Control Design And Simulation Module Labview 2015 22
This module isderived from thecourse "Intro to Mechatronics" at Lawrence Technological University and was developed through seed funding from theCAAT. This module contains a PowerPoint presentation and LabVIEW simulation file. In the presentation the following concepts are discussed: wheel/tire-terrain interactive dynamics (wheel loads, effective rolling radius, and power balance),inverse dynamics-based control (changing rolling conditions and angular velocity control),control strategies (loops and algorithms), andcontrol algorithms in the LabVIEW environment.
control design and simulation module labview 2015 22
Students explore the use of wind power in the design, construction and testing of "sail cars," which, in this case, are little wheeled carts with masts and sails that are powered by the moving air generated from a box fan. The scientific method is reviewed and reinforced with the use of controls and variables, and the engineering design process is explored. The focus of the activity is on renewable energy, as well as the design, testing and redesign of small cars made from household materials. The activity (and an extension worksheet) includes the use of kinematic equations using distance, time traveled and speed to enforce exponents and decimals.
First-level and second-level compliant interconnect structures are being pursued in universities and industries to accommodate the differential displacement induced by the coefficient of thermal expansion mismatch between the die and the substrate or between the substrate and the board. The compliant interconnects mechanically decouple the die from the substrate or the substrate from the board, and thus reduce the thermally induced stresses in the assembly. This paper presents drop-test experimental and simulation data for scaled-up prototype of compliant interconnects. The simulations were based on Input-G method and performed using ANSYS finite element software for varying drop heights. In parallel to the simulations, scaled-up compliant polymer interconnects sandwiched between a polymer die and a polymer substrate were fabricated using three-dimensional (3D) printing, and this fabrication provides a quick low-cost alternative to cleanroom fabrication. The prototype of the assembly was subjected to drop tests from varying drop heights. The response of the assembly during drop testing was captured using strain gauges and an accelerometer mounted on the prototype. The data from the experiments were compared with the predictions from the simulations. Based on such simulations, significant insight into the behavior of compliant interconnects under impact loading was obtained, which could be used for reliable design of compliant interconnect under impact loading. Both the experimental and simulation data reveal that the compliant interconnects are able to reduce the strains that transfer from substrate to die by one-order.
The passive vibration isolation system has received considerable academic attention owing to its reliability. Zhang et al. developed a passive vibration isolation system using multiple coordinated dampers with a Stewart platform. The simulation proved that a vibration isolation effect of 28 dB could be achieved above 100 Hz; the resonance peak amplitude was approximately 4.27 dB . Kamesh et al. designed a passive vibration isolator based on a folded beam that was experimentally validated; it could suppress vibrations above 30 Hz [15,16]. However, owing to their structural features, the passive platform is difficult to further improve vibrations at resonant frequencies. Therefore, semi-active vibration isolation techniques are also widely studied. Memet et al. developed a six-degree-of-freedom parallel isolated platform using a coil-over magnetorheological (MR) damper to reduce the amplification of resonant peaks by varying the damping of the system . Xu et al. used electromagnetic springs to vary the equivalent stiffness of the system and, thus, the resonant frequency . Semi-active vibration isolation reduces power requirements and improves stability. Both passive and semi-active control perform unfavorably for low-frequency, and the suppression effect at the resonant peak needs further improvement. If the performance of these platforms is improved by reducing the resonant frequency, it will lead to insufficient dynamic stiffness and affect the stability of the system .
In this study, a state-differential feedback control strategy with a disturbance observer (DOB)-based linear quadratic regulator (LQR) is proposed for further suppressing microvibrations to meet the vibration isolation requirements of an optical reference cavity. The manuscript is organized into four sections as follows: (1) the problems to be solved in this study, including the demand of the optical reference cavity and the equation of the individual vibration isolation module; (2) the design principle of the controller and the results of the simulation verification; (3) the experimental verification through the active vibration isolation system to confirm the feasibility and effectiveness of the designed controller; and (4) the summary of the main points of the study in the conclusion.
The relationship between the optical reference cavity and verification index under the vibration isolation performance is discussed in this section. Then, the control system is described, and the general framework of the proposed control strategy with a single vibration isolation module is presented as an example.
