An observer-based control strategy is proposed for regulating problem of a Cartesian robot arm, which is modeled as a flexible cantilever beam with a translational base support. The base motion is controlled utilizing...
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An observer-based control strategy is proposed for regulating problem of a Cartesian robot arm, which is modeled as a flexible cantilever beam with a translational base support. The base motion is controlled utilizing an electrodynamic shaker, while a piezoelectric (PZT) patch actuator is bonded on the surface of the flexible beam for suppressing residual arm vibrations. Taking into account both electrical and mechanical fields for the PZT patch actuator, a full-order model is developed using assumed mode model expansion and the Lagrangian approach. Utilizing three measurable quantities (i.e., the base displacement, arm tip deflection and the strain at the root end of the arm), a reduced-order observer is designed to estimate the velocity related variables, which are not directly measurable for the truncated model. A simple PD controller is selected for the moving base regulation, while a lyapunov-based controller is utilized for the PZT input voltage to make the closed-loop system energy dissipative and hence stable. The PZT input voltage control uses the velocity related signals estimated by the reduced-order observer, which simplifies the control implementation in practice. The feasibility of the controller is validated through both numerical simulations and experimental testing. Significant matching between experimental results and numerical simulation is observed. (C) 2003 Elsevier Ltd. All rights reserved.
A mixed chemotherapy-immunotherapy treatment protocol is developed for cancer treatment. Chemotherapy pushes the trajectory of the system towards the desired equilibrium point, and then immunotherapy alters the dynami...
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A mixed chemotherapy-immunotherapy treatment protocol is developed for cancer treatment. Chemotherapy pushes the trajectory of the system towards the desired equilibrium point, and then immunotherapy alters the dynamics of the system by affecting the parameters of the system. A co-existing cancerous equilibrium point is considered as the desired equilibrium point instead of the tumour-free equilibrium. Chemotherapy protocol is derived using the pseudo-spectral (PS) controller due to its high convergence rate and simple implementation structure. Thus, one of the contributions of this study is simplifying the design procedure and reducing the controller computational load in comparison with lyapunov-based controllers. In this method, an infinite-horizon optimal control problem is proposed for a non-linear cancer model. Then, the infinite-horizon optimal control of cancer is transformed into a non-linear programming problem. The efficient Legendre PS scheme is suggested to solve the proposed problem. Then, the dynamics of the system is modified by immunotherapy is another contribution. To restrict the upper limit of the chemo-drug dose based on the age of the patients, a Mamdani fuzzy system is designed, which is not present yet. Simulation results on four different dynamics cases how the efficiency of the proposed treatment strategy.
In this paper, a novel lyapunov-based robust controller by using meta-heuristic optimization algorithm has been proposed for lateral control of an autonomous vehicle. In the first step, double lane change path has bee...
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In this paper, a novel lyapunov-based robust controller by using meta-heuristic optimization algorithm has been proposed for lateral control of an autonomous vehicle. In the first step, double lane change path has been designed using a fifth-degree polynomial (quantic) function and dynamic constraints. A lane changing path planning method has been used to design the double lane change manoeuvre. In the next step, position and orientation errors have been extracted based on the two-degree-of-freedom vehicle bicycle model. A combination of sliding mode and backstepping controllers has been used to control the steering in this paper. Overall stability of the combined controller has been analytically proved by defining a lyapunov function and based on lyapunov stability theorem. The proposed controller includes some constant parameters which have effects on controller performance;therefore, particle swarm optimization algorithm has been used for finding optimum values of these parameters. The comparing result of the proposed controller with backstepping controller illustrated the better performance of the proposed controller, especially in the low road frictions. Simulation of designed controllers has been conducted by linking CarSim software with Matlab/Simulink which provides a nonlinear full vehicle model. The simulation was performed for manoeuvres with different durations and road frictions. The proposed controller has outperformed the backstepping controller, especially in low frictions.
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