Adaptive Pitch Control Research Articles

Adaptive Pitch-Tracking Control with Dynamic and Static Gains for Remotely Operated Towed Vehicles

The pitch angle regulation in Remotely Operated Towed Vehicles (ROTVs) is essential to ensure the robustness of emitted signals within the maritime surveillance domain. Characterized by inherent nonlinear dynamics and stochastic uncertainties, the pitch angle model poses significant challenges to conventional tracking controls relying on linearization. This study introduces an adaptive pitch-control algorithm designed for ROTVs, which adeptly manages nonlinear dynamics as well as unmeasurable states through a synergistic integration of dynamic and static gains. A key feature of our approach is the incorporation of a high-order observer that adeptly estimates the system’s unmeasurable states, thereby enhancing control precision. Our proposed algorithm greatly exceeds traditional PID and fuzzy PID methods in both settling time and steady-state error, particularly in high-order nonlinear and unmeasurable state scenarios. Compared to sliding mode control, the proposed control strategy improved the settling time by 74% and the steady-state error was enhanced from 10−6 to 10−8, as confirmed by numerical simulations. The efficacy of the algorithm in achieving the desired tracking trajectories highlights its potential for deep-water operations and fine-tuned attitude adjustments for ROTVs.

Performance and mechanism of adaptive pitch control in a floating vertical axis wind turbine with a surge motion

Floating vertical axis wind turbines are bearing complex aerodynamic fatigue loads due to the movement of the platform and the reciprocating variations in the angle of attack and the blade relative wind speed. To explore the effect of the surge motion of the platform and verify the performance and acting mechanism of adaptive pitch control on reducing the fatigue loads and improving the power coefficient, a floating vertical axis wind turbine with three motion forms (non-surge, pure surge, and surge-adaptive pitch) is investigated in the condition of a low tip speed ratio with a high incoming wind speed. The results show that the surge motion enhances the fatigue loads, with the power coefficient less affected. The adaptive pitch control reduces the enhanced fatigue loads and improves the power coefficient by nearly twice. Vorticity and pressure distributions verify that the fluctuation ranges of the angle of attack and the blade relative wind speed are expanded by the surge motion, and the angle of attack is reduced by the adaptive pitch control especially in the upwind section, with the flow separation mitigated. However, the effects of the surge motion and the pitch variation are also influenced by the shedding vortex and the flow separation reattachment. For the upwind part of the blade aerodynamic forces, with the surge amplitude increase or the surge period decrease, the global amplitudes are increased gradually by the surge motion and then reduced by the pitch control, with the load reduction performance enhanced gradually.

Comparison of adaptive pitch control strategies for a wind turbine benchmark model

PurposeThe wind turbine (WT) is a complex system subjected to wind disturbances. Because the aerodynamics is nonlinear, the control is thus challenging. For the variation of wind speed when rated power is delivered at rated wind speed, the power is limited to the rate by the pitching of the blades of the turbine. This paper aims to address pitch control with the WT benchmark model. The possible use of appropriate adaptive controller design that modifies the control action automatically identifying any change in system parameters is explored.Design/methodology/approachTo deal with pitch control problem when wind speed exceeds the rated wind speed of the WT, six digital self-tuning controller (STC) with different structures such as proportional integral (PI), proportional derivative (PD), Dahlin’s, pole placement, deadbeat and Takahashi has been taken herein. The system model is identified as a second-order autoregressive exogenous (ARX) model by three techniques for comparison: recursive least square method (RLS), RLS with exponential forgetting and RLS with adaptive directional forgetting identification methods. A comparative study of three identification methods, six adaptive controllers with the conventional PI controller and sliding mode controller (SMC), are shown.FindingsAs per the results, the best improvement in control of the output power by pitching in full load region of benchmark model is achieved by self-tuning PD controller based on RLS with adaptive directional forgetting method. The adaptive control design has a future in WT control applications.Originality/valueA comparative study of identification methods, six adaptive controllers with the conventional PI controller and SMC, are shown here. As per the results, the best improvement in control of the output power by pitching in the full load region of the benchmark model has been achieved by self-tuning PD controller. The best identification method or the system is RLS with an adaptive directional forgetting method. Instead of a step input response design for the controllers, the controller design has been carried out for the stochastic wind and the performance is adjudged by the normalized sum of square tracking error (NSSE) index. The validation of the proposed self-tuning PD controller has been shown in comparison to the conventional controller with Monte-Carlo analysis to handle model parameter alteration and erroneous measurement issues.

