Robust Closed-loop Control Research Articles

A Multimode Transverse Dynamic Force Microscope—Design, Identification, and Control

The transverse dynamic force microscope (TDFM) and its shear force sensing principle permit true noncontact force detection in contrast to typical atomic force microscopes. The two TDFM measurement signals for the cantilever allow, in principle, two different scanning modes of which, in particular, the second presented here permits a full-scale noncontact scan. Previous research work mainly focused on developing the sensing mechanism, whereas this paper investigates the vertical axis dynamics for advanced robust closed-loop control. This paper presents a new TDFM digital control solution, built on field-programmable gate array equipment running at high implementation frequencies. The integrated control system allows the implementation of online customizable controllers, and raster scans in two modes at very high detection bandwidth and nanoprecision. Robust control algorithms are designed, implemented, and practically assessed. The two realized scanning modes are experimentally evaluated by imaging nanospheres with known dimensions in wet conditions.

Robust Extremum Seeking for a Second Order Uncertain Plant Using a Sliding Mode Controller

Abstract This paper suggests a novel continuous-time robust extremum seeking algorithm for an unknown convex function constrained by a dynamical plant with uncertainties. The main idea of the proposed method is to develop a robust closed-loop controller based on sliding modes where the sliding surface takes the trajectory around a zone of the optimal point. We assume that the output of the plant is given by the states and a measure of the function. We show the stability and zone-convergence of the proposed algorithm. In order to validate the proposed method, we present a numerical example.

Robust closed-loop control of spike-and-wave discharges in a thalamocortical computational model of absence epilepsy

In this paper, we investigate the abatement of spike-and-wave discharges in a thalamocortical model using a closed-loop brain stimulation method. We first explore the complex states and various transitions in the thalamocortical computational model of absence epilepsy by using bifurcation analysis. We demonstrate that the Hopf and double cycle bifurcations are the key dynamical mechanisms of the experimental observed bidirectional communications during absence seizures through top-down cortical excitation and thalamic feedforward inhibition. Then, we formulate the abatement of epileptic seizures to a closed-loop tracking control problem. Finally, we propose a neural network based sliding mode feedback control system to drive the dynamics of pathological cortical area to track the desired normal background activities. The control system is robust to uncertainties and disturbances, and its stability is guaranteed by Lyapunov stability theorem. Our results suggest that the seizure abatement can be modeled as a tracking control problem and solved by a robust closed-loop control method, which provides a promising brain stimulation strategy.

Open-End Windings Induction Motor Drive With Floating Capacitor Bridge at Variable DC-Link Voltage

The open-end winding configuration allows feeding an electric motor from two sides. If one of them is connected to an inverter closed on a floating capacitor and operates as a power conditioning system, it is possible to obtain several benefits over the traditional configuration, such as an increase in the constant-power speed range. However, the additional converter causes switching losses that reduce the total efficiency of the drive. In this paper, it is shown how to improve the efficiency of an induction motor drive with open-end windings by controlling the dc-link voltage of the floating bridge depending on the operating conditions. The set-point of the secondary dc link is not calculated as an explicit function of the motor speed, which could depend on many machine parameters, but it is generated by a robust closed-loop control that uses the actual motor state. The variable dc link allows improving the overall efficiency of the drive mainly around the base speed at high values of the torque. Experimental results are shown to confirm the effectiveness of the developed configuration.

Model Analysis of Heat Transfer by Hammerstein systems and optical instrumentation

Abstract Heat transfer is the core of a combustion process. In the present work, motivated by the recent inclusion of optical instrumentation to perform in situ analysis or combustion diagnostics, we consider the modeling and control of heat transfer by total radiation Radt, by taking information from Hammerstein and LTI modeling. We analyze the overall H ∞ -norm performance in open-loop and closed-loop, calculated around specific operational conditions for Hammerstein nominal model. From the results, we verify a significant uncertainty, and simultaneously we propose a robust closed-loop control of the Hammerstein nominal model able to handle the uncertainty in the models.

Robust closed-loop control of vegetable production in plant factory

Internal variations and external disturbances often adversely influence normal operation of plant factories and their production stability. In this research, a salad-cultivating plant factory (abbreviated as SPF) was considered as a dissipative system, its highly valid kinetic model was developed using system dynamics and experimental data. Optimal closed-loop control law of light intensity, temperature and aerating rate was then obtained based on the gradient of stored-energy (Lyapunov) function of the SPF derived from Hamilton-Jacobi-Isaacs equation. Both digital and real-time simulation results showed that the SPF closed-loop control system with optimal control law could continuously dissipate the stored energy, namely internal variation and external disturbances resulting from insect and microbial damage and other environmental fluctuations with different strengths to stabilize the SPF at an operating point and maintaining the good yield of salad with desired dynamic response characteristics to control actions. This research will lay a theoretical and method foundation for construction and operation of facility agricultural systems and closed artificial ecosystems.

