Extremum seeking control of quantum gates

To be useful for quantum computation, gate operations must be maintained at high fidelities over long periods of time. In addition to decoherence, slow drifts in control hardware leads to inaccurate gates, causing the quality of operation of as-built quantum computers to vary over time. Here, we demonstrate a data-driven approach to stabilized control, combining extremum-seeking control (ESC) with direct randomized benchmarking (DRB) to stabilize two-qubit gates under unknown control parameter fluctuations. As a case study, we consider these control strategies in the context of a trapped ion quantum computer using physically-realistic simulation. We then experimentally demonstrate this control strategy on a state-of-the-art, commercial trapped-ion quantum computer.Comment: 5 pages, 6 figure

Extremum seeking control of uncertain systems

Extremum seeking is used in control problems where the reference trajectory or reference set point of the system is not known but it is searched in real time in order to maximize or minimize a performance function representing the optimal behaviour of the system. In this paper, extremum seeking algorithm is applied to the systems with parametric uncertainties.Publisher's Versio

Extremum seeking control for truck drag reduction

The aerodynamic drag on a heavy truck tractor and semi-trailer combination can be reduced by means of a wind deflector installed on the roof of the tractor cab. The drag reduction is dependent upon the height and shape of the deflector. A variable height deflector has been constructed and tested in a wind-tunnel and on-road. In this paper, an extremum-seeking control scheme is proposed to adjust on-line the deflector height to minimize the aerodynamic drag. The effectiveness of the scheme is evaluated by simulation and its practicality is evaluated

Extremum-Seeking Control Optimizes VRF Energy Consumption

To a VRF (Variable Refrigerant Flow) system, outdoor unit (ODU) energy consumption is the combination of the power consumption of compressors and outdoor fans. The combined power consumption changes with discharge pressures and other conditions. Discharge pressures are controlled to its’ setpoint by manipulating fan speed. There are optimal discharge pressure points, where the combined power consumptions are at its’ minimum. Most common control approaches in industry on the discharge pressure is setting them to a constant value or calculating as a function of compressor speed and ambient temperature. Fixing it to a constant value is not a desired solution since the optimal pressure points change with load, ambient temperature and other operating conditions. Calculating as a function of compressor speed and ambient temperature, though two major factors are in the consideration, still needs lab tests and calibration to find the relation between the energy consumption and discharge pressure. Since VRF system consists multiple ODUs and IDUs (Indoor Units), the task of lab tests could be overwhelming. In this work, ESC (Extremum-Seeking Control) is used to automatically find the optimum discharge/suction pressure points when VRF is in cooling/heating operation. ESC algorithm is implemented into the VRF equipment control. When ESC is enabled, a small excitement signal applies to discharge setpoint, power consumption of compressors and fans is monitored. ESC will find the optimal discharge setpoints to minimize the combined power consumption. ESC is active in all normal operation conditions, it will optimize the energy consumption over all load ranges of heating/cooling and heat recovery operation. Simulation has been conducted to demonstrate the potential savings on the outdoor unit energy consumption

Advanced control and optimisation of DC-DC converters with application to low carbon technologies

Prompted by a desire to minimise losses between power sources and loads, the aim of this Thesis is to develop novel maximum power point tracking (MPPT) algorithms to allow for efficient power conversion within low carbon technologies. Such technologies include: thermoelectric generators (TEG), photovoltaic (PV) systems, fuel cells (FC) systems, wind turbines etc. MPPT can be efficiently achieved using extremum seeking control (ESC) also known as perturbation based extremum seeking control. The basic idea of an ESC is to search for an extrema in a closed loop fashion requiring only a minimum of a priori knowledge of the plant or system or a cost function. In recognition of problems that accompany ESC, such as limit cycles, convergence speed, and inability to search for global maximum in the presence local maxima this Thesis proposes novel schemes based on extensions of ESC. The first proposed scheme is a variance based switching extremum seeking control (VBS-ESC), which reduces the amplitude of the limit cycle oscillations. The second scheme proposed is a state dependent parameter extremum seeking control (SDP-ESC), which allows the exponential decay of the perturbation signal. Both the VBS-ESC and the SDP-ESC are universal adaptive control schemes that can be applied in the aforementioned systems. Both are suitable for local maxima search. The global maximum search scheme proposed in this Thesis is based on extensions of the SDP-ESC. Convergence to the global maximum is achieved by the use of a searching window mechanism which is capable of scanning all available maxima within operating range. The ability of the proposed scheme to converge to the global maximum is demonstrated through various examples. Through both simulation and experimental studies the benefit of the SDP-ESC has been consistently demonstrated

Control-Affine Extremum Seeking Control with Attenuating Oscillations

Control-affine Extremum Seeking Control (ESC) systems have been increasingly studied and applied in the last decade. Similar to classic ESC related structures, control-affine ESC systems are operable by assuming access to measurements of the objective function, and not necessarily its expression. In contrast to classic ESC related structures, in a control-affine ESC, the objective function -- or a map of it -- is incorporated within the system's vector fields themselves. This has invoked the use of tools from geometric control theory, namely Lie Bracket Systems (LBSs). Said LBSs play a crucial role in stability and performance characterization of ESCs. In a recent effort, many control-affine ESC structures have been generalized in a unifying class and analyzed through LBSs. In addition, this generalized class converge asymptotically to the extremum point; however, the extremum point has to be known a priori and guaranteeing vanishing control input at the extremum point requires the application of strong conditions. In this paper, we introduce a LBS-based ESC structure that: (1) does not require the extremum point a priori, (2) its oscillations attenuate structurally via a novel application of a geometric-based Kalman filter estimating LBSs; and (3) its stability is characterized by a time-dependent (one bound) condition that is verifiable via simulations and relaxed when compared to the generalized approach mentioned earlier. We provide numerical simulations of three problems to demonstrate the ability of our proposed ESC; these problems cannot be solved with vanishing oscillations using the above-mentioned generalized approach in literature

Sliding Mode Extremum Seeking Control for Maximum Power Point Tracking in Wind System

This paper proposes a sliding mode extremum seeking control (SM-ESC) for maximum power point tracking (MPPT) in variable speed wind energy conversion system, which includes the permanent magnet synchronous generator (PMSG), the uncontrolled rectifier, boost converter, battery and the DC constant power load (CPL). The presented MPPT control method integrates the theory of sliding mode control and the extremum seeking control. It refrains from some disadvantages in traditional wind MPPT methods, such as detecting the gradient of output power vs. rotor speed, longer transient response, high frequency noise and larger oscillations of output power. The specific working principle and adaptive step size setting of the MPPT controller are also analyzed based on the SM-ESC algorithm. Numerical simulation results demonstrate accurate operation and robustness of the MPPT algorithm in each operating condition

Robots Looking for Interesting Things: Extremum Seeking Control on Saliency Maps

Abstract-This paper presents a novel approach to increase the amount of visual stimuli in sensor measurements using saliency maps. A saliency map is a combination of normalized feature maps in different channels (i.e. color, intensity) to represent the relative strength of visual stimuli in an image. The total saliency is higher when the camera is looking at a scene with more interesting things in the field of view and vise versa. We employ methods of extremum seeking control to find a camera position that corresponds to local maximum saliency value. We combine the global properties of simplex optimization methods with the local search properties and dynamic response of extremum seeking control to create a novel algorithm that is more likely to find a global maximum than conventional extremum seeking control. Simulations and experiments are presented to show the strength of this approach