Electrohydraulic proportional valve-controlled vane type semi-rotary actuated wind turbine control by feedforward fractional-order feedback controller

In this study, proportional valve-controlled semi-rotary electrohydraulic actuator proposed for horizontal axis wind turbine pitch movement. Semi-rotary actuator can be connected directly to the wind turbine blade, which reduces mechanical complexity compare to linear electrohydraulic actuator system. Adaptive torque control scheme has been adopted for the horizontal axis wind turbine in region II; however, adaptive pitch control has been adopted for region III. Optimum pitch demand and torque demand have been estimated through blade element momentum theory based on predicted wind speed. The control objective is to track maximum power through torque control in region II and to maintain rated power with structural safety by limiting thrust force in the region III. The proposed wind turbine model has been validated with 1.5-MW wind turbine experimental data. Feedforward fractional-order proportional–integral–derivative controller with adaptive teaching–learning based optimization algorithm has been developed for wind turbine control application. In region II, feedforward control signal generates due to torque demand and feedback control signal generates due to combined torque and pitch error. However, in region III, feedforward and feedback control estimated with pitch demand and combined pitch and torque error, respectively. The proposed controller performance has been tested with sinusoidal, step and actual wind data. The controller performance also compared with respect to other conventional controllers. Performance of the adaptive teaching–learning-based optimization has been compared with genetic algorithm and teaching–learning-based optimization process. Sensitivity analysis has been performed with proposed controller to check the effectiveness of the optimization. Furthermore, the proposed controller response has been compared with existing data of 1.5-MW wind turbine. Lyapunov-based stability analysis has been performed to ensure stability and convergence of the proposed system. Proposed controller performance has been found better compare to the existing result.

Research on power increase adaptive control strategy based on 5 MW wind turbine

Wind power is one of the cheapest and direct methods to alleviate negative impacts on environment therefore the demand of efficient wind energy conversion system is increasing. Uneven distribution of wind impacts the performance of Wind Turbine (WT) system so constant and noise free power at output is required. The pitching angle varies according to the Wind Speed (WS), and the power output equation of the entire WT system depends upon WT pitch angle. Pitch control is widely used to optimize power above rated WS. This paper proposes an efficient adaptive pitch control controller to maintain the output power of a 5 MW WT in dynamic wind conditions. Compared to low level control loops (such as PI), this illustrates the effectiveness of the proposed controller. The model was tested in a 5 MW WT GH bladed system.

Adaptive Pitch Controller of a Large-Scale Wind Turbine Using Multi-Objective Optimization

This paper deals with the control problems of a wind turbine working in its nominal zone. In this region, the wind turbine speed is controlled by means of the pitch angle, which keeps the nominal power constant against wind fluctuations. The non-uniform profile of the wind causes tower displacements that must be reduced to improve the wind turbine lifetime. In this work, an adaptive control structure operating on the pitch angle variable is proposed for a nonlinear model of a wind turbine provided by FAST software. The proposed control structure is composed of a gain scheduling proportional–integral (PI) controller, an adaptive feedforward compensation for the wind speed, and an adaptive gain compensation for the tower damping. The tuning of the controller parameters is formulated as a Pareto optimization problem that minimizes the tower fore-aft displacements and the deviation of the generator speed using multi-objective genetic algorithms. Three multi-criteria decision making (MCDM) methods are compared, and a satisfactory solution is selected. The optimal solutions for power generation and for tower fore-aft displacement reduction are also obtained. The performance of these three proposed solutions is evaluated for a set of wind pattern conditions and compared with that achieved by a classical baseline PI controller.

Combining LIDAR and LADRC for intelligent pitch control of wind turbines

At present, most of the pitch control methods are based on PI controller, the pitch control system has poor disturbance resistance, and the research of variable parameter feedforward based on Light detection and ranging (LIDAR) and the Linear Active Disturbance Rejection controller (LADRC) composite control is rarely studied to reduce the blade root load, so this paper conceives a hybrid intelligent and adaptive pitch control approach to reduce a wind turbine generator speed fluctuation and its blade root load. Specifically, we combine the Radial Basis Neural Network and Finite Impulse Response filter (RBFNNFIR) based on LIDAR wind measurement. We then use a variable bandwidth of LADRC controller. Overall the approach enables and facilitates self-adaption and self-adjustment. We use Matlab s-function to call the multi-freedom mathematical wind turbine model based on FAST code, the composite intelligent control algorithm is established in Simulink. Initial results from the statistical analysis of the experiments under different turbulent wind conditions shows that the hybrid intelligent pitch control approach can reduce the generator speed fluctuation by about 40.8%, and the blade root max value of load moment by about 13.1%, compared with the baseline values of the traditional variable gain PI control algorithm.

