27,367 research outputs found
Some issues in the sliding mode control of rigid robotic manipulators
This thesis investigates the problem of robust adaptive sliding mode control for nonlinear rigid robotic manipulators. A number of robustness and convergence results are presented for sliding mode control of robotic manipulators with bounded unknown disturbances, nonlinearities, dynamical couplings and parameter uncertainties. The highlights of the research work are summarized below : • A robust adaptive tracking control for rigid robotic manipulators is proposed. In this scheme, the parameters of the upper bound of system uncertainty are adaptively estimated. The controller estimates are then used as controller parameters to eliminate the effects of system uncertainty and guarantee asymptotic error convergence. • A decentralised adaptive sliding mode control scheme for rigid robotic manipulators is proposed. The known dynamics of the partially known robotic manipulator are separated out to perform linearization. A local feedback controller is then designed to stabilize each subsystem and an adaptive sliding mode compensator is used to handle the effects of uncertain system dynamics. The developed scheme guarantees that the effects of system dynamics are eliminated and that asymptotic error convergence is obtained with respect to the overall robotic control system. • A model reference adaptive control using the terminal sliding mode technique is proposed. A multivariable terminal sliding mode is defined for a model following control system for rigid robotic manipulators. A terminal sliding mode controller is then designed based on only a few uncertain system matrix bounds. The result is a simple and robust controller design that guarantees convergence of the output tracking error in a finite time on the terminal sliding mode
Adaptive Discrete Second Order Sliding Mode Control with Application to Nonlinear Automotive Systems
Sliding mode control (SMC) is a robust and computationally efficient
model-based controller design technique for highly nonlinear systems, in the
presence of model and external uncertainties. However, the implementation of
the conventional continuous-time SMC on digital computers is limited, due to
the imprecisions caused by data sampling and quantization, and the chattering
phenomena, which results in high frequency oscillations. One effective solution
to minimize the effects of data sampling and quantization imprecisions is the
use of higher order sliding modes. To this end, in this paper, a new
formulation of an adaptive second order discrete sliding mode control (DSMC) is
presented for a general class of multi-input multi-output (MIMO) uncertain
nonlinear systems. Based on a Lyapunov stability argument and by invoking the
new Invariance Principle, not only the asymptotic stability of the controller
is guaranteed, but also the adaptation law is derived to remove the
uncertainties within the nonlinear plant dynamics. The proposed adaptive
tracking controller is designed and tested in real-time for a highly nonlinear
control problem in spark ignition combustion engine during transient operating
conditions. The simulation and real-time processor-in-the-loop (PIL) test
results show that the second order single-input single-output (SISO) DSMC can
improve the tracking performances up to 90%, compared to a first order SISO
DSMC under sampling and quantization imprecisions, in the presence of modeling
uncertainties. Moreover, it is observed that by converting the engine SISO
controllers to a MIMO structure, the overall controller performance can be
enhanced by 25%, compared to the SISO second order DSMC, because of the
dynamics coupling consideration within the MIMO DSMC formulation.Comment: 12 pages, 7 figures, 1 tabl
Model-Free Adaptive Sensing and Control for a Piezoelectrically Actuated System
Since the piezoelectrically actuated system has nonlinear and time-varying behavior, it is difficult to establish an accurate dynamic model for a model-based sensing and control design. Here, a model-free adaptive sliding controller is proposed to improve the small travel and hysteresis defects of piezoelectrically actuated systems. This sensing and control strategy employs the functional approximation technique (FAT) to establish the unknown function for eliminating the model-based requirement of the sliding-mode control. The piezoelectrically actuated system’s nonlinear functions can be approximated by using the combination of a finite number of weighted Fourier series basis functions. The unknown weighted vector can be estimated by an updating rule. The important advantage of this approach is to achieve the sliding-mode controller design without the system dynamic model requirement. The update laws for the coefficients of the Fourier series functions are derived from a Lyapunov function to guarantee the control system stability. This proposed controller is implemented on a piezoelectrically actuated X-Y table. The dynamic experimental result of this proposed FAT controller is compared with that of a traditional model-based sliding-mode controller to show the performance improvement for the motion tracking performance
Adaptive sliding mode control for uncertain wheel mobile robot
In this paper a simple adaptive sliding mode controller is proposed for tracking control of the wheel mobile robot (WMR) systems. The WMR are complicated systems with kinematic and dynamic model so the error dynamic model is built to simplify the mathematical model. The sliding mode control then is designed for this error model with the adaptive law to compensate for the mismatched. The proposed control scheme in this work contains only one control loop so it is simple in both implementation and mathematical calculation. Moreover, the requirement of upper bounds of disturbance that is popular in the sliding mode control is cancelled, so it is convenient for real world applications. Finally, the effectiveness of the presented algorithm is verified through mathematical proof and simulations. The comparison with the existing work is also executed to evaluate the correction of the introduced adaptive sliding mode controller. Thoroughly, the settling time, the peak value, the integral square error of the proposed control scheme reduced about 50% in comparison with the compared disturbance observer based sliding mode control
Adaptive MIMO Fuzzy Compensate Fuzzy Sliding Mode Algorithm: Applied to Second Order Nonlinear System.
