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This paper concerns with a tracking control of a servo mechanism with friction. An adaptive friction compensation strategy based on notion of H<sup>∞</sup> optimality is proposed. It is assumed that the friction dynamics is described by the LuGre model. Neural-network (NN) is used to parameterize the nonlinear characteristic function of the LuGre m...
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Faults or process failures may drastically change system behaviour leading to performance degradation and instability. The reliability and fault-tolerance of a control system can be achieved through the design of either an active or passive fault tolerant control (FTC) scheme. This paper proposes a new approach to fault compensation for FTC using f...
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... This method would often result in a suboptimal performance and fail completely when the disturbances are large. In the σ -modification [10], [11], the standard Lyapunov-based adaptive rule is modified with a damping term that is independent of the tracking error. The adaptation estimates are then naturally bounded, but the resulting tracking error would usually be very large, since the adaptation would unlearn the plant as the tracking error approaches zero. ...
The new trajectory regulating model reference adaptive controller (TRMRAC) has been proposed in this brief. The intermediate reference model in the TRMRAC is self-regulated to enhance the stability and robustness of adaptation, with the trajectories of the controlled system proven to be ultimately uniformly bounded. The developed controller is implemented and simulated in a multivariable robotic arm system with its system dynamics approximated by a neural network, showing superior stability characteristics even under unmodeled actuator dynamics and input saturation. To demonstrate its practicality, a nested version of the controller was tested on a quadcopter for quaternion attitude tracking, showing enhanced robustness over the conventional model reference adaptive control strategy. IEEE
... To face on this problem, in the previous works [11], the control input and estimation strategies contain the discontinuous function term which reflects the component for compensation of the NN approximation error. This discontinuous function will cause a risk of exciting high-frequency fluctuations and chattering phenomena [12], [13]. Therefore, a control strategy with discontinuous function is not suitable to apply the practical servo-motion control systems. ...
... Therefore, a control strategy with discontinuous function is not suitable to apply the practical servo-motion control systems. To solve the aforementioned problems, NN approximation error is regarded as an exogenous disturbance to the system and an adaptive H ∞ controller is given [12], [13]. An adaptive H ∞ controller can be designed without solving the Hamilton-Jaccobi-Isaacs equation, because it based on the inverse optimal control strategy [2], [6], [7]. ...
... September 13-18, 2011, Waseda University, Tokyo, Japan In this paper, we apply this adaptive differentiator to the adaptive friction compensation method [12], [13], and show the effectiveness of this approach. Experimental results are given to show the effectiveness of this method. ...
This paper considers an adaptive positioning control problem using adaptive velocity estimator. Previous adaptive control methods, the control strategy requires full–states mea-surements, such as position and velocity measurements. In the practical case, only the position is measured by using position sensors, therefore, we have to make a velocity signals . Making a velocity signal component, an approximate differentiator and first order filter are often applied. But, it may cause deterioration of the control performance for the high ultra precision positioning control problems. This paper deals with an adaptive friction compensation method that includes an adaptive differentiator which can estimate velocity signals without using approximated differentiator. Experimental results are given to show the effec-tiveness of the proposed method for the high ultra precision positioning control problems.
... Therefore, in the previous works [11], the control input and estimation strategies contain the discontinuous function term which reflects the component for compensation of the NN approximation error. It has already been noticed that the discontinuous function will cause a risk of exciting high–frequency fluctuations and chattering phenomena [12], [13]. This suggests that a control strategy with discontinuous function is not suitable to apply the practical servo–motion control systems. ...
... This suggests that a control strategy with discontinuous function is not suitable to apply the practical servo–motion control systems. A NN approximation error is regarded as an exogenous disturbance to the system and an adaptive H ∞ controller is given [12], [13]. Based on the inverse optimal control strategy [2], [6], [7], an adaptive H ∞ controller can be designed without solving the Hamilton–Jaccobi–Isaacs equation. ...
... This non-model-based adaptive differentiator does not need the information of the dynamic structure of the signal. In this paper, we apply this adaptive differentiator to the adaptive friction compensation method [12], [13], and show the effectiveness of this approach. Numerical simulations is given to show the effectiveness of this method. ...
This paper considers an adaptive tracking control problem for a positioning mechanism with friction. Almost of the previous adaptive control methods, the control strategy needs full-states measurements, such as position and velocity measurements. In general, only the position is measured by using position sensors, therefore, we have to make a velocity signals. To make a velocity signal component, an approximate differentiator and first order filter are often applied. But, unfortunately, it may cause deterioration of the control performance for the high ultra precision positioning control problems. This paper deals with adaptive friction compensation method that includes an adaptive differentiator which can estimate velocity signals without using approximated differentiator. The effectiveness of the proposed method is demonstrated by numerical simulations for the high ultra precision positioning control problems.
... Therefore, in the previous works [16], the control input and estimation strategies contain the discontinuous function term which reflects the component for compensation of the NN approximate error. It has already been noticed that the discontinuous function will cause a risk of exciting high–frequency fluctuations and chattering phenomena for the practical applications [18], [19]. This suggests that a control strategy with discontinuous function is not suitable to apply the practical servo–motion control systems. ...
