In this study, the design of adaptive backstepping sliding mode control (ABSMC) has been developed for vibration suppression of earth-quaked building supported by magneto-rheological (MR) damper. The control and adaptive laws developed based on ABSMC methodology has been established according to stability analysis based on Lyupunov theorem. A Single degree of freedom (SDOF) building system has been considered and the earthquake acceleration data used in performance analysis of the proposed controller is based on El Centro Imperial Valley Earthquake. The ABSMC has been compared to classical sliding mode control in terms of vibration suppression in the controlled system subjected to earthquake. The performance of proposed controller has been assessed via computer simulation, which showed its effectiveness to stabilize the building against earthquake vibration and the boundness of estimated stiffness and viscosity coefficients.
This work presents the design of two control schemes for a Delta/Par4-like parallel robot: augmented PD (APD) controller and augmented nonlinear PD (ANPD) controller. The stability of parallel robot based on nonlinear PD controller has been analyzed and proved based on Lyapunov method. A comparison study between APD and ANPD controllers has been made in terms of performance and accuracy improvement of trajectory tracking. Also, another comparison study has been presented between augmented nonlinear PD (ANPD) controller and nonaugmented nonlinear PD (NANPD) controller in order to show the enhancement of introducing the augmented structure on dynamic performance and trajectory tracking accuracy. The effectiveness of augmented PD controllers (APD and ANPD) and nonaugmented nonlinear PD (NANPD) controller for the considered parallel robot are verified via simulation within the MATLAB environment.
This work proposes a new kind of trajectory tracking controller for the differential drive mobile robot (DDMR), namely, the nonlinear neural network fractional-order proportional integral derivative (NNFOPID) controller. The suggested controller’s coefficients comprise integral, proportional, and derivative gains as well as derivative and integral powers. The adjustment of these coefficients turns the design of the proposed NNFOPID control further problematic than the conventional proportional-integral-derivative control. To handle this issue, an Enhanced Fruit Fly Swarm Optimization algorithm has been developed and proposed in this work to tune the NNFOPID’s parameters. The enhancement achieved on the standard fruit fly optimization technique lies in the increased uncertainty in the values of the initialized coefficients to convey a broader search space. subsequently, the search range is varied throughout the updating stage by beginning with a big radius and declines gradually during the course of the searching stage. The proposed NNFOPID controller has been validated its ability to track specific three types of continuous trajectories (circle, line, and lemniscate) while minimizing the mean square error and the control energy. Demonstrations have been run under MATLAB environment and revealed the practicality of the designed NNFOPID motion controller, where its performance has been compared with that of a nonlinear Neural Network Proportional Integral Derivative controller on the tracking of one of the aforementioned trajectories of the DDMR.
Multi-Inputs-Multi-Outputs (MIMO) systems are recognized mainly in industrial applications with both input and state couplings, and uncertainties. The essential principle to deal with such difficulties is to eliminate the input couplings, then estimate the remaining issues in real-time, followed by an elimination process from the input channels. These difficulties are resolved in this research paper, where a decentralized control scheme is suggested using an Improved Active Disturbance Rejection Control (IADRC) configuration. A theoretical analysis using a state-space eigenvalue test followed by numerical simulations on a general uncertain nonlinear highly coupled MIMO system validated the effectiveness of the proposed control scheme in controlling such MIMO systems. Time-domain comparisons with the Conventional Active Disturbance Rejection Control (CADRC)-based decentralizing control scheme are also included.
The construction of pavement layers on subgrade soil with good characteristics decreases the thickness of these layers, which in turn lowers the cost of building and maintaining roadways. However, it is impossible to avoid constructing pavements on unsuitable subgrade due to a number of limitations. Using conventional additives like lime and cement to improve subgrade properties results in additional costs. As a result, utilizing by-products (cement kiln dust and reclaimed asphalt pavement) in this field has benefits for the environment, economy, and technology. Large amounts of cement kiln dust (CKD), a by-product material, are produced in Portland cement factories. On the other hand, large amounts of reclaimed asphalt pavement (RAP) are accumulated as a result of the rehabilitation of old roads. This paper discusses using CKD and RAP to improve the characteristics of poor subgrade layers by conducting a series of Unconfined Compressive Strength (UCS) and California Bearing Ratio (CBR) tests on samples of natural soil and soil stabilized with different percentages of CKD and RAP with different curing times to investigate their impacts on soil properties. The curing was carried out by wrapping the stabilized samples with several layers of nylon and then placing them in plastic bags at room temperature. The compaction results illustrated that the addition of CKD increases OMC and decreases MDD, in contrast to RAP, which decreases OMC and increases MDD. The addition of CKD and RAP led to a significant and unexpected increase in the CBR values. The results show that the soaked and unsoaked CBR values improve from 3.4% and 12.1% for natural soil to 220.1% and 211%, respectively, after adding 20% CKD and curing the samples for 28 days. Also, the addition of 25% RAP to soil-20% CKD blend increased the soaked and unsoaked CBR values to 251% and 215%, respectively. All the additions resulted in a significant reduction in swelling.
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