Massachusetts Institute of Technology, Cambridge, MA 02139, USA .
This paper proposes an adaptive controller for a class of multi-input multi-output (MIMO) plants where the number of outputs is larger than the number of inputs, an example of which is very-flexible aircraft (VFA). A dominant presence of model uncertainties and actuator anomalies necessitates an adaptive approach for control of VFA. The proposed controller, denoted as the adaptive SPR/LTR controller, combines a baseline observer-based design withloop transfer recovery (LTR) properties and an adaptive design based on strictly positive real (SPR) transfer functions. In addition to accommodating the absence of full state measurements, the controller includes a reference model that also plays the role of an observer through a closed-loop compo- nent. Conditions are delineated under which this controller, can guarantee asymptotic reference tracking, and the control design is validated using a VFA model around a single equilibrium flight condition with 707 states, 12 outputs and 2 control inputs. Simulation results show that the adaptive controller not only ensures stability but also recovers a nominal performance both in time domain and in frequency domain despite the presence of varying wing shape and actuator anomalies.
Abstract: The design, characterization and control of a novel 2-DoF MEMS nanopositioner is presented, with Z-shaped electrothermal actuators being used to position the device’s central stage. Whereas the more commonly-used V-shaped electrothermal actuator only allows displacements in one direction, the design of the Z-shaped beams used in the presented device allows two actuators to be coupled back-to-back to achieve bidirectional motion along each of the two axes. Testing of the device shows that stage displacements in excess of ±5 µm are achievable for both the x and y axes. The device features integrated displacement sensors based on polysilicon electrothermal heaters, which are supplied with an electrical bias voltage that results in Joule heating. The resistance of each heater varies depending on the position of the central stage, with two heaters being used per axis in a differential configuration. The displacement measurements are utilized as part of an implemented closed-loopcontrol scheme that uses both feedforward and feedback mechanisms based on the principle of internal model control. Experimental testing shows that the use of the controller enhances the static and dynamic performance of the system, with particular improvements being seen in the device’s reference tracking, response time and cross-coupling rejection.
C. Instructions given to the participants before each closed-loop trial
For both F_CL and B_CL conditions, participants were instructed to stand on the force plate, remain still, lightly touch the belt and close their eyes. Before each closed-loop trial, participants were told to: “Stand on this plate, put your index finger on this white tape, look at in front of you and then close your eyes. Remain as still as possible during the trial. The trial will last less than 2 minutes. I will tell you when the trial is finished so you can open your eyes and remove your finger.” Closing the eyes was expected to favor the use of the kinesthetic sensory information. Participants were asked to put the tip of their forefinger on a double-sided adhesive tape stuck on the flexiforce sensor before the beginning of the trial and maintain the contact between their finger and the belt for the duration of each trial (as seen in Fig. 1(b)). The physiotherapist verified visually that the participants’ forefinger stayed in contact with the belt during the trials. If the participant exceeded a force of 1N on the flexiforce sensor, an alarm sound was emitted. The subject was then asked to release the pressure on the belt while maintaining the contact between the sensor and his finger. After the end of the trial (80 seconds), participants were allowed to remove their finger from the sensor until the beginning of the next trial. PS patients and controls were asked to use the forefinger of their unaffected side or of their dominant hand respectively.
d Centre Automatique et Systemes, Mines ParisTech, Paris, France
In this paper, we develop three methods to achieve reliable closed-loop, tool face control for directional drilling operations. This is a necessary step to achieve closed-loop, automated directional guidance. Our algorithms combine existing industry top-drive controllers with new control approaches. The torsional model we use for the drill string has been field validated and takes into account the Coulomb friction between the drill string and the borehole. These distributed friction terms are either assumed known (or measured) or can be estimated using a state-observer. In this work, we improve such a state-observer to obtain an estimation of the tool face orientation in real-time. We then propose different approaches to control the tool face. The first method is based on a feed-forward control law. It uses the flatness of the model and the estimation of the orientation to generate an admissible trajectory which is then tracked. In the second procedure, we require a stable rotation off-bottom before smoothly changing the reference to zero to stop bit rotation. This change of reference induces a change of orientation that can be estimated and finally compensated by repeating the procedure. Finally, the last method uses a series of trapezoidal setpoint inputs – bumps – to calculate the change in downhole tool face per change in surface orientation before arriving at the correct tool face after three iterations. These three algorithms are illustrated in simulations of field scenarios and their effectiveness and limitations, depending on the reliability and availability of downhole orientation data, are discussed.
