows based on two design considerations and their trade-off: control performance and resource utilisation. The design flows are validated by means of MATLAB and Hardware-in-the-Loop (HIL) experiments for a motion control application.
MPC-PID control of operator-in-the-loop overhead cranes: A practical approach
In this paper, a velocity control system for industrial overhead cranes based on a Model Predictive Control approach is proposed. The problem of the control of the operator-in-the-loop system is addressed, as the operator drives the system pushing a button while the control algorithm drives the cart reducing the oscillations of the load. An inner velocity control loop is used in order to overcome some of the problems of controlling the system by using directly the torque of the motor as a control variable. Simulations show the effectiveness of the approach, in particular in the presence of friction.
Model Predictive Control for operator-in-the-loop overhead cranes
In this paper, a Model Predictive Control approach for the velocity control of operator-in-the loop overhead cranes is proposed. The operator can select the maximum position overshoot as a tuning parameter for the method. Simulations provide a comparison between the proposed method and the well known Zero Vibration input shaping technique, showing its effectiveness in controlling the payload oscillations.
Learning in Machines
T. Oomen, "Learning in Machines", Mikroniek December 2018
Control of high-tech mechatronic systems traditionally involves feedback and feedforward control, and essentially only uses a few recent measurements. Here, we aim to explore what can be learned from all available sensor data. A general learning framework is developed that exploits the abundance of data of previously executed tasks. Both fundamental insight and experimental results show that such iterative learning control approaches enable substantial performance improvement compared to traditional control. Interestingly, traditional model-based control theory turns out to have an essential role for fast and safe learning from measured data.
A Fast Autotuning Method for Velocity Control of Mechatronic Systems
In this paper a fast automatic tuning methodology for velocity controllers of mechatronic systems is proposed. In order to be applicable in general, the method takes into account the position, velocity and torque constraints of the motion control system and it requires a minimum intervention of the operator. Further, it can be implemented also with small computational capabilities which makes it suitable for industrial drives. Simulation results show the effectiveness of the technique.
Simplified input-output inversion control of a double pendulum overhead crane for residual oscillations reduction
In this paper we present the application of an input-output inversion technique for the open-loop control of an overhead crane modelled as a double pendulum. The method is mathematically derived, obtaining a parametric trajectory that ensures reduced residual oscillations. Then, it is shown that the postactuation can be neglected so that the method can be implemented with standard industrial drives. The robustness of the method is evaluated by means of simulations, and the performance of the method is experimentally compared with the well-known input shaping technique. The advantages of using a double pendulum model instead of a simple pendulum one are also shown.
On the inclusion of temperature in the friction model of industrial robots
This paper deals with a modelling technique that takes into account the effects of the temperature in the joint friction of industrial robot manipulators. In particular, it is shown that a general friction model can be suitably modified by explicitly considering the temperature as a parameter. This allows to estimate the friction term accurately in different operating conditions without the direct measurement of the joint internal temperature, which makes the overall technique suitable to apply in practical cases. Experimental results show the effectiveness of the methodology.
Modelling the temperature in joint friction of industrial manipulators
In this paper, a new model for joint dynamic friction of industrial robot manipulators is presented. In particular, the effects of the temperature in the joints are considered. A polynomial-based model is proposed and the parameter estimation is performed without the need of a joint temperature sensor. The use of an observer is then proposed to compensate for the uncertainty in the initial estimation of the temperature value. A large experimental campaign show that the model, in spite of the simplifying assumptions made, is effective in estimating the joint temperature and therefore the friction torque during the robot operations, even for values of velocities that have not been previously employed.
On the use of a temperature based friction model for a virtual force sensor in industrial robot manipulators
In this paper we propose the use of a dynamic model in which the effects of temperature on friction are considered to develop a virtual force sensor for industrial robot manipulators. The estimation of the inertial parameters and of the friction model are explained. The effectiveness of the virtual force sensor has been proven in a polishing task. In fact, the interaction forces between the robot and the environment has been measured both with the virtual force sensor and a common load cell. Moreover, the advantages provided by considering the temperature dependency are highlighted.