1,000 research outputs found

    Disturbance observer-based fault-tolerant control for robotic systems with guaranteed prescribed performance

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    The actuator failure compensation control problem of robotic systems possessing dynamic uncertainties has been investigated in this paper. Control design against partial loss of effectiveness (PLOE) and total loss of effectiveness (TLOE) of the actuator are considered and described, respectively, and a disturbance observer (DO) using neural networks is constructed to attenuate the influence of the unknown disturbance. Regarding the prescribed error bounds as time-varying constraints, the control design method based on barrier Lyapunov function (BLF) is used to strictly guarantee both the steady-state performance and the transient performance. A simulation study on a two-link planar manipulator verifies the effectiveness of the proposed controllers in dealing with the prescribed performance, the system uncertainties, and the unknown actuator failure simultaneously. Implementation on a Baxter robot gives an experimental verification of our controller

    Robust fractional-order fast terminal sliding mode control with fixed-time reaching law for high-performance nanopositioning

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    Open Access via the Wiley Agreement ACKNOWLEDGEMENTS This work is supported by the China Scholarship Council under Grant No. 201908410107 and by the National Natural Science Foundation of China under Grant No. 51505133. The authors also thank the anonymous reviewers for their insightful and constructive comments.Peer reviewedPublisher PD

    Second Order Integral Fuzzy Logic Control Based Rocket Tracking Control

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    Fuzzy logic is a logic that has a degree of membership in the vulnerable 0 to 1. Fuzzy logic is used to translate a quantity that is expressed using language. Fuzzy logic is used as a control system because this control process is relatively easy and flexible to design without involving complex mathematical models of the system to be controlled. The purpose of this paper is to present a fuzzy control system implemented in a rocket tracking control system. The fuzzy control system is used to keep the rocket on track and traveling at a certain speed. The signal from the fuzzy logic control system is used to control the rocket thrust. The fuzzy Logic System was chosen as the controller because it is able to work well on non-linear systems and offers convenience in program design. Fuzzy logic systems have a weakness when working on systems that require very fast control such as rockets. With this problem, fuzzy logic is modified by adding second-order integral control to the modified fuzzy logic. The proposed algorithm shows that the missile can slide according to the ramp path at 12 m altitude of 12.78 at 12 seconds with a steady-state error of 0.78 under FLC control, at 10 m altitude of 10.68 at 10 seconds with a steady-state error of 0.68 with control integral FCL, at a height of 4 m is 4.689 at 4 seconds with a steady-state error of 0.689 with a second-order integral control of FCL. The missile can also slide according to the parabolic path with the second-order integral control of FCL at an altitude of 15.47 in the 4th minute with a steady-state error of 0

    Adaptive Active Anti-vibration Control for a Three-dimensional Helicopter Flexible Slung-load System with Input Saturations and Backlash

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    This study investigates active anti-vibration control for a three-dimensional helicopter flexible slung-load system (HFSLS) subject to input saturations and backlash. The first target of the study is to establish a model for a three-dimensional HFSLS. The second target is to develop an adaptive control law for a HFSLS by analyzing its ability to compensate for the effects of input saturations, input backlash, and external disturbances, while achieving the goal of vibration reduction. Simulation results of the numerical show that the proposed adaptive active control technology is effective in solving the oscillation suppression problem for the three-dimensional HFSLS with input saturations and backlash.</p

    A CENTER MANIFOLD THEORY-BASED APPROACH TO THE STABILITY ANALYSIS OF STATE FEEDBACK TAKAGI-SUGENO-KANG FUZZY CONTROL SYSTEMS

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    The aim of this paper is to propose a stability analysis approach based on the application of the center manifold theory and applied to state feedback Takagi-Sugeno-Kang fuzzy control systems. The approach is built upon a similar approach developed for Mamdani fuzzy controllers. It starts with a linearized mathematical model of the process that is accepted to belong to the family of single input second-order nonlinear systems which are linear with respect to the control signal. In addition, smooth right-hand terms of the state-space equations that model the processes are assumed. The paper includes the validation of the approach by application to stable state feedback Takagi-Sugeno-Kang fuzzy control system for the position control of an electro-hydraulic servo-system

    Direct thrust force control of primary permanent magnet linear motor based on improved extended state observer and model-free adaptive predictive control

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    A model-free adaptive predictive control algorithm based on an improved extended state observer (IESO) is proposed to solve the problem that the primary permanent magnet linear motor is susceptible to time-varying parameters and unknown disturbances. Firstly, a model-free adaptive control algorithm based on compact format is designed to achieve high control precision of the system and reduce thrust fluctuation, only through the input/output data of the system. Because the traditional model-free adaptive control is too sensitive to the internal parameters of the controller, a combination of model-free adaptive control and predictive control is further developed. By predicting the data for a future time in advance, the sensitivity to the internal parameters of the controller is reduced and the control performance is further improved. Since the load change and other nonlinear disturbances in practical applications have a great impact on the control effect of the system, an improved extended state observer is further used to compensate for the impact of nonlinear disturbances on the control system. In addition, the stability of the closed-loop system is analyzed. Comparable simulation results clearly demonstrate the good tracking performance and strong robustness of the proposed control

