We present progressive work that is based on our recently developed rapid control prototyping system (RCP), designed for the implementation of high-performance adaptive optical control algorithms using a continuous de-formable mirror (DM). The RCP system, presented in 2014, is resorting to a Xilinx Kintex-7 Field Programmable Gate Array (FPGA), placed on a self-developed PCIe card, and installed on a high-performance computer that runs a hard real-time Linux operating system. For this purpose, algorithms for the efficient evaluation of data from a Shack-Hartmann wavefront sensor (SHWFS) on an FPGA have been developed. The corresponding analog input and output cards are designed for exploiting the maximum possible performance while not being constrained to a specific DM and control algorithm due to the RCP approach.
In this second part of our contribution, we focus on recent results that we achieved with this novel experimental setup. By presenting results which are far superior to the former ones, we further justify the deployment of the RCP system and its required time and resources. We conducted various experiments for revealing the effective performance, i.e. the maximum manageable complexity in the controller design that may be achieved in real-time without performance losses. A detailed analysis of the hidden latencies is carried out, showing that these latencies have been drastically reduced. In addition, a series of concepts relating the evaluation of the wavefront as well as designing and synthesizing a wavefront are thoroughly investigated with the goal to overcome some of the prevalent limitations. Furthermore, principal results regarding the closed-loop performance of the low-speed dynamics of the integrated heater in a DM concept are illustrated in detail; to be combined with the piezo-electric high-speed actuators in the next step
The speed of real-time adaptive optical systems is primarily restricted by the data processing hardware and computational aspects. Furthermore, the application of mirror layouts with increasing numbers of actuators reduces the bandwidth (speed) of the system and, thus, the number of applicable control algorithms. This burden turns out a key-impediment for deformable mirrors with continuous mirror surface and highly coupled actuator influence functions. In this regard, specialized hardware is necessary for high performance real-time control applications. Our approach to overcome this challenge is an adaptive optics system based on a Shack-Hartmann wavefront sensor (SHWFS) with a CameraLink interface. The data processing is based on a high performance Intel Core i7 Quadcore hard real-time Linux system. Employing a Xilinx Kintex-7 FPGA, an own developed PCie card is outlined in order to accelerate the analysis of a Shack-Hartmann Wavefront Sensor. A recently developed real-time capable spot detection algorithm evaluates the wavefront. The main features of the presented system are the reduction of latency and the acceleration of computation For example, matrix multiplications which in general are of complexity O(n3 are accelerated by using the DSP48 slices of the field-programmable gate array (FPGA) as well as a novel hardware implementation of the SHWFS algorithm. Further benefits are the Streaming SIMD Extensions (SSE) which intensively use the parallelization capability of the processor for further reducing the latency and increasing the bandwidth of the closed-loop. Due to this approach, up to 64 actuators of a deformable mirror can be handled and controlled without noticeable restriction from computational burdens.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.