Series elasticity is examined with three models. First, it is generalized by using a minimal actuator model. This mathematical model consists of an ideal velocity source actuator, linear spring and proportional controller. Series elasticity is then demonstrated in two case studies of physical actuator systems. The first is a linear hydraulic piston with a servo valve and the second is an electric motor with a geared linear transmission. Both case studies have a linear spring and low complexity control systems. The case studies are analyzed mathematically and verified with physical hardware. A series elastic actuator under simple closed-loopcontrol is physically equivalent to a second order system. This means that an equivalent mass defined by the control system and physical parameters, is effectively in series with the physical spring connected to the actuator load. Non- dimensional analysis of the dynamics clarifies important parametric relationships into a few key dimensionless groups and aids understanding when trying to scale the actuators. The physical equivalent abstractions and non-dimensional dynamic equations help in the development of guidelines for choosing a proper spring stiffness given required force, speed and power requirements for the actuator.
Despite the significant progress in CLAD system design, further improvements should be possible. First, for each control signal a monotonic relationship between the signal and the anesthetic state is assumed or established, yet the neurophysiological mechanism of how each signal relates to the specific state is not known. Second, although BIS has been the most widely used control signal in CLAD studies, BIS computations require up to a 20- second delay to output a new value, making true real-time feedback not possible with this index . Third, the control target has often been specified as a range—say, a BIS between 40 and 60. Maintenance of the BIS within this range is considered successful control. Maintenance of the anesthetic state at a specific value of the control signal, as has been demonstrated in some studies , is more challenging but would represent a tighter level of control . Therefore, a plausible approach to improving CLAD system design is to identify neurophysiologically-based EEG signatures that relate directly to well-defined anesthetic states and that can be processed in real-time to achieve reliable individual control. We hypothesize that developing a CLAD system to control burst suppression would be a good starting point for studying the feasibility of these possible improvements. Burst suppression, an EEG pattern in which periods of bursts of electrical activity alternate with periods of isoelectricity, i.e. flatlines, (Fig. 1A), is a state of profound brain inactivation and unconsciousness seen in deep general anesthesia, hypothermia, significantly compromised brain development and coma [28, 29]. Burst suppression is a much studied anesthetic state. A long-standing interpretation is that burst-suppression represents an active thalamic stimulus being transmitted to a largely inactivated cortex . A recent modeling study has shown that burst-suppression likely arises when the brain rates of ATP production are insufficient to maintain the integrity of ATP-dependent potassium channels .
Recently, morphing wing system studies have branched out into new research directions. Extremely complex and catalogued as inter- and multidisciplinary studies, morphing wing studies continue to ‘push’ the science, up to the extreme boundaries of mathematics and physics. These multidisciplinary studies therefore require knowledge in the following disciplines: aerodynamics and computational fluid dynamics, aeroelasticity, automatic control, intelligent materials, signal detection using the latest miniaturized sensors, high computer-time calculations, wind tunnel and flight testing, instruments, and signal acquisition - these signals have such speed that they are raising serious problems for the existing calculus technology. Consequently, real-time system functioning is conditioned (in addition to other factors) by the obtaining of the best data processing algorithms, easy to implement software within the command and control unit. Fuzzy logic theories, which offer remarkable facilities, may therefore be used in these algorithms. They facilitate signal processing by allowing empirical models to be designed based on experimental data; and thus, the complex mathematical calculus currently in use can be avoided. In addition, fuzzy logic can be used to model highly non-linear, multidimensional systems, including those with parameter variations, or where the sensors’ signals are not accurate enough for other models. This research project included the following: optical sensor selection and testing for laminar-to-turbulent flow transition validation (by use of XFoil code and Matlab), smart material actuator modeling, aeroelasticity wing studies using MSC/Nastran, open loop and closedloop transition delay controller design, integration and validation on a wing equipped with SMAs and optical sensors.
Fig. 12. Syntax tree representation of an IPv4 address.
A. Tainted graph to syntax tree mapping
Starting with an initial set of seeds, we identify the fields in the input data that make good candidates for mutations. It is reasonable to assume that the target program will ignore some of the data provided in the message. For instance, headers like Subject: or User Agent: will be useless for a high-speed proxy that has to deliver the message no matter what the source is or what the subject is. But in the case of an end- user application, these fields can be useful for displaying information on the screen and thus informing the user about the message. Even further, filtering such fields according to what the target program executes will allow the generation of a testing strategy that reduces the number of malformed inputs based on their impact and discard all the mutations which generate messages that have no effect on the target.