    Relative Threshold-Based Event-Triggered Control for Nonlinear Constrained Systems With Application to Aircraft Wing Rock Motion

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    This paper concentrates upon the event-driven controller design problem for a class of nonlinear single input single output (SISO) parametric systems with full state constraints. A varying threshold for the triggering mechanism is exploited, which makes the communication more flexible. Moreover, from the viewpoint of energy conservation and consumption reduction, the system capability becomes better owing to the contribution of the proposed event triggered mechanism. In the meantime, the developed control strategy can avoid the Zeno behavior since the lower bound of the sample time is provided. The considered plant is in a lower-triangular form, in which the match condition is not satisfied. To ensure that all the states to retain in a predefined region, a barrier Lyapunov function (BLF) based adaptive control law is developed. Due to the existence of the parametric uncertainties, an adaptive algorithm is presented as an estimated tool. All the signals appearing in the closed-loop systems are then proven to be uniformly ultimately bounded (UUB). Meanwhile, the output of the system can track a given signal as far as possible. In the end, the effectiveness of the proposed approach is validated by an aircraft wing rock motion system

    Research on Advanced Control Strategies for Vehicle Active Seat Suspension Systems

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    Vehicle seat suspensions play a very important role in vibration reduction for vehicle drivers, especially for some heavy vehicles. Compared with small vehicles, these heavy vehicle drivers suffer much more from vibrations, which influence driving comfort and may cause health problems, so seat suspensions are necessary for those heavy vehicle drivers to reduce vibrations and improve driving comfort. Advanced control systems and control strategies are investigated for vehicle seat suspensions in this project. Firstly, for an active single-degree of freedom (single-DOF) seat suspension, a singular system-based approach for active vibration control of vehicle seat suspensions is proposed, where the drivers’ acceleration is augmented into the conventional seat suspension model together with seat suspension deflection and relative velocity as system states to make the suspen- sion model as a singular system. Then, an event-triggered H∞ controller is designed for an active seat suspension, where both the continuous and discrete-time event-triggered schemes are considered, respectively. The proposed control method can reduce the work- load of data transmission of the seat suspension system and work as a filter to remove the effect of noise, so it can decrease the precision requirement of the actuator, which can help to reduce the cost of the seat suspension. For complicated seat suspension systems, a singular active seat suspension system with a human body model is also established and an output-feedback event-triggered H∞ controller is designed. The accelerations of each part are considered as part of the system states, which makes the system a singular sys- tem. The seat suspension deflection, relative velocity, the accelerations of the seat frame, body torso, and head are defined as the system outputs. At last, to deal with whole-body vibration, a control system and a robust H∞ control strategy are designed for a 2-DOF seat suspension system. Two H∞ controllers are designed to reduce vertical and rotational vibrations simultaneously. All the proposed seat suspension systems and control methods are verified by simulations and some are also tested by experiments. These simulation and experimental results show their effectiveness and advantages of the proposed methods to improve the driving comfort and some can reduce the workload of data transmission

    Hybrid modeling and control of mechatronic systems using a piecewise affine dynamics approach

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    This thesis investigates the topic of modeling and control of PWA systems based on two experimental cases of an electrical and hydraulic nature with varying complexity that were also built, instrumented and evaluated. A full-order model has been created for both systems, including all dominant system dynamics and non-linearities. The unknown parameters and characteristics have been identi ed via an extensive parameter identi cation. In the following, the non-linear characteristics are linearized at several points, resulting in PWA models for each respective setup. Regarding the closed loop control of the generated models and corresponding experimental setups, a linear control structure comprised of integral error, feed-forward and state-feedback control has been used. Additionally, the hydraulic setup has been controlled in an autonomous hybrid position/force control mode, resulting in a switched system with each mode's dynamics being de ned by the previously derived PWA-based model in combination with the control structure and respective mode-dependent controller gains. The autonomous switch between control modes has been de ned by a switching event capable of consistently switching between modes in a deterministic manner despite the noise-a icted measurements. Several methods were used to obtain suitable controller gains, including optimization routines and pole placement. Validation of the system's fast and accurate response was obtained through simulations and experimental evaluation. The controlled system's local stability was proven for regions in state-space associated with operational points by using pole-zero analysis. The stability of the hybrid control approach was proven by using multiple Lyapunov functions for the investigated test scenarios.publishedVersio
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