Magnetic Actuators and Suspension for Space Vibration Control

The research on microgravity vibration isolation performed at the University of Virginia is summarized. This research on microgravity vibration isolation was focused in three areas: (1) the development of new actuators for use in microgravity isolation; (2) the design of controllers for multiple-degree-of-freedom active isolation; and (3) the construction of a single-degree-of-freedom test rig with umbilicals. Described are the design and testing of a large stroke linear actuator; the conceptual design and analysis of a redundant coarse-fine six-degree-of-freedom actuator; an investigation of the control issues of active microgravity isolation; a methodology for the design of multiple-degree-of-freedom isolation control systems using modern control theory; and the design and testing of a single-degree-of-freedom test rig with umbilicals

Active suspension control of electric vehicle with in-wheel motors

In-wheel motor (IWM) technology has attracted increasing research interests in recent years due to the numerous advantages it offers. However, the direct attachment of IWMs to the wheels can result in an increase in the vehicle unsprung mass and a significant drop in the suspension ride comfort performance and road holding stability. Other issues such as motor bearing wear motor vibration, air-gap eccentricity and residual unbalanced radial force can adversely influence the motor vibration, passenger comfort and vehicle rollover stability. Active suspension and optimized passive suspension are possible methods deployed to improve the ride comfort and safety of electric vehicles equipped with inwheel motor. The trade-off between ride comfort and handling stability is a major challenge in active suspension design. This thesis investigates the development of novel active suspension systems for successful implementation of IWM technology in electric cars. Towards such aim, several active suspension methods based on robust H∞ control methods are developed to achieve enhanced suspension performance by overcoming the conflicting requirement between ride comfort, suspension deflection and road holding. A novel fault-tolerant H∞ controller based on friction compensation is in the presence of system parameter uncertainties, actuator faults, as well as actuator time delay and system friction is proposed. A friction observer-based Takagi-Sugeno (T-S) fuzzy H∞ controller is developed for active suspension with sprung mass variation and system friction. This method is validated experimentally on a quarter car test rig. The experimental results demonstrate the effectiveness of proposed control methods in improving vehicle ride performance and road holding capability under different road profiles. Quarter car suspension model with suspended shaft-less direct-drive motors has the potential to improve the road holding capability and ride performance. Based on the quarter car suspension with dynamic vibration absorber (DVA) model, a multi-objective parameter optimization for active suspension of IWM mounted electric vehicle based on genetic algorithm (GA) is proposed to suppress the sprung mass vibration, motor vibration, motor bearing wear as well as improving ride comfort, suspension deflection and road holding stability. Then a fault-tolerant fuzzy H∞ control design approach for active suspension of IWM driven electric vehicles in the presence of sprung mass variation, actuator faults and control input constraints is proposed. The T-S fuzzy suspension model is used to cope with the possible sprung mass variation. The output feedback control problem for active suspension system of IWM driven electric vehicles with actuator faults and time delay is further investigated. The suspended motor parameters and vehicle suspension parameters are optimized based on the particle swarm optimization. A robust output feedback H∞ controller is designed to guarantee the system’s asymptotic stability and simultaneously satisfying the performance constraints. The proposed output feedback controller reveals much better performance than previous work when different actuator thrust losses and time delay occurs. The road surface roughness is coupled with in-wheel switched reluctance motor air-gap eccentricity and the unbalanced residual vertical force. Coupling effects between road excitation and in wheel switched reluctance motor (SRM) on electric vehicle ride comfort are also analysed in this thesis. A hybrid control method including output feedback controller and SRM controller are designed to suppress SRM vibration and to prolong the SRM lifespan, while at the same time improving vehicle ride comfort. Then a state feedback H∞ controller combined with SRM controller is designed for in-wheel SRM driven electric vehicle with DVA structure to enhance vehicle and SRM performance. Simulation results demonstrate the effectiveness of DVA structure based active suspension system with proposed control method its ability to significantly improve the road holding capability and ride performance, as well as motor performance

Magnetic Microrobot Locomotion in Vascular System Using A Combination of Time Delay Control and Terminal Sliding Mode Approach