The design of the control action follows the procedure described above (Section 3). First, it is found that, because the case is very unstable, tripping 2 critical machines 150 ms after the fault inception would not be sufficient to stabilize it. Figures 2a and 2b portray, respectively, the multi-machine swing curves and the δ-P OMIB curves of the totally stability-unconstrained system. Obviously, this is an extremely stressed system. Since the emergency action is insufficient to stabilize the case, the procedure of Section 3 continues with step 3: the new substitute margin is computed and the appropriate preventive generation rescheduling is decided in order to stabilize the operating conditions. The final result of the preventive stabilization procedure of the system with 5 critical machines indicates that their generation should be reduced from 4010 MW to 2415 MW.
_______________________________________________________________ This research is partially funded by IRT Saint Exupéry grant EPowerDrive.
Author Version – Paper published in IEEE TPEL - https://doi.org/10.1109/TPEL.2020.2995531
Abstract— This paper shows both theoretical and experimental analyses of a fully integrated CMOS active gate driver (AGD) developed to control the high dv/dt of GaN transistors for both 48 V and 400 V applications. To mitigate negative effects in the high- frequency spectrum emission, an original technique is proposed to reduce the dv/dt with lower switching losses compared to classical solutions. The AGD technique is based on a subnanosecond delay feedback loop, which reduces the gate current only during the dv/dt sequence of the switching transients. Hence, the dv/dt and di/dt can be actively controlled separately, and the trade-off between the dv/dt and E ON switching energy is optimized. Since GaN transistors have typical voltage switching times on the order of a few nanoseconds,
2 Reinforcement Learning
The idea that we learn by interacting with our environment is probably the first to occur to us when we think about the nature of learning. Reinforcement learning is learning what to do, i.e. how to map situations to actions, so as to maximize a reward signal (). The goal is to discover the actions which yield the most reward, by trying them out. In the most interesting and challenging case, actions may affect not only the immediate reward but also the next situation and all the subsequent rewards.
2 . GIPSA / LAG – Control System Department – Micro, nano sytems and SOC projects – Grenoble, France. E-mail: email@example.com
Abstract— A closed-loopcontrol approach for the dynamic
shaping of a microbeam by electrostatic actuation is described. Starting from a desired displacements reference vector of N small segments of the beam (representing the approximation of the continuous case), n controllers (n is the number of considered modes) output the stresses that must be distributed throughout the beam, on the N actuators. Because this reference may vary with time, the controllers are designed so that they accomplish good response dynamics, as well as performance and robustness specifications. The innovation in this method is that we control the dynamic coefficients associated to the modes of the microbeam and not directly the physical displacements in each small segment, which reduces the number of correctors from N to the number of n modes to control.
The disturbance considered here is a three-phase short-circuit followed by the tripping of one line to clear the fault. The lo- cation of the fault was chosen at random among a number of “dangerous” scenarios, for which the system is driven to loss of synchronism. Note however that to get “dangerous” scenar- ios the considered fault clearing time was quite large (150 ms); with modern circuit breakers it is possible to get clearing times of less than 50 ms (3 cycles).
Closed-loop MPC with Dense Visual SLAM - Stability through Reactive Stepping
Arnaud Tanguy 1,2 ∗ , Daniele De Simone 4 ∗ , Andrew I. Comport 1 , Giuseppe Oriolo 4 and Abderrahmane Kheddar 3,2
Abstract— Walking gaits generated using Model Predictive Control (MPC) is widely used due to its capability to handle several constraints that characterize humanoid locomotion. The use of simplified models such as the Linear Inverted Pendulum allows to perform computations in real-time, giving the robot the fundamental capacity to replan its motion to follow external inputs (e.g. reference velocity, footstep plans). However, usually the MPC does not take into account the current state of the robot when computing the reference motion, losing the ability to react to external disturbances. In this paper a closed- loop MPC scheme is proposed to estimate the robot’s real state through Simultaneous Localization and Mapping (SLAM) and proprioceptive sensors (force/torque). With the proposed control scheme it is shown that the robot is able to react to external disturbances (push), by stepping to recover from the loss of balance. Moreover the localization allows the robot to navigate to target positions in the environment without being affected by the drift generated by imperfect open-loopcontrol execution. We validate the proposed scheme through two different experiments with a HRP-4 humanoid robot.
IV. A CKNOWLEDGMENTS
This work was partly supported by Bpifrance within the Investment for the Future program in France.
V. C ONCLUSIONS
A VNS closed-loopcontrol system is proposed in order to regulate the heart rate of a sheep with induced heart failure, in a beat-to-beat basis. Due to the hardware constraints of the current version of the stimulator, only an on-off approach was implemented. Experimental results confirm that closed-loop VNS, with the tested parameter configurations, significantly modifies the spontaneous RR interval. Nevertheless, results showed significant RR oscillations, inherent to the on-off algorithm. Such oscillations may be reduced by implementing a more advanced control algorithm, which will automatically adapt other VNS parameters.