879 research outputs found
Adaptive Backstepping Control for Fractional-Order Nonlinear Systems with External Disturbance and Uncertain Parameters Using Smooth Control
In this paper, we consider controlling a class of single-input-single-output
(SISO) commensurate fractional-order nonlinear systems with parametric
uncertainty and external disturbance. Based on backstepping approach, an
adaptive controller is proposed with adaptive laws that are used to estimate
the unknown system parameters and the bound of unknown disturbance. Instead of
using discontinuous functions such as the function, an
auxiliary function is employed to obtain a smooth control input that is still
able to achieve perfect tracking in the presence of bounded disturbances.
Indeed, global boundedness of all closed-loop signals and asymptotic perfect
tracking of fractional-order system output to a given reference trajectory are
proved by using fractional directed Lyapunov method. To verify the
effectiveness of the proposed control method, simulation examples are
presented.Comment: Accepted by the IEEE Transactions on Systems, Man and Cybernetics:
Systems with Minor Revision
Globally Intelligent Adaptive Finite-/Fixed- Time Tracking Control for Strict-Feedback Nonlinear Systems via Composite Learning Approaches
This article focuses on the globally composite adaptive law-based intelligent
finite-/fixed- time (FnT/FxT) tracking control issue for a family of uncertain
strict-feedback nonlinear systems. First, intelligent approximators with new
composite updating laws are developed to model uncertain nonlinear terms, which
encompass prediction errors to enhance intelligent approximators' learning
behaviors and fewer online learning parameters to diminish computational
burden. Then, a novel smooth switching function coupled with robust controllers
is designed to pull system states back when the transients are out of the
approximators' active domain. After that, a modified FnT/FxT backstepping
technique is constructed to render output to follow the reference trajectory,
and an adaptive law is employed to alleviate the impact of external
disturbances. It is theoretically confirmed that the proposed control
strategies ensure globally FnT/FxT boundedness of all the closed-loop
variables. Finally, the validity of theoretical results is testified via a
simulation case.Comment: 6 pages,12 figure
Prescribed Performance Adaptive Fixed-Time Attitude Tracking Control of a 3-DOF Helicopter with Small Overshoot
In this article, a novel prescribed performance adaptive fixed-time
backstepping control strategy is investigated for the attitude tracking of a
3-DOF helicopter. First, a new unified barrier function (UBF) is designed to
convert the prescribed performance constrained system into an unconstrained
one. Then, a fixed-time (FxT) backstepping control framework is established to
achieve the attitude tracking. By virtual of a newly proposed inequality, a
non-singular virtual control law is constructed. In addition, a FxT
differentiator with a compensation mechanism is employed to overcome the matter
of "explosion of complexity". Moreover, a modified adaptive law is developed to
approximate the upper bound of the disturbances. To obtain a less conservative
and more accurate approximation of the settling time, an improved FxT stability
theorem is proposed. Based on this theorem, it is proved that all signals of
the system are FxT bounded, and the tracking error converges to a preset domain
with small overshoot in a user-defined time. Finally, the feasibility and
effectiveness of the presented control strategy are confirmed by numerical
simulations.Comment: 6 pages, 4 figure
Control of power electronic interfaces in distributed generation.
Renewable energy has gained popularity as an alternative resource for electric power generation. As such, Distributed Generation (DG) is expected to open new horizons to electric power generation. Most renewable energy sources cannot be connected to the load directly. Integration of the renewable energy sources with the load has brought new challenges in terms of the system’s stability, voltage regulation and power quality issues. For example, the output power, voltage and frequency of an example wind turbine depend on the wind speed, which fluctuate over time and cannot be forecasted accurately. At the same time, the nonlinearity of residential electrical load is steadily increasing with the growing use of devices with rectifiers at their front end. This nonlinearity of the load deviates both current and voltage waveforms in the distribution feeder from their sinusoidal shape, hence increasing the Total Harmonics Distortions (THD) and polluting the grid. Advances in Power Electronic Interfaces (PEI) have increased the viability of DG systems and enhanced controllability and power transfer capability. Power electronic converter as an interface between energy sources and the grid/load has a higher degree of controllability compared to electrical machine used as the generator. This controllability can be used to not only overcome the aforementioned shortfalls of integration of renewable energy with the grid/load but also to reduce THD and improve the power quality. As a consequence, design of a sophisticated controller that can take advantage of this controllability provided by PEIs to facilitate the integration of DG with the load and generate high quality power has become of great interest. In this study a set of nonlinear controllers and observers are proposed for the control of PEIs with different DG technologies. Lyapunov stability analysis, simulation and experimental results are used to validate the effectiveness of the proposed control solution in terms of tracking objective and meeting the THD requirements of IEEE 519 and EN 50160 standards for US and European power systems, respectively
U-model based predictive control for nonlinear processes with input delay
In this paper, a general control scheme is proposed for nonlinear dynamic processes with input delay described by different models, including polynomial models, state-space models, nonlinear autoregressive moving average with eXogenous inputs (NARMAX) models, Hammerstein or Wiener type models. To tackle the input delay and nonlinear dynamics involved with the control system design, it integrates the classical Smith predictor and a U-model based controller into a U-model based predictive control scheme, which gives a general solution of two-degree-of-freedom (2DOF) control for the set-point tracking and disturbance rejection, respectively. Both controllers are analytically designed by proposing thedesired transfer functions for the above objectives in terms of a linear system expression with the U-model, and therefore are independent of the process model for implementation. Meanwhile, the control system robust stability is analyzed in the presence of process uncertainties. To demonstrate the control performance and advantage, three examples from the literature are conducted with a user-friendly step by step procedure for the ease of understanding by readers
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