Problem statement: Many problems in scientific computing can be formulated as inverse problem. A vast majority of these problems are ill-posed problems. In Electrical Charge Tomography (EChT), normally the sensitivity matrix generated from forward modeling is very ill-condition. This condition posts difficulties to the inverse problem solution especially in the accuracy and stability of the image being reconstructed. The objective of this study is to reconstruct the image cross-section of the material in pipeline gravity dropped mode conveyor as well to solve the ill-condition of matrix sensitivity. Approach: Least Square with Regularization (LSR) method had been introduced to reconstruct the image and the electrodynamics sensor was used to capture the data that installed around the pipe. Results: The images were validated using digital imaging technique and Singular Value Decomposition (SVD) method. The results showed that image reconstructed by this method produces a good promise in terms of accuracy and stability. Conclusion: This implied that LSR method provides good and promising result in terms of accuracy and stability of the image being reconstructed. As a result, an efficient method for electrical charge tomography image reconstruction has been introduced.
<p>This paper presents a new robust bounded control law to stabilize uncertain nonlinear system with time varying disturbance. The design idea comes from the advantages of backstepping with Lyapunov redesign, which avoid the needs of fast switching of discontinuous control law offered by its counterpart - a variable structure control. We reduce the conservatism in the design process where the control law can be flexibly chosen from Lyapunov function, hence avoiding the use of convex optimization via linear matrix inequality (LMI) in which the feasibility is rather hard to be obtained. For this work, we design two type control algorithms namely normal control and bounded control. As such, our contribution is the introduction of a new bounded control law that can avoid excessive control energy, high magnitude chattering in control signal and small oscillation in stabilized states. Computation of total energy for both control laws confirmed that the bounded control law can stabilize with less enegry consumption. We also use Euler's approximation to compute average power for both control laws. The robustness of the proposed controller is achieved via saturation-like function in Lyapunov redesign, and hence guaranting asymptotic stability of the closed-loop system.</p>
This paper proposes an improved robust position controller for the electro-hydraulic actuator system using the varying boundary layered sliding mode control scheme. The proposed scheme has the ability to improve the position tracking performance of the actuator in the presence of friction and internal leakage. The former is represented using the LuGre model while later is modelled as a turbulent flow. To evaluate the effectiveness of the proposed method, MATLAB simulations are carried out under friction and leakage effects. Its performance is compared with the conventional PID and fuzzy PID (FPID) methods. Finally, an experimental rig that comprises of a single-rod and double acting hydraulic cylinder is set up to validate the proposed idea. The software development is carried out in the DSpace 1104 environment using a TMS320F240 digital signal processor. The superiority of the proposed method over the PID and FPID in terms of tracking position is highlighted by simulation and experimental results.
This paper presents backstepping controller design for tracking purpose of nonlinear system. Since the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA) and particle swarm optimization (PSO) techniques are used to optimise these parameters in order to achieve a predefined system performance. The performance is evaluated based on the tracking error between reference input given to the system and the system output. Then, the efficacy of the backstepping controller is verified in simulation environment under various system setup including both the system subjected to external disturbance and without disturbance. The simulation results show that backstepping with particle swarm optimization technique performs better than the similar controller with gravitational search algorithm technique in terms of output response and tracking error.
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