... This suggests that a control strategy with discontinuous function is not suitable to apply the practical servo–motion control systems. To solve this problem, NN approximation error is regarded as an exogenous disturbance to the system and an adaptive H ∞ controller is given [18]. This method is also based on inverse optimal control strategy, an adaptive H ∞ controller can be designed without solving the HJI equation. ...
This paper considers an adaptive H<sup>infin</sup> control method with link frictions compensation and external disturbances rejection for robotic systems. It is assumed that all the system parameters for friction model and robot are unknown. The proposed method ensures that the unknown parameters are estimated and approximation errors of friction model and external disturbances are attenuated by means of H<sup>infin</sup> control performance. In spite of considering the adaptive H<sup>infin</sup> control problems, the compensator can design without solving the Hamilton-Jacobi-Isaacs equation. Simulation and experimental results are given to illustrate the effectiveness of our proposed method. It is also shown that we can easily design to determine the relative importance of the error and the expenditure of the input energy
... To overcome this problem, the control input and estimation strategies contain the discontinuous function term which reflects the component for compensation of the NN approximation error [12]. It has already been noticed that the discontinuous function will cause a risk of exciting high–frequency fluctuations and chattering phenomena[14], [15]. This suggests that a control strategy with discontinuous function is not suitable to apply the practical servo–motion control systems. ...
... This suggests that a control strategy with discontinuous function is not suitable to apply the practical servo–motion control systems. A NN approximation error is regarded as an exogenous disturbance to the system and an adaptive H ∞ controller is given [13], [14], [15] . Based on inverse optimal control strategy[3], [7], [8], an adaptive H ∞ controller can be designed without solving the Hamilton–Jaccobi–Isaacs equation. ...
In this paper an adaptive tracking control of a servo mechanism with friction is developed, based on the notion of H<sup>infin</sup> optimality. It is assumed that the friction dynamics can be described by the LuGre model. The nonlinear characteristic function of the LuGre model is parameterized by a neural-network (NN). In general, friction parameters and NN weight are unknown. These parameters are updated by estimating strategy in this proposed method. An approximation error in NN is regarded as an exogenous disturbance to the system, the L<sub>2 </sub> gains from the disturbance to generalized outputs are made less than prescribed positive constants. To cope with the practical applications, gradient algorithms with projection method is also applied to the unknown parameter estimation methods. The effectiveness of the proposed method is evaluated via some experimental results
Recently, with the deterioration of bridge facilities, demand has arisen for a method to inspect many bridges efficiently. One proposed bridge inspection method involves observation and inspection of cracks on undersides of bridges using a video camera mounted on an unmanned aerial vehicle (UAV) that flies under the bridges. There is an option to have a pilot operate the UAV, but it is desirable to have the UAV fly autonomously when efficiency of inspection is considered. Though there is a method using GPS for autonomous flight control of UAVs, there are many cases in which GPS cannot be utilized under bridges, and a new method is required for autonomous flight control in such places. The authors have already shown that autonomous flight control of UAVs can be achieved within the range of a monocular camera image by measuring the position of a UAV using camera images. However, since the flight range is bounded by the monocular camera image, it is necessary to move the camera position to fly the UAV autonomously in a wider space. In this paper, it is shown that a UAV can achieve autonomous flight control in wider spaces by constructing a single coordinate system for a combination of two camera images. In addition, considering that various measuring instruments might be mounted on a UAV, an adaptive control method capable of obtaining good control performance without changing the design parameters of the controllers should be applied. This method is useful for maintaining control performance when the total weight of the UAV changes. To show the effectiveness of our proposed method, we give an appropriate practical flight target orbit and present its experimental results.
This paper deals with a adaptive tracking control for a positioning mechanism with friction. All most of the previous method, the controller requires full–states measurements, such as position and velocity measurements. It is often that only the position is measured by position sensors in the practical experimentation. Therefore, the velocity should be estimated in some way using only position measurement. This paper deals with adaptive friction compensation method that includes a adaptive differentiator which can estimate velocity signals. The effectiveness of the proposed method is demonstrated by numerical simulations and experimental results.
In this paper, we design an adaptive estimator for the nonlinear dynamic friction force when the output is the position. To begin with, a velocity estimator is proposed based on the adaptive identification method. Then, an acceleration estimator is proposed with the non-passifiable adaptive schemes. Finally, the proposed acceleration estimator is applied to the estimation of friction forces. Numerical examples are given to illustrate the performance of the estimator in the case of the viscous friction model, the Coulomb friction model, and the LuGre model.
In this note, we design adaptive observers to estimate the nonlinear friction model when the output is the velocity and the position, respectively. First, two adaptive observer are designed to estimate the viscous friction force in the velocity measurement and in the position measurement, respectively. Secondly, the kinetic friction force and the dynamic friction force are estimated by the fuzzy adaptive observers in the position measurement. Finally, simulation results for the proposed observers are presented
The paper presents an adaptive integral position controller usingRBF (Radial Basis Function) neural networks (NNs) for a brushless DC linear motor. By assuming that the upper bounds of the nonlinear friction and force ripple, an RBF NN is used for approximating the friction, the force ripple and the load; an adaptive backstepping control with integral action is then proposed to achieve position tracking of the linear motor. The parameter adjustment rules for the overall controller are derived via the Lyapunov stability theory. Based on the LaSalle-Yoshizawa lemma, the proposed controller is proven asymptotically stable. Experimental results are conducted to show the efficacy and usefulness of the proposed control method.