Adaptive Pitch Control of Variable-Pitch PMSG Based Wind Turbine

This paper presents an adaptive pitch-angle control approach for a permanent magnet-synchronous generator-based wind turbine (PMSG-WT) connecting with a power grid to limit extracted power above the rated wind speed. In the proposed control approach, a designed perturbation observer is employed for estimating and compensating unknown parameter uncertainties, system nonlinearities, and unknown disturbances. The proposed control approach does not require full state measurements or the accurate system model. Simulation tests verify the effectiveness of the proposed control approach. The simulation results demonstrate that compared with the feedback linearizing controller, conventional vector controller with proportional-integral (PI) loops, and PI controller with gain scheduling, the proposed control approach can always maintain the extracted wind power around rated power, and has higher performance and robustness against disturbance and parameter uncertainties.

Adaptive pitch control of full-scale ship composite propeller using shape memory alloy to enhance propulsive efficiency in off-design conditions

In this study, we investigate the use of shape memory alloy for adaptive control of twist of the propeller blade for a full-scale marine composite propeller of actual blade geometry, to offset the reduction in its hydrodynamic efficiency in off-design conditions. A full-scale ship propeller of 4.2 m diameter, made of graphite–epoxy laminate integrated with Nitinol fibre–reinforced hybrid composite (shape memory alloy hybrid composite) patches, is considered. The shape memory alloy hybrid composite patches are placed such that the recovery stress induced on heating the pre-strained shape memory alloy fibres embedded in martensite phase to the austenite phase causes twisting deformation in the propeller blade. The open water performance is estimated from the flow solution obtained using the finite volume method considering viscous flow and fluid structure interaction, while the deformation analysis is performed using the finite element method based on the first-order shear deformation theory, considering the nonlinearity due to large deformation. It is shown for the first time for a ship propeller of actual size and shape that the heating of the shape memory alloy fibres generates sufficient twist in the propeller to cause appreciable improvement (up to 6.3%) in its hydrodynamic efficiency in off-design conditions with lower advance ratios, thereby enhancing its fuel efficiency.

Improved pole-placement for adaptive pitch control

This paper presents an improved technique to regulate the pitch angle of a wind turbine benchmark model (WTBM) implemented in MATLAB SIMULINK environment. As the model is nonlinear in nature, to accomplish the desired power production level in the constant power region, an adaptive controller is implemented. It takes care of the pitch control with online estimates of the plant parameters that are susceptible to change due to disturbances. Here, the controller design is based on the pole-placement methodology for a self-tuning controller (STC). Location of the desired pair of poles is defined by the damping factor and natural frequency. The selection of these parameters is performed by utilising particle swarm optimisation (PSO), constriction factor-based PSO (CFBPSO), genetic algorithm (GA), modified grey wolf optimisation (MGWO) and improved sine cosine algorithm (ISCA) and the results are put side by side for a consistent set of algorithm parameters. A Monte Carlo simulation has been carried out for comparison of the algorithms. The achieved results show the improvement in performance by employing ISCA for pole-placement of an adaptive STC controller.

Improved pole-placement for adaptive pitch control

Improved pole-placement for adaptive pitch control

Adaptive pitch control for ships with diesel mechanical and hybrid propulsion

Shipping urgently needs to reduce its impact on the environment, both due to CO2, NOx and particulate matter (PM) emissions and due to underwater noise. On the other hand, multifunction ships such as offshore support vessels, anchor handling and towing vessels, naval vessels and wind farm construction and support vessels require fast and accurate manoeuvring and need highly reliable systems to support reduced or no crew. Diesel mechanical propulsion with controllable pitch propellers provides high efficiency and low CO2 emissions, but has traditionally been poor in manoeuvrability, can suffer from thermal overloading due to manoeuvring and requires significant measures to meet NOx and PM emission regulations. The control strategy of diesel mechanical propulsion with fixed combinator curves is one of the causes of the poor manoeuvrability, thermal overloading and cavitation noise during manoeuvring, such as slam start and intermediate acceleration manoeuvres. This paper proposes an adaptive pitch control strategy with slow integrating speed control that reduces fuel consumption, CO2, NOx and PM emissions and underwater noise, improves acceleration performance, limits engine loading and prevents engine under- and overspeed. A simulation study with a validated model of a case study Holland class Patrol Vessel demonstrates 5–15% reduction in fuel consumption and CO2 emissions, compared to the baseline transit control mode in the ship speed range from 6 to 15 kts, during constant speed sailing. Moreover, the adaptive pitch control strategy reduces acceleration time from 0 to 15 kts with the slam start procedure by 32% compared to the baseline manoeuvre control mode and by 84% for an intermediate acceleration from 10 to 15 kts, while preventing thermal overloading of the engine, during straight line manoeuvres. Combining this control strategy with hybrid propulsion, running an electric drive in parallel with the propulsion diesel engine, can potentially further reduce fuel consumption at low speeds while also improving acceleration performance even more. Therefore, hybrid propulsion plants with controllable pitch propellers and adaptive pitch control can provide a significant contribution to the urgent reduction of environmental impact of shipping and to the need for more autonomous and reliable ship systems.

Integrated in-process chatter monitoring and automatic suppression with adaptive pitch control in parallel turning

Simultaneous processes such as parallel turning or milling offer great opportunities for more efficient manufacturing because of their higher material removal rates. To maximize their advantages, chatter suppression technologies for simultaneous processes must be developed. In this study, we constructed an automatic chatter suppression system with optimal pitch control for shared-surface parallel turning with rigid tools and a flexible workpiece, integrating in-process chatter monitoring based on the cutting force estimation. The pitch angle between two tools is tuned adaptively in a position control system in accordance with the chatter frequency at a certain spindle speed, in a similar manner as the design methodology for variable-pitch cutters. The cutting force is estimated without using an additional external sensor by employing a multi-encoder-based disturbance observer. In addition, the chatter frequency is measured during the process by performing a low-computational-load spectrum analysis at a certain frequency range, which makes it possible to calculate the power spectrum density in the control system of the machine tool. Thus, the constructed system for automatic chatter suppression does not require any additional equipment.

Parallel Control for Hybrid Propulsion of Multifunction Ships

Multifunction ships, naval vessels in particular, need to reduce fuel consumption while maintaining manoeuvrability. Hybrid propulsion that runs a main diesel engine and electric drive in parallel can achieve this. However, a parallel control strategy needs to be developed. In this paper, we use a simulation model of a hybrid propulsion system to investigate two parallel control strategies for diesel mechanical and electrical propulsion on multifunction ships. For the case study frigate, parallel control can increase the ship top speed with 3 kts when using two 4 MW electric drives and two 10 MW main diesel engines, compared with the same baseline hybrid propulsion without parallel control. The diesel engine speed control with electric drive torque control strategy increases ship acceleration rate with 17% and reduces average engine thermal loading with 150 K. Moreover, the electric drive speed control with diesel engine torque control strategy can improve acceleration rate by 40%, while eliminating thermal loading fluctuation due to heavy seas, and also reducing engine average thermal loading with 150 K. Future combination of the proposed electric drive speed control strategy with an adaptive pitch control and optimal power split strategy can potentially further increase hybrid propulsion plant performance.

Adaptive pitch control of wind turbine for load mitigation under structural uncertainties

In this research, a new adaptive control strategy is formulated for the pitch control of wind turbine that may suffer from reduced life owing to extreme loads and fatigue when operated under high wind speed and internal structural uncertainties. Specifically, we aim at making a trade-off between the maximum energy captured and the load induced. The adaptive controller is designed to both regulate generator speed and mitigate component loads under turbulent wind field when blade stiffness uncertainties exist. The proposed algorithm is tested on the NREL offshore 5-MW benchmark wind turbine. The control performance is compared with those of the gain scheduled proportional integral (GSPI) control and the disturbance accommodating control (DAC) that are used as baselines. The results show that with the proposed adaptive control the blade root flapwise load can be reduced at a slight expense of optimal power output. Moreover, the blade load mitigation performance under uncertain blade stiffness reduction is improved over the baseline controllers. The control approach developed in this research is general, and can be extended to mitigating loads on other components.