This research is focused on proposed adaptive fuzzy sliding mode algorithms with the adaptation laws
derived in the Lyapunov sense. The stability of the closed-loop system is proved mathematically based on
the Lyapunov method. Adaptive MIMO fuzzy compensate fuzzy sliding mode method design a MIMO fuzzy
system to compensate for the model uncertainties of the system, and chattering also solved by linear
saturation method. Since there is no tuning method to adjust the premise part of fuzzy rules so we
presented a scheme to online tune consequence part of fuzzy rules. Classical sliding mode control is
robust to control model uncertainties and external disturbances. A sliding mode method with a switching
control low guarantees the stability of the certain and/or uncertain system, but the addition of the switching
control low introduces chattering into the system. One way to reduce or eliminate chattering is to insert a
boundary layer method inside of a boundary layer around the sliding surface. Classical sliding mode
control method has difficulty in handling unstructured model uncertainties. One can overcome this problem
by combining a sliding mode controller and artificial intelligence (e.g. fuzzy logic). To approximate a timevarying
nonlinear dynamic system, a fuzzy system requires a large amount of fuzzy rule base. This large
number of fuzzy rules will cause a high computation load. The addition of an adaptive law to a fuzzy sliding
mode controller to online tune the parameters of the fuzzy rules in use will ensure a moderate
computational load. The adaptive laws in this algorithm are designed based on the Lyapunov stability
theorem. Asymptotic stability of the closed loop system is also proved in the sense of Lyapunov
Memory-based adaptive sliding mode load frequency control in interconnected power systems with energy storage
This paper presents a memory-based adaptive sliding mode load frequency control (LFC) strategy aimed at minimizing the impacts of exogenous power disturbances and parameter uncertainties on frequency deviations in interconnected power systems with energy storage. First, the dynamic model of the system is constructed by considering the participation of the energy storage system (ESS) in the conventional decentralized LFC model of a multiarea power system. A disturbance observer (DOB) is proposed to generate an online approximation of the lumped disturbance. In order to enhance the transient performance of the system and effectively mitigate the adverse effects of power fluctuations on grid frequency, a novel memory-based sliding surface is developed. This sliding surface incorporates the estimation of the lumped disturbance, as well as the past and present information of the state variables. The conservative assumption about the lumped disturbance is eased by considering the unknown upper bound of the disturbance and its first derivative. Based on the output of the proposed DOB, an adaptive continuous sliding mode controller with prescribed H performance index is introduced. This controller ensures that the sliding surface is reachable and guarantees asymptotic stability of the closed-loop system. The controller design utilizes strict linear matrix inequalities (LMIs) to achieve these objectives. Finally, the applicability and efficacy of the proposed scheme are verified through comparative simulation cases. Autho
Control of a 3D piezo-actuating table by using an adaptive sliding-mode controller for a drilling process
AbstractRecently, the micropositioner has become an important developing target for achieving the requirements of precision machinery. The piezo-actuating device plays a very important role in this application area. In this paper, a model-free adaptive sliding-mode controller is proposed for a 3D piezo-actuating system because of the system’s hysteresis nonlinearity and time-varying characteristics. This control strategy employs the functional approximation technique to establish the unknown function for releasing the model based requirements of the sliding-mode control. The update laws for the coefficients of the Fourier series function parameters are derived from a Lyapunov function to guarantee the control system stability. To verify the effectiveness of the proposed controller, drilling process control using the designed controller is investigated in this paper
Sliding Mode Control for Trajectory Tracking of a Non-holonomic Mobile Robot using Adaptive Neural Networks
In this work a sliding mode control method for a non-holonomic mobile robot using an adaptive neural network is proposed. Due to this property and restricted mobility, the trajectory tracking of this system has been one of the research topics for the last ten years. The proposed control structure combines a feedback linearization model, based on a nominal kinematic model, and a practical design that combines an indirect neural adaptation technique with sliding mode control to compensate for the dynamics of the robot. A neural sliding mode controller is used to approximate the equivalent control in the neighbourhood of the sliding manifold, using an online adaptation scheme. A sliding control is appended to ensure that the neural sliding mode control can achieve a stable closed-loop system for the trajectory-tracking control of a mobile robot with unknown non-linear dynamics. Also, the proposed control technique can reduce the steady-state error using the online adaptive neural network with sliding mode control; the design is based on Lyapunov’s theory. Experimental results show that the proposed method is effective in controlling mobile robots with large dynamic uncertaintiesFil: Rossomando, Francisco Guido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Soria, Carlos Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Carelli Albarracin, Ricardo Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentin
Incorporating thruster dynamics in the control of an underwater vehicle
Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 1989The dynamics of an underwater vehicle are greatly influenced by the dynamics
of the thrusters. Precise control, for example to perform repeatable survey or coordinated
vehicle/manipulator control, should incorporate knowledge of thruster dynamic behavior.
An energy-based lumped parameter model of the nonlinear thruster dynamic response is
developed and experimentally verified using static and dynamic thruster relationships.
Three controllers to compensate for the nonlinear dynamics are designed including
analog lead compensation, model-based computed torque and adaptive sliding control
techniques. The proposed controller designs are implemented and evaluated in a hybrid,
one degree-of-freedom vehicle simulation using an actual thruster under digital control as
the actuator. Controller evaluation and comparison is based on observed vehicle tracking
performance.
The incorporation of thruster dynamics is shown to significantly improve
vehicle tracking performance. Superior, robust tracking performance with significant
model uncertainty is demonstrated in the application of the adaptive sliding control
technique. The evaluated adaptive controller structure may permit on-line adaptation to
complex hydrodynamic phenomena associated with complete vehicle/thruster
configurations such as cross-flow and mutual interference
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