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An algebraic method based on unknown input observer for fault estimation in linear time invariant system with unknown input is implementable if matching condition is satisfied. Matching condition limits practical application of these methods. In this article, a method is proposed for fault estimation which need not to satisfy matching condition. Unlike classical methods, the provided method doesn’t require for auxiliary output for fault estimation. In first step, the unknown input is divided in two parts: the matched and the unmatched unknown inputs. Assuming that there exist a dynamic model for the unmatched part, new augmented system is constructed. The augmented system has revealed as a new system with matched unknown input. Then, the effect of matched unknown input has perfectly removed from observer estimation using the traditional unknown input decoupling strategy. In next step, the full order observer is designed for the augmented system. A fast adaptive law is employed for the fault estimation. Lyapunov stability condition of state and fault estimation is derived by linear matrix inequality(LMI) criteria. The effectiveness of the proposed method is shown via numerical simulation on a flexible joint example.

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In this paper dynamic model analysis, position control and locomotion generation of a 2-link robotic fish has been presented. For this purpose, the dynamic model of a 2-link robotic fish based on Lighthill hydrodynamic theory is employed. The effect of system inputs on robot linear velocity, radius curvature of path and hydrodynamic efficiency is investigated with a large amount of simulations. A position controller is designed to generate path by the point to point method. By defining target point and angle and distance errors, control design strategy is proposed to limit the angle error to the neighborhood of zero. It is shown that bounding angle error in a ten degree neighborhood of zero, makes the distance error tend to zero. Despite former methods in which, driving both angle and distance errors to zero simultaneously result in huge control effort, the proposed control strategy in addition to improve performance by spending less control effort, make the controller structure simpler and no need to velocity feedback. Finally by using the results of model analysis, it is shown that using minimum amplitude for the 2-link robot drives the average hydrodynamic efficiency of path close enough to its optimum value.

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In this study, a modified method has been introduced for forward dynamic analysis of fast parallel robots. For this purpose, inspired by the Lagrange-Virtual Spring (LVS) method, the Decoupled Natural Orthogonal Complement (DeNOC) method is modified which is a Newtonian based method. So far, virtual springs have been already used in energy based methods. However using the virtual springs in DeNOC method is a novel approach which is proposed in current study. In order to clarify the advantages of Modified Decoupled Natural Orthogonal Complement (MDeNOC) method, a planar 3RRR mechanism is chosen as case study. According to the results, the process of deriving the equations of motion is much less costly while the accuracy of MDeNOC is similar to the LVS and unlike the energy methods, the modified method is also able to calculate the constraint reactions, as well. On the other hand, the calculation time of MDeNOC is much more than the DeNOC and hence, is not suitable for real time calculations. Also, in closed loop systems, constraints must be defined in such a way that express the virtual springs’ longitudinal changes; otherwise, MDeNOC will not give proper results.

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Sliding mode control is one of the most common types robust control that can compensate the model structure and parametric uncertainties, but the main disadvantage of this method is chattering phenomenon. Although a boundary layer around the sliding surface can eliminate chattering effect, it reduces tracking performance and robustness in control. The second generation of sliding mode control called Second Order Sliding Modes (SOSM) is a solution to this problem. Super-Twisting Sliding Mode (STSM) is a modified SOSM control that reduces chattering effect naturally and without a defined boundary layer, while maintaining the robustness of the Conventional Sliding Mode (CSM) control. In this paper, the problem trajectory planning is solved in an environment with fixed obstacles by using firefly optimization algorithm and polynomial trajectories, then STSM control is designed for quadrotor in the presence of uncertainties to tracking path trajectory and the performance of this controller is compared against Feedback Linearization (FL) and CSM control. Also, derivative of some of the states calculates by using super-twisting observer in the closed loop control and stabilization while there is no direct access to them through the sensors.