Innovative adaptive pitch control for small wind turbine fatigue load reduction

As a renewable source of energy, wind is widely used to produce electrical power. The progress of wind turbine technology can greatly benefit from the improvement of control algorithms. The pitch angle control of a horizontal axis wind turbine above the rated wind speed is a challenging issue related to the nonlinear aerodynamic behavior of blades. The linearization of aerodynamic model around nominal operating condition, as well as manufacturing deficiencies, result in unknown parameter uncertainties in a wind turbine model. Therefore, the performance of controller, which is designed based on the mathematical model, defects in practice. In the current paper, an adaptive self-tuning regulator (STR) configuration is proposed for the pitch control, so that the parameters of wind turbine model are constantly estimated and the controller gains are updated based on the assessed parameters. The STR structure consists of a recursive least square estimator and a proportional-integral-derivative (PID) controller with adjustable gains, which are determined by the pole placement method in a real-time routine. The robustness of the closed loop system is investigated by implementation of the control structure on an aero-servo-elastic wind turbine simulator. For the sake of comparison, a baseline gain scheduling PID controller, which is well-accepted for wind turbine pitch control, is designed. A comparison between the simulations of two controllers confirms a significant improvement in the closed-loop performance including less fluctuation of rotor speed and power besides minor fatigue loads on the blades and main-shaft.

Robust Adaptive Fault Tolerant Pitch Control of Wind Turbines

Inaccuracy in linear modeling of wind turbines, effects of wind speed disturbance, and faults in components of the closed-loop system increase the need for advanced controllers in wind energy conversion systems. In this article, an adaptive pitch controller is developed to regulate the generator speed in region 3. Also, an adaptive feed-forward term is augmented to improve the generator speed regulation in presence of the wind speed disturbance. Parameters of the controller are adaptively adjusted based on the improved dead-zone modification rule that guarantees closed-loop stability and zero regulation error in presence of the unstructured modeling uncertainties, step-like wind speed disturbance, and faults in pitch actuator. Proposed controller is compared to the baseline proportional-integral controller for controls advanced research turbine. Simulation results confirm the improvement in closed-loop regulation performance with proposed robust adaptive controller.

L1 adaptive pitch control of an autonomous underwater vehicle

Purpose – The purpose of this paper is to show the application of an L1 adaptive controller to control an autonomous underwater vehicle (AUV), considering realistic perturbations. Design/methodology/approach – In this paper, an L1 adaptive controller is proposed to control the pitch channel of an AUV, for the first time. Based on a six degree of freedom (6-DOF) nonlinear equations, an appropriate linear model considering real perturbations is derived for the pitch channel of AUV. Then L1 adaptive controller is applied on the model in the presence of the bounded disturbances and uncertainties. For this purpose, verified parameters of the REMUS AUV have been considered. Several simulations are performed in different operating conditions. Findings – The results confirm the quality of the proposed method in various situations. Furthermore, it is shown that the L1 adaptive controller is potential to contribute in practical applications of AUVs such as other autonomous systems. Originality/value – This is the first time that this method has been applied to an AUV.

The Research of Model-Free Adaptive Control for Large Scale Wind Turbine

Dynamic load is a key consideration in large scale wind turbine design. It is approved that the performance of controller can distinguish impact wind turbine loads. For strong external disturbances and inaccurately modeled of large wind turbines, In this paper, we propose model-free adaptive (Model Free Adapt, MFA) individual pitch control algorithms. The controller was developed in to mitigate the rotor unbalance structural load for variable speed wind turbine. The controller is designed from a nonlinear model of the system which takes into account the blades, shaft and tower flexibilities. Bladed software was used for the control strategy and traditional PID control strategy simulation comparison. The results show that the new control strategy can effectively stabilize wind turbine power output and reduce aerodynamic loads.

Generator speed regulation in the presence of structural modes through adaptive control using residual mode filters

Wind turbines operate in highly turbulent environments resulting in aerodynamic loads that can easily excite turbine structural modes, potentially causing component fatigue and failure. Two key technology drivers for turbine manufacturers are increasing turbine up time and reducing maintenance costs. Since the trend in wind turbine design is towards larger, more flexible turbines with lower frequency structural modes, manufacturers will want to develop control paradigms that properly account for the presence of these modes. Accurate models of the dynamic characteristics of new wind turbines are often not available due to the complexity and expense of the modeling task, making wind turbines ideally suited to adaptive control approaches. In this paper, we develop theory for adaptive control with rejection of disturbances in the presence of modes that inhibit the controller. A residual mode filter is introduced to accommodate these modes and restore important properties to the adaptively controlled plant. This theory is then applied to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine. The adaptive pitch controller is compared in simulations with a baseline classical proportional integrator (PI) collective pitch controller.