The work provides a general model of communication attacks on a networked infinite dimensional system. The system employs a network of inexpensive control units consisting of actuators, sensors and control processors. In an effort to replace a reduced number of expensive high-end actuating and sensing devices implementing an observer-based feedback, the alternate is to use multiple inexpensive actuators/sensors with static output feedback. In order to emulate the performance of the high-end devices, the controllers for the multiple actuator/sensors implement controllers which render the system networked. In doing so, they become prone to communication attacks either as accidental or deliberate actions on the connectivity of the control nodes. A single attack function is proposed which models all types of communication attacks and an adaptive detection scheme is proposed in order to (i) detect the presence of an attack, (ii) diagnose the attack and (iii) accommodate the attack via an appropriate control reconfiguration. The reconfiguration employs the adaptive estimates of the controller gains and restructure the controller adaptively in order to minimize the detrimental effects of the attack on closed-loop performance. Numerical studies on a 1D diffusion PDE employing networked actuator/sensor pairs are included in order to further convey the special architecture of detection and accommodation of networked systems under communication attacks.
more »
« less
This content will become publicly available on June 1, 2024
On Controller Reduction in Linear Quadratic Gaussian Control with Performance Bounds
The problem of controller reduction has a rich history in control theory. Yet, many questions remain open. In particular, there exist very few results on the order reduction of general non-observer based controllers and the subsequent quantification of the closed-loop performance. Recent developments in model-free policy optimization for Linear Quadratic Gaussian (LQG) control have highlighted the importance of this question. In this paper, we first propose a new set of sufficient conditions ensuring that a perturbed controller remains internally stabilizing. Based on this result, we illustrate how to perform order reduction of general (non-observer based) output feedback controllers using balanced truncation and modal truncation. We also provide explicit bounds on the LQG performance of the reduced-order controller. Furthermore, for single-input-single-output (SISO) systems, we introduce a new controller reduction technique by truncating unstable modes. We illustrate our theoretical results with numerical simulations. Our results will serve as valuable tools to design direct policy search algorithms for control problems with partial observations.
more »
« less
- NSF-PAR ID:
- 10443278
- Date Published:
- Journal Name:
- Proceedings of Machine Learning Research
- Volume:
- 211
- ISSN:
- 2640-3498
- Page Range / eLocation ID:
- 1008-1019
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
The control of cryogenic qubits in today’s super-conducting quantum computer prototypes presents significant scalability challenges due to the massive costs of generating/routing the analog control signals that need to be sent from a classical controller at room temperature to the quantum chip inside the dilution refrigerator. Thus, researchers in industry and academia have focused on designing in-fridge classical controllers in order to mitigate these challenges. Due to the maturity of CMOS logic, many industrial efforts (Microsoft, Intel) have focused on Cryo-CMOS as a near-term solution to design in-fridge classical controllers. Meanwhile, Supercon-ducting Single Flux Quantum (SFQ) is an alternative, less mature classical logic family proposed for large-scale in-fridge controllers. SFQ logic has the potential to maximize scalability thanks to its ultra-high speed and very low power consumption. However, architecture design for SFQ logic poses challenges due to its unconventional pulse-driven nature and lack of dense memory and logic. Thus, research at the architecture level is essential to guide architects to design SFQ-based classical controllers for large-scale quantum machines.In this paper, we present DigiQ, the first system-level design of a Noisy Intermediate Scale Quantum (NISQ)-friendly SFQ-based classical controller. We perform a design space exploration of SFQ-based controllers and co-design the quantum gate decompositions and SFQ-based implementation of those decompositions to find an optimal SFQ-friendly design point that trades area and power for latency and control while ensuring good quantum algorithmic performance. Our co-design results in a single instruction, multiple data (SIMD) controller architecture, which has high scalability, but imposes new challenges on the calibration of control pulses. We present software-level solutions to address these challenges, which if unaddressed would degrade quantum circuit fidelity given the imperfections of qubit hardware.To validate and characterize DigiQ, we first implement it using hardware description languages and synthesize it using state-of-the-art/validated SFQ synthesis tools. Our synthesis results show that DigiQ can operate within the tight power and area budget of dilution refrigerators at >42,000-qubit scales. Second, we confirm the effectiveness of DigiQ in running quantum algorithms by modeling the execution time and fidelity of a variety of NISQ applications. We hope that the promising results of this paper motivate experimentalists to further explore SFQ-based quantum controllers to realize large-scale quantum machines with maximized scalability.more » « less
-
Scalability of today’s superconducting quantum computers is limited due to the huge costs of generating/routing microwave control pulses per qubit from room temperature. One active research area in both industry and academia is to push the classical controllers to the dilution refrigerator in order to increase the scalability of quantum computers. Superconducting Single Flux Quantum (SFQ) is a classical logic technology with low power consumption and ultra-high speed, and thus is a promising candidate for in-fridge classical controllers with maximized scalability. Prior work has demonstrated high-fidelity SFQ-based single-qubit gates. However, little research has been done on SFQ-based multi-qubit gates, which are necessary to realize SFQ-based universal quantum computing.In this paper, we present the first thorough analysis of SFQ-based two-qubit gates. Our observations show that SFQ-based two-qubit gates tend to have high leakage to qubit non-computational subspace, which presents severe design challenges. We show that despite these challenges, we can realize gates with high fidelity by carefully designing optimal control methods and qubit architectures. We develop optimal control methods that suppress leakage, and also investigate various qubit architectures that reduce the leakage. After carefully engineering our SFQ-friendly quantum system, we show that it can achieve similar gate fidelity and gate time to microwave-based quantum systems. The promising results of this paper show that (1) SFQ-based universal quantum computation is both feasible and effective; and (2) SFQ is a promising approach in designing classical controller for quantum machines because it can increase the scalability while preserving gate fidelity and performance.more » « less
-
This paper addresses the end-to-end sample complexity bound for learning the H2 optimal controller (the Linear Quadratic Gaussian (LQG) problem) with unknown dynamics, for potentially unstable Linear Time Invariant (LTI) systems. The robust LQG synthesis procedure is performed by considering bounded additive model uncertainty on the coprime factors of the plant. The closed-loopi dentification of the nominal model of the true plant is performed by constructing a Hankel-like matrix from a single time-series of noisy finite length input-output data, using the ordinary least squares algorithm from Sarkar and Rakhlin (2019). Next, an H∞ bound on the estimated model error is provided and the robust controller is designed via convex optimization, much in the spirit of Mania et al. (2019) and Zheng et al. (2020b), while allowing for bounded additive uncertainty on the coprime factors of the model. Our conclusions are consistent with previous results on learning the LQG and LQR controllers.more » « less
-
null (Ed.)The ubiquitous usage of communication networks in modern sensing and control applications has kindled new interests on the timing-based coordination between sensors and controllers, i.e., how to use the “waiting time” to improve the system performance. Contrary to the common belief that a zero-wait policy is always optimal, Sun et al. showed that a controller can strictly improve the data freshness, the so-called Age-of-Information (AoI), by postponing transmission in order to lengthen the duration of staying in a good state. The optimal waiting policy for the sensor side was later characterized in the context of remote estimation. Instead of focusing on the sensor and controller sides separately, this work develops the optimal joint sensor/controller waiting policy in a Wiener-process system. The results can be viewed as strict generalization of the above two important results in the sense that not only do we consider joint sensor/controller designs (as opposed to sensor-only or controller only schemes), but we also assume random delay in both the forward and feedback directions (as opposed to random delay in only one direction). In addition to provable optimality, extensive simulation is used to verify the performance of the proposed scheme in various settings.more » « less
