A short computational program was undertaken to evaluate the effectiveness of a closed-loop control strategy for the stabilization of an unstable bluff-body flow. In this effort, the non-linear one-dimensional Ginzburg–Landau wake model at 20% above the critical Reynolds number was studied. The numerical model, which is a non-linear partial differential equation with complex coefficients, was solved using the FEMLAB®/MATLAB® software packages and validated by comparison with published literature. At first, a model independent approach was attempted for wake suppression using feedback control. The closed-loop system was controlled using a conventional proportional-integral-derivative (PID) controller as well as a non-linear fuzzy controller. A single sensor is used for feedback, and the actuator is represented by altering the boundary conditions of the cylinder. Simulation results indicate that for a single sensor scheme, the increase in the sophistication of the control results in significantly shorter settling times. However, there is only a marginal improvement concerning the suppression of the wake at higher Reynolds numbers. The feedback control design was then augmented by switching over to a model-dependent controller. Based on computationally generated data obtained from solving the unforced wake, a low-dimensional model of the wake was developed and evaluated. The low-dimensional model of the unforced Ginzburg–Landau equation captures more than 99.8% of the kinetic energy using just two modes. Two sensors, placed in the absolutely unstable region of the wake, are used for real-time estimation of the first two modes. The estimator was developed using the linear stochastic estimation scheme. Finally, the loop is closed using a PID controller that provides the command input to the variable boundary conditions of the model. This method is relatively simple and easy to implement in a real-time scenario. The control approach, applied to the 300 node FEMLAB® model at 20% above the unforced critical Reynolds number stabilizes the entire wake. Compared to the model-independent controllers, the controller based on the low-dimensional model is far more effective in the suppression of the wake at higher Reynolds numbers. Furthermore, while the latter approach employs only the estimated temporal amplitude of the first mode of the imaginary part of the amplitude, all higher modes are stabilized. This suggests that the higher order modes are caused by a secondary instability that is suppressed once the primary instability is controlled.
The effectiveness of a small array of body-mounted sensors, for estimation and eventually feedback flow control of a D-shaped cylinder wake is investigated experimentally. The research is aimed at suppressing unsteady loads resulting from the von-Kármán vortex shedding in the wake of bluff-bodies at a Reynolds number range of 100–1,000. A low-dimensional proper orthogonal decomposition (POD) procedure was applied to the stream-wise and cross-stream velocities in the near wake flow field, with steady-state vortex shedding, obtained using particle image velocimetry (PIV). Data were collected in the unforced condition, which served as a baseline, as well as during influence of forcing within the “lock-in” region. The design of sensor number and placement was based on data from a laminar direct numerical simulation of the Navier-Stokes equations. A linear stochastic estimator (LSE) was employed to map the surface-mounted hot-film sensor signals to the temporal coefficients of the reduced order model of the wake flow field in order to provide accurate yet compact estimates of the low-dimensional states. For a three-sensor configuration, results show that the estimation error of the first two cross-stream modes is within 20–40% of the PIV-generated POD time coefficients. Based on previous investigations, this level of error is acceptable for a moderately robust controller required for feedback flow control.
The ability to spatially alter both the amount of body force along the span of a plasma actuator and the angle of the resulting jet relative to the surface has been demonstrated. A dielectric barrier discharge plasma actuator consists of two electrodes separated by a dielectric barrier, which imparts momentum to the surrounding fluid parallel to the dielectric. To investigate a technique to shape the spanwise body force created by the plasma actuator, a control volume momentum balance was used. By shaping the buried electrode along the span of the actuator, the local volume of plasma generated can be controlled, which is related to the local body force. Pressure measurements were taken in the boundary layer behind the actuator to calculate the momentum imparted to the flow at various spanwise locations corresponding to different electrode widths. Particle image velocimetry data were then used to show that spatially varying, steady jets could be created with the use of only one actuator by varying the width of the buried electrode in a quiescent flow. The angle of the jet created, relative to the dielectric, by a plasma synthetic jet is also investigated. By pointing two plasma actuators at each other, an inverted impinging jet can be created as a result of the two independent jets colliding. By altering the strength of one of the jets relative to the other, the angle of separation can be changed. Particle image velocimetry data were taken to show the effects of altering the voltage (strength) applied to one of the actuators relative to the other. It was found that, with this method, jet vectoring could be achieved. The angle of the jet could be controlled a full 180 deg through small changes in the voltage applied to the electrodes, also in a quiescent flow.