This thesis deals with designing a control law for trajectory tracking. The target is to move a microrobot in a blood vessel accurately. The microrobot is made of a ferromagnetic material and is propelled by a magnetic gradient coil. The controller combines time delay control (TDC) and terminal sliding mode (TSM) control. TDC allows deriving a control law without prior knowledge of the plant. As the system is a nonlinear function which also includes uncertainties and unexpected disturbance, TDC gives a benefit of less effort needed compared to model-based controller. Meanwhile, TSM term adds accuracy which it compensates TDC estimation error and also adds robustness against parameter variation and disturbance. In addition, anti-windup scheme acts as a support by eliminating the accumulated error due to integral term by TDC and TSM. So, the proposed controller can avoid actuator saturation problem caused by windup phenomenon. Simulations are conducted by copying a realistic situation. Accuracy and robustness evaluations are done in stages to see how each terms in a control law give an improvement and to see how an overall controller performs. ⓒ 2014 DGISTI. INTRODUCTION 1 -- 1.1. BACKGROUND 1 -- 1.2. RELATED RESEARCH 3 -- 1.3. OBJECTIVE 4 -- 1.4. SPECIFICATION 4 -- 1.5. SCOPE 5 -- 1.6. OVERVIEW 5 -- II. METHOD 6 -- 2.1. TIME DELAY CONTROL 6 -- 2.2. TERMINAL SLIDING MODE 9 -- 2.3. ANTI-WINDUP SCHEME 11 -- 2.4. PRACTICAL APPROACH 14 -- 2.4.1. FEEDBACK SIGNAL 14 -- 2.4.2. CONTROLLER GAIN SELECTION 15 -- 2.4.3. MEASUREMENT NOISE 16 -- 2.5. ADVANTAGES AND DRAWBACKS 16 -- III. RESULTS 17 -- 3.1. SIMULATION SETUP 17 -- 3.1.1. PLANT MODELING 18 -- 3.1.2. ACTUATOR AND POSITION SENSOR MODELING 20 -- 3.1.3. TRAJECTORY 21 -- 3.1.4. SIMULATION PARAMETER 21 -- 3.1.5. CONTROLLER TARGET 24 -- 3.2. ACCURACY AND ROBUSTNESS EVALUATION 24 -- 3.3. ANTI-WINDUP SCHEME EVALUATION 32 -- 3.4. SOLUTION FOR MEASUREMENT NOISE 35 -- 3.5. 2D SIMULATION 46 -- CONCLUSION AND FUTURE WORK 49 -- REFERENCES 50 -- 요 약 문(ABSTRACT IN KOREAN) 52이 논문은 경로 추적을 위한 컨트롤 법을 설계한 것이다. 목표는 혈관 내에서 정확하게 마이크로 로봇의 움직이는 것이다. 마이크로 로봇은 강자성체 물질로 만들어져 있고 자기장에 의해서 추진 된다. 컨트롤러는 시간지연제어기법(time delay control)과 terminal sliding 컨트롤을 함께 사용하였다. TDC는 플랜트에 대한 선행 지식 없이 적용할 수 있다. 시스템이 불확실함과 예상치 못한 외란을 포함하고 있는 비선형 일 때 TDC는 모델 기반의 컨트롤러에 비해 적은 노력이 드는 장정이 있다. 한편, TSM은 정확도를 더하여 TDC의 주정에러를 보상하고 또한 매개변수의 변화와 외란에 반한 견고함을 더한다. 게다가 안티 와인드 업은 TDC와 TSM의 적분 때문에 축적되는 에러를 제거하는 역할을 한다. 제안한 컨트롤러는 와인드업 현상에 의한 작동기의 포화현상을 피할 수 있다. 시뮬레이션은 실제 현상을 따라 시행되었다. 정확도와 견고함 평가는 전체적인 컨트롤러가 어떻게 수행하는가를 보는 것과 각각 컨트롤 방법이 주는 개선점을 보는 단계로 실시하였다. ⓒ 2014 DGISTMasterdCollectio

Advanced suspension system using magnetorheological technology for vehicle vibration control