The system used in this study was a self-developed active vibration isolation system . The structural arrangement of the active vibration isolation platform (AVIS) is shown in Figure 2. The entire system consisted of a foundation platform, payload platform, and eight vibration isolation modules between them. These modules were arranged orthogonally, with half along the direction of gravity, and the other half along the horizontal direction. Each module contained coaxially mounted accelerometers and VCMs for collecting signals and driving control forces. Structurally, as shown in the enlarged part of Figure 2, they can be considered as a spring-mass-damper system module. The system uses a decentralized control strategy, where each module is controlled independently. In this way, they can be considered as a closed-loop single-input single-output (SISO) system based on sensor measurements and actuator outputs. Each module has the same structure and control loop, differing only in the parameters of the controller.
A schematic of a single vibration isolation module is shown in Figure 3. The equivalent stiffness, damping, and mass are k, c, and m, respectively; these form the passive structure of the mass-spring-damper model. The effect of the noise a1 transmitted from the base plane noise a0 to the payload platform was reduced by applying the active control force Fc provided by the VCM; z0 and z1 were the base platform and payload platform displacements, respectively; and Fd could be regarded as a disturbance force from the base platform. The force balance equation is expressed as follows:(3)mz1+cz1+kz1=cz0+kz0+Fc=Fd+Fc,
The active vibration isolation system was controlled by acceleration feedback. Considering the possible drift of the measured signal in the low-frequency band, a state-differential feedback controller with an LQR was designed in this study to calculate the control quantity u. Furthermore, the disturbance force from the base plane was estimated with the assistance of a DOB to ensure the suppression effect and control accuracy of the payload platform acceleration.
In Figure 4, Fk is the force calculated by the LQR controller K, which is obtained from the previous section; Fd is the disturbance force transmitted from the base platform; G(s) represents the real uncertainties of the plant of the system; Gn(s) is the nominal model; Q(s) is the selected low-pass filter; and U is the final output control voltage. The measured signal y of the system contains the joint effects of the control and disturbance forces for the plant G(s), which can both be considered control inputs in the disturbance observer. The equivalent disturbance is estimated by designing the nominal model Gn(s) and the filter Q(s), and that is imported into the controller as compensation to achieve the suppression of the disturbance. Using Equation (3), the transfer function of the acceleration of the payload platform and the applied combined force can be written as:(15)G(s)=s2x(s)Fc(s)+Fd(s)=s2x(s)F(s)=s2ms2+cs+k,
In principle, a suitable low-pass filter Q(s) is required to ensure that the overall transfer function is positive and thereby enable the DOB to estimate the direct disturbance by inverse nominal model calculation. The order of the filter should be suitably designed because it affects the stability of the DOB and is not conducive to real-time control. In this study, the force balance equation is satisfied as a positive-definite inverse model function; so, the low-pass filter can be chosen more conservatively as only a first-order filter:(16)Q(s)=1τs+1, where τ is the time constant of the filter. The DOB can have a suppression effect in a wide frequency range; it was designed with τ=0.001.
Generally, it is difficult for the parameters of the designed Gn(s) to be the same as those in the real plant G(s). However, according to the conclusions mentioned by Hyungbo, robust stability can be achieved for bounded uncertainty models if the uncertainty system is a minimum phase system, provided that the outer-loop controller is stable . The real uncertainty model G(s) used in this study had open-loop zeros in the left half-plane of s, i.e., which are minimum-phase systems. Additionally, the outer-loop LQR controller designed could remain stable; the effects caused by parameter uncertainty could be neglected.
The control loop is shown in Figure 5. The system was subjected to disturbance forces transmitted from the base platform and control forces driven by the VCM, where the control forces were obtained through a combination of disturbances calculated by the LQR controller and DOB. Simulation experiments were conducted on a single vibration isolation module to compare the dynamic characteristics of the passive isolator and active control. The simulated physical parameters were similar to those of the real system. The vibration signal in the time domain and PSD obtained from the experimental results are shown in Figure 6. 350c69d7ab