Design strategies for dynamic closed-loop optogenetic neurocontrol in vivo

Objective. Controlling neural activity enables the possibility of manipulating sensory perception, cognitive processes, and body movement, in addition to providing a powerful framework for functionally disentangling the neural circuits that underlie these complex phenomena. Over the last decade, optogenetic stimulation has become an increasingly important and powerful tool for understanding neural circuit function, owing to the ability to target specific cell types and bidirectionally modulate neural activity. To date, most stimulation has been provided in open-loop or in an on/off closed-loop fashion, where previously-determined stimulation is triggered by an event. Here, we describe and demonstrate a design approach for precise optogenetic control of neuronal firing rate modulation using feedback to guide stimulation continuously. Approach. Using the rodent somatosensory thalamus as an experimental testbed for realizing desired time-varying patterns of firing rate modulation, we utilized a moving average exponential filter to estimate firing rate online from single-unit spiking measured extracellularly. This estimate of instantaneous rate served as feedback for a proportional integral (PI) controller, which was designed during the experiment based on a linear-nonlinear Poisson (LNP) model of the neuronal response to light. Main results. The LNP model fit during the experiment enabled robust closed-loop control, resulting in good tracking of sinusoidal and non-sinusoidal targets, and rejection of unmeasured disturbances. Closed-loop control also enabled manipulation of trial-to-trial variability. Significance. Because neuroscientists are faced with the challenge of dissecting the functions of circuit components, the ability to maintain control of a region of interest in spite of changes in ongoing neural activity will be important for disambiguating function within networks. Closed-loop stimulation strategies are ideal for control that is robust to such changes, and the employment of continuous feedback to adjust stimulation in real-time can improve the quality of data collected using optogenetic manipulation.

Design of a Model-based Fractional-Order Controller for Optimal Charging of Batteries

this paper proposes a robust closed-loop control strategy for optimal charging of batteries. Model-based design of the charging controller is performed based on a coupled electro-thermal aging battery model. For developing an optimal charging strategy, besides minimization of charging time, prolonging the lifetime of the battery is of great importance. As the first step towards implementing a health-conscious charging controller, trajectory planning is carried out by solving a nonlinear optimization problem. The aim is to obtain optimal charging profiles while minimizing the aging. By linearization of the nonlinear battery model, a large uncertainty is observed in the behavior of the linear battery model under different operating conditions. In order to address this problem, CRONE control methodology is used. CRONE control scheme is a robust non-conservative control methodology that shows to be a good candidate for achieving the control targets for our case of study. Subsequently, the design and parametrization of the controller is explained. The simulation results are provided to prove the effectiveness of the CRONE controller. Simulation tests show that the developed controller meets the design requirements while tracking the reference signals in presence of model uncertainties.

A Real-Time SOSM Super-Twisting Technique for a Compound DC Motor Velocity Controller

In this paper, a real-time robust closed-loop control scheme for controlling the velocity of a Direct Current (DC) motor in a compound connection is proposed. This scheme is based on the state-feedback linearization technique combined with a second-order sliding mode algorithm, named super-twisting, for stabilizing the system and achieving control goals. The control law is designed to track a periodic square reference signal, being one of the most severe tests applied to closed-loop systems. The DC motor drives a squirrel-cage induction generator which represents the load; this generator must work above the synchronous velocity to deliver the generated power towards the grid. A classical proportional-integral (PI) controller is designed for comparison purposes of the time-domain responses with the proposed second-order sliding mode (SOSM) super-twisting controller. This robust controller uses only a velocity sensor, as is the case of the PI controller, as the time derivative of the velocity tracking variable is estimated via a robust differentiator. Therefore, the measurements of field current and stator current, the signal from a load torque observer, and machine parameters are not necessary for the controller design. The validation and robustness test of the proposed controller is carried out experimentally in a laboratory, where the closed-loop system is subject to an external disturbance and a time-varying tracking signal. This test is performed in real time using a workbench consisting of a DC motor—Alternating Current (AC) generator group, a DC/AC electronic drive, and a dSPACE 1103 controller board.

A New Procedure for Tuning an Allocator and Designing a Robust High-Level Control Law for Over-Actuated Systems.

This paper presents a new integrated procedure to tune a control law for over-actuated mechanical systems that may encounter singularities. First, the allocator that divides the commands among the actuators is tuned thanks to a genetic optimization algorithm, that computes the optimal values of its parameters. Then, the open-loop system including the allocator is identified and a robust closed-loop controller is computed with the structured H∞ method. Indeed, near singularities, the system and the allocator may create errors to deviate from these points or create delays to reconfigure the actuators, hence there is a need to create a closed-loop controller robust to these characteristics and to parameter variations. This procedure is carried out on a planar redundant robotic manipulator example. Simulations of the behaviours of the open-loop system with the allocator and in a closed loop are presented.

