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In this paper, we develop and analyze an integral fixed-time sliding mode control method for a scenario in which the system model is only partially known, utilizing Gaussian processes. We present two theorems on fixed-time convergence. The…

Systems and Control · Electrical Eng. & Systems 2025-05-30 Chaimae El Mortajinea , Moussa Labbadib , Adnane Saoudc , Mostafa Bouzia

Parametric fluctuations or stochastic signals are introduced into the control pulse sequence to investigate the feasibility of random control over quantum open systems. In a large parameter error region, the out-of-order control pulses work…

Quantum Physics · Physics 2014-09-19 Jun Jing , C. Allen Bishop , Lian-Ao Wu

In this review paper, we survey the main concepts and some of the recent developments in quantum feedback control. For consistency and clarity, essential ideas and notations in the theory of open quantum systems and quantum stochastic…

Quantum Physics · Physics 2012-10-02 L. D. Tóth

We present a new Lyapunov-based switching attitude controller for energy-efficient real-time selection of the torque inputted to an uncrewed aerial vehicle (UAV) during flight. The proposed method, using quaternions to describe the attitude…

Systems and Control · Electrical Eng. & Systems 2024-11-04 Francisco M. F. R. Gonçalves , Ryan M. Bena , Néstor O. Pérez-Arancibia

The control of quantum systems is of fundamental scientific interest and promises powerful applications and technologies. Impressive progress has been achieved in isolating the systems from the environment and coherently controlling their…

The optimally designed control of quantum systems is playing an increasingly important role to engineer novel and more efficient quantum technologies. Here, in the scenario represented by controlling an arbitrary quantum system via the…

We evaluate various sources of errors that occur when attempting to produce a specified coherent change of a two-state quantum system using six popular coherent control techniques: resonant excitation, adiabatic following, composite…

Quantum Physics · Physics 2021-03-24 Boyan T. Torosov , Bruce W. Shore , Nikolay V. Vitanov

In recent quantum algorithmic developments, a feedback-based approach has shown promise for preparing quantum many-body system ground states and solving combinatorial optimization problems. This method utilizes quantum Lyapunov control to…

Taking a two-level system as an example, we show that a strong control field may enhance the efficiency of optimal Lyapunov quantum control in [Hou et al., Phys. Rev. A \textbf{86}, 022321 (2012)] but could decrease its control fidelity. A…

Quantum Physics · Physics 2013-06-05 L. C. Wang , S. C. Hou , X. X. Yi , Daoyi Dong , Ian R. Petersen

Control of open quantum systems is an essential ingredient to the realization of contemporary quantum science and technology. We demonstrate such control by employing a thermodynamically consistent framework, taking into account the fact…

Quantum Physics · Physics 2022-05-13 Shimshon Kallush , Roie Dann , Ronnie Kosloff

We develop an input delay-compensating feedback law for linear switched systems with time-dependent switching. Because the future values of the switching signal, which are needed for constructing an exact predictor-feedback law, may be…

Systems and Control · Electrical Eng. & Systems 2025-03-19 Andreas Katsanikakis , Nikolaos Bekiaris-Liberis , Delphine Bresch-Pietri

A variety of tasks in quantum control, ranging from purification and cooling, to quantum stabilization and open-system simulation, rely on the ability to implement a target quantum channel over a specified time interval within prescribed…

Quantum Physics · Physics 2017-08-29 Francesco Ticozzi , Lorenza Viola

Optimal control methods for implementing quantum modules with least amount of relaxative loss are devised to give best approximations to unitary gates under relaxation. The potential gain by optimal control using relaxation parameters…

Quantum Physics · Physics 2011-08-17 T. Schulte-Herbrueggen , A. Spoerl , N. Khaneja , S. J. Glaser

We consider the problem of output feedback stabilization in linear systems when the measured outputs and control inputs are subject to event-triggered sampling and dynamic quantization. A new sampling algorithm is proposed for outputs which…

Dynamical Systems · Mathematics 2016-09-26 Aneel Tanwani , Christophe Prieur , Mirko Fiacchini

Quantum optimal control can play a crucial role to realize a set of universal quantum logic gates with error rates below the threshold required for fault-tolerance. Open-loop quantum optimal control relies on accurate modeling of the…

Quantum Physics · Physics 2018-12-05 Guanru Feng , Franklin H. Cho , Hemant Katiyar , Jun Li , Dawei Lu , Jonathan Baugh , Raymond Laflamme

Closed-loop performance of sequential decision making algorithms, such as model predictive control, depends strongly on the choice of controller parameters. Bayesian optimization allows learning of parameters from closed-loop experiments,…

Systems and Control · Electrical Eng. & Systems 2025-11-18 Sebastian Hirt , Lukas Theiner , Rolf Findeisen

We propose an encoding and control strategy for the stabilization of switched systems with limited information, supposing the controller is given for each mode. Only the quantized output and the active mode of the plant at each sampling…

Systems and Control · Computer Science 2014-12-19 Masashi Wakaiki , Yutaka Yamamoto

The traditional quantum control theory focuses on linear quantum system. Here we show the effect of nonlinearity on quantum control of a two-level system, we find that the nonlinearity can change the controllability of quantum system.…

Quantum Physics · Physics 2015-05-13 W. Wang , J. Shen , X. X. Yi

The purpose of this paper is to present a theoretic and numerical study of utilizing squeezing and phase shift in coherent feedback control of linear quantum optical systems. A quadrature representation with built-in phase shifters is…

Quantum Physics · Physics 2012-06-19 Guofeng Zhang , Heung Wing Joseph Lee , Bo Huang , Hu Zhang

We propose a general model-free strategy for feedback control design of turbulent flows. This strategy called 'machine learning control' (MLC) is capable of exploiting nonlinear mechanisms in a systematic unsupervised manner. It relies on…

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