21,046 research outputs found
Fuzzy second order sliding mode control of a unified power flow controller
Purpose. This paper presents an advanced control scheme based on fuzzy logic and second order sliding mode of a unified power flow controller. This controller offers advantages in terms of static and dynamic operation of the power system such as the control law is synthesized using three types of controllers: proportional integral, and sliding mode controller and Fuzzy logic second order sliding mode controller. Their respective performances are compared in terms of reference tracking, sensitivity to perturbations and robustness. We have to study the problem of controlling power in electric system by UPFC. The simulation results show the effectiveness of the proposed method especiallyin chattering-free behavior, response to sudden load variations and robustness. All the simulations for the above work have been carried out using MATLAB / Simulink. Various simulations have given very satisfactory results and we have successfully improved the real and reactive power flows on a transmission lineas well as to regulate voltage at the bus where it is connected, the studies and illustrate the effectiveness and capability of UPFC in improving power.Π Π½Π°ΡΡΠΎΡΡΠ΅ΠΉ ΡΡΠ°ΡΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° ΡΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½Π½Π°Ρ ΡΡ
Π΅ΠΌΠ° ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½Π°Ρ Π½Π° Π½Π΅ΡΠ΅ΡΠΊΠΎΠΉ Π»ΠΎΠ³ΠΈΠΊΠ΅ ΠΈ ΡΠ΅ΠΆΠΈΠΌΠ΅ ΡΠΊΠΎΠ»ΡΠΆΠ΅Π½ΠΈΡ Π²ΡΠΎΡΠΎΠ³ΠΎ ΠΏΠΎΡΡΠ΄ΠΊΠ° ΡΠ½ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠ° ΠΏΠΎΡΠΎΠΊΠ° ΠΌΠΎΡΠ½ΠΎΡΡΠΈ. ΠΠ°Π½Π½ΡΠΉ ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅Ρ ΠΎΠ±Π»Π°Π΄Π°Π΅Ρ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π°ΠΌΠΈ Ρ ΡΠΎΡΠΊΠΈ Π·ΡΠ΅Π½ΠΈΡ ΡΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ°Π±ΠΎΡΡ ΡΠ½Π΅ΡΠ³ΠΎΡΠΈΡΡΠ΅ΠΌΡ, Π½Π°ΠΏΡΠΈΠΌΠ΅Ρ, Π·Π°ΠΊΠΎΠ½ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΡΠΈΠ½ΡΠ΅Π·ΠΈΡΡΠ΅ΡΡΡ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΡΠ΅Ρ
ΡΠΈΠΏΠΎΠ² ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠΎΠ²: ΠΏΡΠΎΠΏΠΎΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎ-ΠΈΠ½ΡΠ΅Π³ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ, ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠ° ΡΠΊΠΎΠ»ΡΠ·ΡΡΠ΅Π³ΠΎ ΡΠ΅ΠΆΠΈΠΌΠ° ΠΈ ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠ° ΡΠΊΠΎΠ»ΡΠ·ΡΡΠ΅Π³ΠΎ ΡΠ΅ΠΆΠΈΠΌΠ° Π½Π΅ΡΠ΅ΡΠΊΠΎΠΉ Π»ΠΎΠ³ΠΈΠΊΠΈ Π²ΡΠΎΡΠΎΠ³ΠΎ ΠΏΠΎΡΡΠ΄ΠΊΠ°. ΠΡ
ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠΈΠ΅ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠΈ ΡΡΠ°Π²Π½ΠΈΠ²Π°ΡΡΡΡ Ρ ΡΠΎΡΠΊΠΈ Π·ΡΠ΅Π½ΠΈΡ ΠΎΡΡΠ»Π΅ΠΆΠΈΠ²Π°Π½ΠΈΡ ΡΡΠ°Π»ΠΎΠ½ΠΎΠ², ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΊ Π²ΠΎΠ·ΠΌΡΡΠ΅Π½ΠΈΡΠΌ ΠΈ Π½Π°Π΄Π΅ΠΆΠ½ΠΎΡΡΠΈ. ΠΠ΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΠΈΠ·ΡΡΠΈΡΡ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΌΠΎΡΠ½ΠΎΡΡΡΡ Π² ΡΠ½Π΅ΡΠ³ΠΎΡΠΈΡΡΠ΅ΠΌΠ΅ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠ½ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠ° ΠΏΠΎΡΠΎΠΊΠ° ΠΌΠΎΡΠ½ΠΎΡΡΠΈ (UPFC). Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π°, ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎ Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΎΡΡΡΡΡΡΠ²ΠΈΡ Π²ΠΈΠ±ΡΠ°ΡΠΈΠΈ, ΡΠ΅Π°ΠΊΡΠΈΠΈ Π½Π° Π²Π½Π΅Π·Π°ΠΏΠ½ΡΠ΅ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ Π½Π°Π³ΡΡΠ·ΠΊΠΈ ΠΈ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΠΈ. ΠΡΠ΅ ΡΠ°ΡΡΠ΅ΡΡ Π΄Π»Ρ Π²ΡΡΠ΅ΡΠΊΠ°Π·Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΡ Π±ΡΠ»ΠΈ Π²ΡΠΏΠΎΠ»Π½Π΅Π½Ρ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ MATLAB/Simulink. Π Π°Π·Π»ΠΈΡΠ½ΡΠ΅ ΡΠ°ΡΡΠ΅ΡΠ½ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π΄Π°Π»ΠΈ Π²Π΅ΡΡΠΌΠ° ΡΠ΄ΠΎΠ²Π»Π΅ΡΠ²ΠΎΡΠΈΡΠ΅Π»ΡΠ½ΡΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ, ΠΈ ΠΌΡ ΡΡΠΏΠ΅ΡΠ½ΠΎ ΡΠ»ΡΡΡΠΈΠ»ΠΈ ΠΏΠΎΡΠΎΠΊΠΈ ΡΠ΅Π°Π»ΡΠ½ΠΎΠΉ ΠΈ ΡΠ΅Π°ΠΊΡΠΈΠ²Π½ΠΎΠΉ ΠΌΠΎΡΠ½ΠΎΡΡΠΈ Π½Π° Π»ΠΈΠ½ΠΈΠΈ ΡΠ»Π΅ΠΊΡΡΠΎΠΏΠ΅ΡΠ΅Π΄Π°ΡΠΈ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠ΅Π³ΡΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π½Π°ΠΏΡΡΠΆΠ΅Π½ΠΈΡ Π½Π° ΡΠΈΠ½Π΅, ΠΊ ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΎΠ½Π° ΠΏΠΎΠ΄ΠΊΠ»ΡΡΠ΅Π½Π°, ΡΡΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΈΠ·ΡΡΠΈΡΡ ΠΈ ΠΏΡΠΎΠΈΠ»Π»ΡΡΡΡΠΈΡΠΎΠ²Π°ΡΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΈ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ UPFC Π΄Π»Ρ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΡ ΠΌΠΎΡΠ½ΠΎΡΡΠΈ
Predictive Second Order Sliding Control of Constrained Linear Systems with Application to Automotive Control Systems
This paper presents a new predictive second order sliding controller (PSSC)
formulation for setpoint tracking of constrained linear systems. The PSSC
scheme is developed by combining the concepts of model predictive control (MPC)
and second order discrete sliding mode control. In order to guarantee the
feasibility of the PSSC during setpoint changes, a virtual reference variable
is added to the PSSC cost function to calculate the closest admissible set
point. The states of the system are then driven asymptotically to this
admissible setpoint by the control action of the PSSC. The performance of the
proposed PSSC is evaluated for an advanced automotive engine case study, where
a high fidelity physics-based model of a reactivity controlled compression
ignition (RCCI) engine is utilized to serve as the virtual test-bed for the
simulations. Considering the hard physical constraints on the RCCI engine
states and control inputs, simultaneous tracking of engine load and optimal
combustion phasing is a challenging objective to achieve. The simulation
results of testing the proposed PSSC on the high fidelity RCCI model show that
the developed predictive controller is able to track desired engine load and
combustion phasing setpoints, with minimum steady state error, and no
overshoot. Moreover, the simulation results confirm the robust tracking
performance of the PSSC during transient operations, in the presence of engine
cyclic variability.Comment: 6 pages, 5 figures, 2018 American Control Conferance (ACC), June
27-29, 2018, Milwaukee, WI, USA. [Accepted in Jan. 2018
Determination of pilot and vehicle describing functions from the Gemini 10 mission
Three types of manual control maneuvers conducted during the Gemini-10 mission have been analyzed in order to measure and document the describing function of the pilot, the vehicle and the pilot-vehicle combination during an actual space mission. Measurements made from the data records of the reentry maneuver (a single axis control task) indicate that the pilot's control behavior changes during critical portions of the reentry. Measurements made of the deorbit maneuver and of a terminal phase initiation maneuver (three axis tasks) show that the pilot assigns priorities to the separate axes and controls them differently. His control technique is also influenced by the magnitude of the thrust disturbance present during the maneuvers. The results for all three types of maneuvers show that the pilot adapts to the nonlinear spacecraft control system in such a way that the combined pilot-vehicle dynamics take the form of the linear crossover model
Nonlinear control and perturbation compensation in UAV quadrotor
The great interest in the field of flying robotics encouraged a lot of research work to improve its control strategies. This thesis is about modelling and design of controllers and perturbation compensators for a UAV quadrotor. Four approaches are built in this purpose.