Accurate estimation for the closed-loop robust control using global modes

The control using global modes is well suited for the feedback stabilization of oscillatory fluid systems, since it takes into account the unstable dynamics responsible of perturbations growth. The unstable subspace is of small dimension and, most of the time, sufficient to obtain good control performances. But, when an estimator is considered, modeling the high-dimensional stable part is required to ensure consistency between measurement and estimation. The stable part is classically approximated by Galerkin projection onto a well suited basis. Balanced truncation modes or balanced POD are often preferred to global mode’s selection, mainly for their ability to approximate input-output behaviors. In this paper, we avoid the Galerkin approximation and we model the effect of the stable part in the observation by an integral term whose associated kernel is of small dimension and easy to pre-compute. This method guarantees the stability of the compensated system and improves its H∞ performance. Moreover, we give some guidelines to select additional stable modes to enhance estimation in a robust control perspective. The Ginzburg-Landau equation is used as a model problem having a behavior similar than that of fluid flows.

Control of Dynamic Limb Motion Using Fatigue-Resistant Asynchronous Intrafascicular Multi-Electrode Stimulation.

Asynchronous intrafascicular multi-electrode stimulation (aIFMS) of small independent populations of peripheral nerve motor axons can evoke selective, fatigue-resistant muscle forces. We previously developed a real-time proportional closed-loop control method for aIFMS generation of isometric muscle force and the present work extends and adapts this closed-loop controller to the more demanding task of dynamically controlling joint position in the presence of opposing joint torque. A proportional-integral-velocity controller, with integrator anti-windup strategies, was experimentally validated as a means to evoke motion about the hind-limb ankle joint of an anesthetized feline via aIFMS stimulation of fast-twitch plantar-flexor muscles. The controller was successful in evoking steps in joint position with 2.4% overshoot, 2.3-s rise time, 4.5-s settling time, and near-zero steady-state error. Controlled step responses were consistent across changes in step size, stable against external disturbances, and reliable over time. The controller was able to evoke smooth eccentric motion at joint velocities up to 8 deg./s, as well as sinusoidal trajectories with frequencies up to 0.1 Hz, with time delays less than 1.5 s. These experiments provide important insights toward creating a robust closed-loop aIFMS controller that can evoke precise fatigue-resistant motion in paralyzed individuals, despite the complexities introduced by aIFMS.

Just-in-Time-Learning based Extended Prediction Self-Adaptive Control for batch processes

This article presents a new Extended Prediction Self-Adaptive Control (EPSAC) algorithm based on the Just-in-Time Learning (JITL) method. In the proposed JITL-based EPSAC design, linearization of the process model is achieved by a set of local state-space models, each of which can be independently and simultaneously identified by the JITL method along the base trajectory. For the end-product quality control for a simulated semi-batch pH-shift reactive crystallization process where shrinking prediction and control horizons are essential, the proposed EPSAC algorithm not only simplifies the control weight tuning but also provides better and more robust closed-loop control performance than its previous counterpart.

Analysis of Current Sampling Errors in PWM VSI Drives

Current measurement and pulsewidth modulation (PWM) are critical components of modern current-controlled voltage source inverters. Current measurements enable accurate and robust closed-loop control of current, while PWM enables the efficient high-bandwidth regulation of the voltage. These two components do not operate independently, however. The synthesized voltage from PWM, a sequential series of discrete voltage levels, from a predefined finite set of possible levels, is only equivalent to the desired voltage on an average basis. As a result, the response of the electrical current to this synthesized voltage deviates from the response to the desired voltage. This deviation from the desired response, when combined with the standard synchronous sampling method, results in current measurement errors. This paper will present an analytical derivation of this current response deviation. This can be used to model the current measurement errors. A better understanding of this phenomenon will result in better design and control of power converter systems. The analytical work will be evaluated and verified using simulations and experimental measurements.

Experimental Validation of Robust Process Design and Control Based on Gaussian Mixture Densities

In this contribution, the effects of different degrees of uncertainty description are investigated experimentally using an exothermic chemical reaction with safety constraint on the temperature. For that purpose, two robust trajectories are designed that respect the artificially created uncertainties of the experiments either coarsely using a single multivariate normal distribution (1GMD) or in a more detailed fashion using a Gaussian mixture density (GMD) consisting of 32 multivariate normal densities (32GMD). For the optimization, the uncertainties are propagated using the unscented transformation. Both trajectories were run 71 times in an open-loop manner. The more detailed trajectory (32GMD) leads to a 9 % higher yield without increasing the risk of constraint violation. Furthermore, many experimental realizations of two robust closed-loop process control schemes are being compared. They differ again only in the degree of the underlying uncertainty description. Although the frequent corrections of the controller marginalize the advantage of a more detailed stochastic process prediction, the 4GMD-controller still allows for 3 % more educt conversion compared to the 1GMD-controller.