In the past forty years, the concept of controllable vehicle suspension has attracted extensive attention. Since high price of an active suspension system and deficiencies on a passive suspension, researchers pay a lot attention to semi-active suspension. Magneto-rheological fluid (MRF) is always an ideal material of semi-active structure. Thanks to its outstanding features like large yield stress, fast response time, low energy consumption and significant rheological effect. MR damper gradually becomes a preferred component of semi-active suspension for improving the riding performance of vehicle. However, because of the inherent nonlinear nature of MR damper, one of the challenging aspects of utilizing MR dampers to achieve high levels of performance is the development of an appropriate control strategy that can take advantage of the unique characteristics of MR dampers. This is why this project has studied semi-active MR control technology of vehicle suspensions to improve their performance. Focusing on MR semi-active suspension, the aim of this thesis sought to develop system structure and semi-active control strategy to give a vehicle opportunity to have a better performance on riding comfort. The issues of vibration control of the vehicle suspension were systematically analysed in this project. As a part of this research, a quarter-car test rig was built; the models of suspension and MR damper were established; the optimization work of mechanical structure and controller parameters was conducted to further improve the system performance; an optimized MR damper (OMRD) for a vehicle suspension was designed, fabricated, and tested. To utilize OMRD to achieve higher level of performance, an appropriate semi-active control algorithm, state observer-based Takagi-Sugeno fuzzy controller (SOTSFC), was designed for the semi-active suspension system, and its feasibility was verified through an experiment. Several tests were conducted on the quarter-car suspension to investigate the real effect of this semiactive control by changing suspension damping. In order to further enhance the vibration reduction performance of the vehicle, a fullsize variable stiffness and variable damping (VSVD) suspension was further designed, fabricated, and tested in this project. The suspension can be easily installed into a vehicle suspension system without any change to the original configuration. A new 3- degree of freedom (DOF) phenomenological model to further accurately describe the dynamic characteristic of the VSVD suspension was also presented. Based on a simple on-off controller, the performance of the variable stiffness and damping suspension was verified numerically. In addition, an innovative TS fuzzy modelling based VSVD controller was designed. The TS fuzzy modelling controller includes a skyhook damping control module and a state observer based stiffness control module which considering road dominant frequency in real-time. The performance evaluation of the VSVD control algorithm was based on the quarter-car test rig which equipping the VSVD suspension. The experiment results showed that this strategy increases riding comfort effectively, especially under off-road working condition. The semi-active control system developed in this thesis can be adapted and used on a vehicle suspension in order to better control vibration

State of the art of control schemes for smart systems featuring magneto-rheological materials

This review presents various control strategies for application systems utilizing smart magneto-rheological fluid (MRF) and magneto-rheological elastomers (MRE). It is well known that both MRF and MRE are actively studied and applied to many practical systems such as vehicle dampers. The mandatory requirements for successful applications of MRF and MRE include several factors: advanced material properties, optimal mechanisms, suitable modeling, and appropriate control schemes. Among these requirements, the use of an appropriate control scheme is a crucial factor since it is the final action stage of the application systems to achieve the desired output responses. There are numerous different control strategies which have been applied to many different application systems of MRF and MRE, summarized in this review. In the literature review, advantages and disadvantages of each control scheme are discussed so that potential researchers can develop more effective strategies to achieve higher control performance of many application systems utilizing magneto-rheological materials

Adaptive, Intelligent Methods for Real Time Structural Control and Health Monitoring

By framing the structural health monitoring and control problem as being one of enhancing structural system intelligence, novel solutions can be achieved through applications of computational strategies that mimic human learning and attempt to replicate human response to sensory feedback. This thesis proposes several new methods which promote adaptive, intelligent decision making by structural systems relying on sensory feedback and actuator compensation. Four significant contributions can be found in this thesis study. The first method employs an adaptable subclass of Artificial Neural Networks (ANNs), called Radial Basis Function Networks (RBFNs) for robust control in the presence of sensory failure. The second method exploits this computationally efficient network to detect and isolate system faults in real time. The third algorithm utilizes an RBFN to effectively linearize the nonlinear actuator dynamics of a Magnetorheological (MR) damper, thereby improving control of the semiactive device. Lastly, an open loop observer is implemented experimentally to both detect damage and act as a trigger for control of the newly developed Adaptive Length Pendulum-Smart Tuned Mass Damper (ALP-STMD). Some limitation of existing algorithms in the field of real time structural health monitoring and control are that they rely heavily on fixed parameter methods, assume standard linear time invariant assumptions, or mandate accurate modeling of system dynamics. By embedding the proposed reasoning and decision making algorithms into the feedback methodology and design, greater generalization and system adaptivity is possible. Specifically, the proposed methods develop novel solutions for adaptive neural control, fault (sensor failure) tolerant control, real time damage detection, adaptive dynamic inversion, and control applications for STMDs. The neural network adaptive control formulation is successful in rejecting first mode disturbances despite online sensor failure. It is also capable of improving the performance of a baseline Hoc controller in the presence of sensor failure and earthquake ground motion. The proposed fault tolerant controller is validated on a two degree of freedom shear frame subjected to six earthquake records. Furthermore, this application involves the use of piezoelectric patches as sensors and actuators. The RBFN algorithm in combination with an open loop observer is capable of both detecting and isolating stiffness degradation and recovery in multi-degree of freedom systems in real time. The method is validated on experimental data taken from online damage tests using the Semi-Active Independent Variable Stiffness (SAIVS) device. Other validations involve simulations on a two degree of freedom system and a ten degree of freedom system with both independent and coupled damage case scenarios. In all scenarios, the RBFN is capable of identifying the length of time and degree of freedom in which stiffness variation occurred. A neural network formulation is developed to perform dynamic inversion for semiactive control of an MR damper. The MR damper acts as a base isolator in a scaled two story building. Both the building and damper models were based on tests performed at Rice University. The control performance of the adaptive RBFN dynamic inversion method is compared to both passive-off and passive-on methods of semiactive control for MR dampers. The last contribution serves to combine both real time structural health monitoring and control in a proof of concept experimental study. An open loop observer is used to trigger an ALP -STMD device in the presence of base excitation and stiffness damage. The stiffness damage is generated from strategically regulating the current applied to Shape Memory Alloy (SMA) braces in a two degree of freedom shear frame. Once damage exceeds a predefined threshold, the ALP-STMD uses a another SMA to adjust its pendulum length to tune in real time to the dominant pulse present in the base excitation

