Test Configuration for Control For the test configuration we used a VME based control system, constituted by a VME crate with a VMPC4a from Cetia (CPU board with PowerPC 604 at 200 MHz, 64 MB RAM – 10Mbit Ethernet on board) and 12bit ADC- DAC mod. VDAD from PEP. The PC Farm is instead a section of the Farm implemented for the development and test of hardware and software configurations for local and distributed data analysis from coalescing binaries within the context of the Virgo experiment for gravitational waves detection. The farm consists of 8 APPRO 2114Xi with Pentium IV 2.4 GHz. The operating system installed on the Napoli farm is Linux RedHat 7.3, kernel , with the OpenMosix extensions. This farms if also included within the GRID geographical network. In fact, each node of the farm is configured as a dual-boot system and can operate as a “grid-element” when needed. The present configuration uses the master node as starting node, while the other nodes boot from the master node via network. Test Configuration for Control For the test configuration we used a VME based control system, constituted by a VME crate with a VMPC4a from Cetia (CPU board with PowerPC 604 at 200 MHz, 64 MB RAM – 10Mbit Ethernet on board) and 12bit ADC- DAC mod. VDAD from PEP. The PC Farm is instead a section of the Farm implemented for the development and test of hardware and software configurations for local and distributed data analysis from coalescing binaries within the context of the Virgo experiment for gravitational waves detection. The farm consists of 8 APPRO 2114Xi with Pentium IV 2.4 GHz. The operating system installed on the Napoli farm is Linux RedHat 7.3, kernel , with the OpenMosix extensions. This farms if also included within the GRID geographical network. In fact, each node of the farm is configured as a dual-boot system and can operate as a “grid-element” when needed. The present configuration uses the master node as starting node, while the other nodes boot from the master node via network. A Real-time Control System Prototype for Mechanical and Optical Systems based on Parallel Computing Techniques F. Acernese a,b, F. Barone c,b, R. De Rosa a,b, R. Esposito b, P. Mastroserio,b, L. Milano a,b, K. Qipiani b, S. Pardi a, F. Silvestri a,b, G. Spadaccini a,b a University of Napoli “Federico II” - Dept. of Scienze Fisiche, Napoli, Italy, I b INFN sez. Napoli, Napoli, Italy, I c University of Salerno - Dept. of Scienze Farmaceutiche, Fisciano, Salerno, Italy, I Motivation The automatic control systems of optical and mechanical systems requires both the perfect and continuous synchronisation of all the systems. This synchronization is generally obtained using specialised hardware (e.g. VME boards, etc.) and software, including real-time operating systems (i.e. LynxOS). These components are generally very expensive if large computing powers are required for the global control of optical and mechanical systems, like adaptive optics systems, mechanical suspensions for gravitational wave detection, optical inteferometers. Moreover, the management and upgrade of these systems is not an easy task. On the other hand, many techniques are now available for increasing the global available off-line computing power, based on standard units (PCs), standard network (Ethernet) and standard operating systems (Linux) and software. This large standardisation and development of special software packages makes it relatively easy to organise these units in clusters (using software tools like OpenMosix, MPI, GRID middleware, etc.) in order to increase the global computing power. As a consequence the cost/GFlop unit is very low in comparison with real-time systems. Therefore, taking into account that the network speed has been largely increased in these last years, we started to explore the possibility of application of off-line standard parallel computing architectures for the implementation of real-time control systems when a large real-time control computing power is required coupled with a limited control band. For this task, we used a control system prototype developed in Napoli for the low frequency control of a suspended optical interferometer and integrated it with the Napoli Computer Farm implemented for the development of off-line parallel data analysis of gravitational waves from coalescing binaries.Motivation The automatic control systems of optical and mechanical systems requires both the perfect and continuous synchronisation of all the systems. This synchronization is generally obtained using specialised hardware (e.g. VME boards, etc.) and software, including real-time operating systems (i.e. LynxOS). These components are generally very expensive if large computing powers are required for the global control of optical and mechanical systems, like adaptive optics systems, mechanical suspensions for gravitational wave detection, optical inteferometers. Moreover, the management and upgrade of these systems is not an easy task. On the other hand, many techniques are now available for increasing the global available off-line computing power, based on standard units (PCs), standard network (Ethernet) and standard operating systems (Linux) and software. This large standardisation and development of special software packages makes it relatively easy to organise these units in clusters (using software tools like OpenMosix, MPI, GRID middleware, etc.) in order to increase the global computing power. As a consequence the cost/GFlop unit is very low in comparison with real-time systems. Therefore, taking into account that the network speed has been largely increased in these last years, we started to explore the possibility of