Over the past 10 years there has been a growing need to introduce closed-loop control technology for vibration suppression of buildings subject to wind or earthquake disturbances. This paper deals with the investigation of the effectiveness of a fuzzy logic based time variable damping tuned mass damper (TMD) on a building structure undergoing free and forced vibrations. The uniqueness of this approach is the application of a robust, nonlinear fuzzy based controller to emulate a time-optimal control strategy. Fuzzy logic based time variable damping is introduced into a semi-active TMD in order to enhance its performance in the vibration suppression of buildings. First, a single story structure for three different vibration suppression approaches is studied. The fuzzy logic based time variable damping TMD (fuzzy TMD) is compared to the baseline passive TMD as well as a conventional proportional-derivative (PD) controller. Forced vibration is introduced using a resonant harmonic sinusoidal excitation (i.e. same frequency as the fundamental frequency of the structure). Finally, the fuzzy TMD is compared to the baseline for the free vibration of a 15 story structure. For both structures studied, MATLAB based simulation results show that the passive TMD and the PD, both constant gain approaches, provide similar results whereas the fuzzy TMD yields half the settling time. This effort clearly demonstrates the potential of a variable gain (damping) strategy for the vibration suppression of buildings.
UAV’s are being increasingly used today than ever before in both military and civil applications. A certain level of autonomy is imperative to the future of UAV’s. A quadrotor is a helicopter with four rotors, that make it more stable; but more complex to model and control. Characteristics that provide a clear advantage over other fixed wing UAV’s are VTOL and hovering capabilities as well as a greater maneuverability. Fuzzy logic control has been chosen over conventional control methods as it can deal effectively with highly nonlinear systems, allows for imprecise data and is extremely modular. The objective of this research endeavor is to present the steps of designing, building and simulating an intelligent flight control module for a quadrotor UAV. Validation of the math model developed is discussed using actual flight data. Excellent attitude tracking is demonstrated for near hover flight regimes. System design is comprehensively dealt with. The responses are analyzed and future work involving hardware-in-the-loop simulations is proposed.
This study introduces the technique of Genetic Fuzzy Trees (GFTs) through novel application to an air combat control problem of an autonomous squadron of Unmanned Combat Aerial Vehicles (UCAVs) equipped with next-generation defensive systems. GFTs are a natural evolution to Genetic Fuzzy Systems, in which multiple cascading fuzzy systems are optimized by genetic methods. In this problem a team of UCAV's must traverse through a battle space and counter enemy threats, utilize imperfect systems, cope with uncertainty, and successfully destroy critical targets. Enemy threats take the form of Air Interceptors (AIs), Surface to Air Missile (SAM) sites, and Electronic WARfare (EWAR) stations. Simultaneous training and tuning a multitude of Fuzzy Inference Systems (FISs), with varying degrees of connectivity, is performed through the use of an optimized Genetic Algorithm (GA). The GFT presented in this study, the Learning Enhanced Tactical Handling Algorithm (LETHA), is able to create controllers with the presence of deep learning, resilience to uncertainties, and adaptability to changing scenarios. These resulting deterministic fuzzy controllers are easily understandable by operators, are of very high performance and efficiency, and are consistently capable of completing new and different missions not trained for.
A general methodology has been developed for the design of a robust control law for a family of lightly damped second order problems. In this research effort, the passivity approach has been extended to systems having non-collocated input/output pairs by introducing an observer that incorporates the nominal dynamical model of the plant. The developed passive observer-based control law emulates numerous dynamic vibration absorbers which are tuned to a targeted frequency using classical methods and the tuning ratios are time-invariant. However, the uniqueness of this approach is that the damping parameters of the emulated absorbers are continuously varied by means of a fuzzy logic control algorithm to provide near minimum-time suppression of vibration. The developed approach is applied to both several benchmarks in the field of structural dynamics as well as experiments using piezo-ceramic sensors and actuators. Results show that this methodology provides stability and performance robustness on the one hand as well as requiring relatively low amount of actuation authority for desired nominal plant closeloop behavior.