Vibration Suppression in Flexible Structures using Hybrid Active and Semi-active Control

This thesis presents a new hybrid active and semi-active control method for vibration suppression in flexible structures. The method uses a combination of a semi-active device and an active control actuator situated elsewhere in the structure to suppress vibrations. The key novelty is to use the hybrid controller to enable the semi-active device to achieve a performance as close to a fully active device as possible. This is accomplished by ensuring that the active actuator can assist the semi-active device in the regions where energy is required. Also, the hybrid active and semi-active controller is designed to minimise the switching of the semi-active controller. The control framework used is the immersion and invariance control technique in combination with a sliding mode control. A two degree-of-freedom system with lightly damped resonances is used as an example system. Both numerical and experimental results are generated for this system and then compared as part of a validation study. The experimental system uses hardware-in-the-loop simulation to simulate the effect of both the degrees-of-freedom. The results show that the concept is viable both numerically and experimentally, and improved vibration suppression results can be obtained for the semi-active device that approaches the performance of an active device. To illustrate the effectiveness of the proposed hybrid controller, it is implemented to keep the contact force constant in the pantograph-catenary system of high-speed trains. A detailed derivation is given after which the simulation results are presented. Then a method to design a reduced order observer using an invariant manifold approach is proposed. The main advantage of this approach is that it enables a systematic design approach, and (unlike most nonlinear observer design methods), it can be generalised over a larger class of nonlinear systems. The method uses specific mapping functions in a way that minimises the error dynamics close to zero. Another important aspect is the robustness property which is due to the manifold attractivity: an important feature when an observer is used in a closed loop control system. The observer design is validated using both numerical simulations and hardware-in-the-loop testing. The proposed observer is then compared with a very well known nonlinear observer based on the off-line solution of the Riccati equation for systems with Lipschitz type nonlinearity. In all cases, the performance of the proposed observer is shown to be excellent

A neural network-based inversion method of a feedback linearization controller applied to a hydraulic actuator

In this work, we use a neural network as a substitute for the traditional analytic functions employed as an inversion set in feedback linearization control algorithms applied to hydraulic actuators. Although very efective and with strong stability guarantees, feedback linearization control depends on parameters that are difcult to determine, requiring large amounts of experimental efort to be identifed accurately. On the other hands, neural networks require little efort regarding parameter identifcation, but pose signifcant hindrances to the development of solid stability analyses and/or to the processing capabilities of the control hardware. Here, we combine these techniques to control the positioning of a hydraulic actuator, without requiring extensive identifcation procedures nor losing stability guarantees for the closed-loop system, at reasonable computing demands. The efectiveness of the proposed method is verifed both theoretically and by means of experimental results

Comparison of the ride performance of an integrated suspension model

Vehicle suspension is one of the important components to reduce vibration from the road. The vehicle seat suspension acts as another component to provide ride comfort, especially to reduce driver fatigues for long hour’s driving. In this paper, the ride comfort is therefore studied based on the integrated suspension model which includes vehicle chassis suspension, seat suspension and driver model. A four-DOF mathematical model is presented. The hydraulic actuator is introduced as well. Three controllers, including skyhook damper control, slide model control (SMC) and fuzzy logical control (FLC), are applied to the semi-active/active suspension with passive seat suspension. To improve the ride comfort further, combination the best performance of ride comfort from active chassis suspension, the semi-active seat suspension is then designed. The ride performance is evaluated based on driver deformation and acceleration