application of off-line standard parallel computing architectures for the implementation of real-time control systems when a large real-time control computing power is required coupled with a limited control band. For this task, we used a control system prototype developed in Napoli for the low frequency control of a suspended optical interferometer and integrated it with the Napoli Computer Farm implemented for the development of off-line parallel data analysis of gravitational waves from coalescing binaries. Experimental Results The experimental control system set-up used to test the control system is shown in figure, While the control system configuration is instead shown in figure The connection among the master CPUs is a point-to-point connection. In order to made the of data transmission we organized a first test by sending blocks of two bytes (corresponding to a 16bit ADC) continuously from one CPU to the other (and viceversa). In this way we measured the statistical time delay of the data transmission. The results obtained for this transfer span from a minimum of 90 us up to a maximum of 150 us. The second test was related instead to the measurement of the full time required from whole chain (from the ADC to the DAC via farm) that put a limit of about 100 Hz to the control band. This limit is anyway mainly due to the VME hardware used. Tests related to the real-time use of the full farm are still in progress, both on the possible parallel and serial computation configurations obtainable with the internal nodes of the farm. Experimental Results The experimental control system set-up used to test the control system is shown in figure, While the control system configuration is instead shown in figure The connection among the master CPUs is a point-to-point connection. In order to made the of data transmission we organized a first test by sending blocks of two bytes (corresponding to a 16bit ADC) continuously from one CPU to the other (and viceversa). In this way we measured the statistical time delay of the data transmission. The results obtained for this transfer span from a minimum of 90 us up to a maximum of 150 us. The second test was related instead to the measurement of the full time required from whole chain (from the ADC to the DAC via farm) that put a limit of about 100 Hz to the control band. This limit is anyway mainly due to the VME hardware used. Tests related to the real-time use of the full farm are still in progress, both on the possible parallel and serial computation configurations obtainable with the internal nodes of the farm. Results We experimentally demonstrated that using standard hardware and software we were able to implement a control system with our configuration up to 100 Hz control band with a computing power provided by the Pc master node of the farm. These tests are very promising in view of the extension of the computing power with the full inclusion of the internal nodes of the farm.Results We experimentally demonstrated that using standard hardware and software we were able to implement a control system with our configuration up to 100 Hz control band with a computing power provided by the Pc master node of the farm. These tests are very promising in view of the extension of the computing power with the full inclusion of the internal nodes of the farm. Magnets Coils Suspended Mass Laser Lens Beam Splitter PSD 2 PSD 1 Suspension points ADC Control DAC PSD Amplifiers Coil Driver Mirror Auxiliary Mirror Synchronous vs. Asynchronous In control system the control is obtained by simply acquiring data with a sampling period (or equivalently at a sampling frequency) generally ten times the control band. Therefore, once that the sampling frequency is chosen, the control band of the system is defined together with the maximum delay with which the acquired data (from ADC) must be presented at the output (DAC) after being processed for the generation of the control signal. As a consequence, the most strict requirement in a control system is to keep very stable and synchronous the sampling frequency (ADC frequency) and the conversion frequency (DAC frequency). The only requirement concerning the computation of the correction signal (control signal) is that it lasts always less than sampling time. Therefore, from the control theory point of view, every asynchronous system may be considered a synchronous one if its response time, although changing, is always less than the sampling time. Synchronous vs. Asynchronous In control system the control is obtained by simply acquiring data with a sampling period (or equivalently at a sampling frequency) generally ten times the control band. Therefore, once that the sampling frequency is chosen, the control band of the system is defined together with the maximum delay with which the acquired data (from ADC) must be presented at the output (DAC) after being processed for the generation of the control signal. As a consequence, the most strict requirement in a control system is to keep very stable and synchronous the sampling frequency (ADC frequency) and the conversion frequency (DAC frequency). The only requirement concerning the computation of the correction signal (control signal) is that it lasts always less than sampling time. Therefore, from the control theory point of view, every asynchronous system may be considered a synchronous one if its response time, although changing, is always less than the sampling time. Università degli Studi di Napoli “Federico II” Istituto Nazionale di Fisica Nucleare - Sezione di Napoli Università degli Studi di Salerno PC ETHERNET VME CPU ADC VME BUS DAC PC PC FARM PC CHEP03 - March 24-28, La Jolla, California