Exploiting short-term memory in soft body dynamics as a computational resource.

Soft materials are not only highly deformable, but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity and potentially infinitely many degrees of freedom. Here, we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way towards exploiting passive body dynamics for control of a large class of underactuated systems.

Optimal reorientation of asymmetric underactuated spacecraft using differential flatness and receding horizon control

This paper presents a novel method integrating nominal trajectory optimization and tracking for the reorientation control of an underactuated spacecraft with only two available control torque inputs. By employing a pseudo input along the uncontrolled axis, the flatness property of a general underactuated spacecraft is extended explicitly, by which the reorientation trajectory optimization problem is formulated into the flat output space with all the differential constraints eliminated. Ultimately, the flat output optimization problem is transformed into a nonlinear programming problem via the Chebyshev pseudospectral method, which is improved by the conformal map and barycentric rational interpolation techniques to overcome the side effects of the differential matrix’s ill-conditions on numerical accuracy. Treating the trajectory tracking control as a state regulation problem, we develop a robust closed-loop tracking control law using the receding-horizon control method, and compute the feedback control at each control cycle rapidly via the differential transformation method. Numerical simulation results show that the proposed control scheme is feasible and effective for the reorientation maneuver.

Robust Control of VO<formula formulatype="inline"><tex Notation="TeX">$_{\bf 2}$</tex></formula>-Coated Microbenders Using Self-Sensing Feedback

This paper presents the first studies on robust closed-loop deflection control of vanadium dioxide (VO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> )-based microactuators using self-sensing. The deflection output of the microactuator is estimated by VO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> resistance-based self-sensing through a high-order polynomial in order to eliminate the need for complicated external sensing mechanisms. An H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> robust controller is designed and implemented for precision deflection control, where uncertainties produced by the hysteresis between the deflection and the temperature input and the error in the self-sensing model are accommodated. The performance of the robust controller is tested in experiments under step and multisinusoidal reference inputs and compared to that of a proportional-integral-derivative (PID) controller. The robust controller outperforms the PID controller with 36% and 18% less tracking error for the step and multisinusoidal reference responses, respectively. To further show the robust performance of the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller, a multisinusoidal reference tracking experiment with simulated white noise current signal is conducted, where the error using robust control is 34% less than that with PID control.

Design of a robust quantitative feedback theory position controller for an ionic polymer metal composite actuator using an analytical dynamic model

Nowadays, ionic polymer metal composite actuators are widely used in many fields such as biometric, biomedical, and micro-manipulator devices. Although extensive research exists on control of the ionic polymer metal composite actuators, not much research has been done on robust control considering the nonlinear dynamics of the ionic polymer metal composite. In this study, for the first time, a closed-loop robust controller based on quantitative feedback theory is designed to overcome the actuation performance degradation of the ionic polymer metal composite actuators. First, an analytical electromechanical model is developed to fully describe dynamics of the flexible ionic polymer metal composite actuator. The model is based on the Euler–Bernoulli beam theory and includes structural damping to model viscoelastic behavior of the ionic polymer metal composite actuator. Considering the highly nonlinear and uncertain dynamics of the ionic polymer metal composite actuator, a feedback controller based on quantitative feedback theory is designed to suppress the arbitrary external disturbances and consistently track desired input. Results indicate that the robust quantitative feedback theory control techniques can significantly improve the ionic polymer metal composite performance against nonlinearity and parametric uncertainties.

Toward Movement Restoration of Knee Joint Using Robust Control of Powered Orthosis

Powered orthoses are external mechanical devices used to stabilize human limbs, to restore or to reinforce lost or weak functions of people with reduced mobility. The embodied actuators produce the necessary joint torques to compensate gravity and passive effort as well as to generate the intended human movements. Nonlinearities due to human orthosis coupling, as well as modeling errors, parameter uncertainties, and external disturbances, necessitate the use of a robust closed-loop controller in order to guarantee precise movement generation. This paper aims to present a new prototype of an actuated knee joint orthosis using a robust controller. This orthosis is designed to restore or to assist knee-joint movements of dependent people. Dynamic modeling of the lower limb/orthosis is presented, and its parameters are estimated using different techniques. Control strategies based on second-order sliding mode are applied, which show satisfactory performance compared to classical controllers in terms of tracking errors and robustness with respect to parameter uncertainties and external disturbances. Real-time experiments are conducted on healthy subjects to illustrate the efficiency of the proposed approach.