The first approach is perturbation attenuation system in a UAV quadrotor. Hierarchical Perturbation Compensator (HPC) is built to compensate for system uncertainties, non-modelled dynamics and external disturbances. It comprises three subsystems designed to provide continuous and precise estimation of perturbation. Each subsystem is designed to avoid the drawbacks of the other. This approach has superior proficiency to decrease unknown perturbation either external or internal.
The second approach is a Three Loop Uncertainties Compensator (TLUC), designed to estimate unknown time- varying uncertainties and perturbations to reduce their effects and in order to preserve stability. The novelty of this approach is that the TLUC can estimate and compensate for uncertainties and disturbances in three loops made to provide tracking to residual uncertainty in order to achieve a higher level of support to the controller. Exponential reaching law sliding mode controller is proposed and applied. It is integrated based on Lyapunov stability theory to obtain fast response with lowest possible chattering. The performance is verified through analyses, simulations and experiments.
The third approach is Feedback Linearization based on Sliding Mode Control (FLSMC). The purpose is to provide nonlinear control that reduces the effect of the highly coupled dynamic behavior and the hard nonlinearity in the quadrotor. The proposed controller uses a Second Order sliding mode Exact Differentiator SOED to estimate the velocity and the acceleration.
The fourth approach proposes an improved Non-Singular Terminal Super-Twisting Control for the problem of position and attitude tracking of quadrotor systems. The super-twisting algorithm is an effective control used to provide high precision and less chattering. The proposed method is based on a non-singular terminal sliding surface with new exponent that solves the problem of singularity in terminal sliding mode control.
Design procedure and the stability analysis using Lyapunov theory are detailed for the considered approaches. The performance is verified through analyses, simulations and experiments
Design, analysis, and control of a cable-driven parallel platform with a pneumatic muscle active support
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG gefΓΆrderten) Allianz- bzw. Nationallizenz frei zugΓ€nglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The neck is an important part of the body that connects the head to the torso, supporting the weight and generating the movement of the head. In this paper, a cable-driven parallel platform with a pneumatic muscle active support (CPPPMS) is presented for imitating human necks, where cable actuators imitate neck muscles and a pneumatic muscle actuator imitates spinal muscles, respectively. Analyzing the stiffness of the mechanism is carried out based on screw theory, and this mechanism is optimized according to the stiffness characteristics. While taking the dynamics of the pneumatic muscle active support into consideration as well as the cable dynamics and the dynamics of the Up-platform, a dynamic modeling approach to the CPPPMS is established. In order to overcome the flexibility and uncertainties amid the dynamic model, a sliding mode controller is investigated for trajectory tracking, and the stability of the control system is verified by a Lyapunov function. Moreover, a PD controller is proposed for a comparative study. The results of the simulation indicate that the sliding mode controller is more effective than the PD controller for the CPPPMS, and the CPPPMS provides feasible performances for operations under the sliding mode control
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