Cascade Control Strategy Research Articles

An effective cascade control strategy for frequency regulation of renewable energy based hybrid power system with energy storage system

Frequency deviations occur when load frequency control(LFC) is incompetent to bridge the gap between supply and demand. Thus, this paper presents the effective (1 + TD)-TID cascade regulator to this significant field. The regulator is efficient to execute, and it interfaces the yield of 1 + TD regulator with all the inputs of TID regulator. Here, the power deviation of tie-line and frequency are employed to the TID regulator, which is referred to as the feedback signals. An imperialist competitive algorithm (ICA) is employed for tuning the controller design variables. The primary aim of this study is to examine the LFC issue and further exploration of 2 area thermal systems coordinated with renewable energy sources (RES) like solar PV, wind, and fuel cell with nonlinearities like governor dead band (DB) unit; reheat based turbine, and the generation rate constraints (GRC). The efficacy the of proposed control strategy are investigated in contrast with those of other common works, which disclose not only its simple structure but also, the ICA enhanced (1 + TD)-TID technique gives the smallest values of the performance index (0.091) compare to TIDF (0.372), PIDF (0.467) and least settling time (24.7 s) in contrast to TID (22.8 s) and PIDF (10s). Hence proposed control strategy shows efficient response with lesser oscillations and fast response. The sturdiness of suggested controller is also corroborated with nonlinearities and parameter variations of ±25% . The examination has been additionally improved by integrating a redox flow battery (RFB) in the proposed framework.

Temperature sensor location for the implementation of cascade control schemes in distillation columns: an approach based on multiscale time series analysis

Abstract In this work, the application of multiscale analysis to evaluate the sensitivity of the dynamic responses of the trays in a distillation column exposed to external disturbances is explored. This sensitivity allows for the identification of the tray where the temperature sensor improves the performance of a composition-temperature type cascade controller. To implement the proposed methodology, synthetic time series are generated for each plate of the column, which is subsequently analyzed using the multiscale rescaled range (R/S) analysis. Three case studies were evaluated (binary mixtures, azeotropic mixture and ternary mixture), finding that the highest values of the Hurst exponent correlate with the areas of greatest sensitivity of the column. To corroborate this result, a composition-temperature cascade control scheme was implemented, evaluating the temperature sensor in each plate of the column, identifying that the zone of greatest sensitivity determined with the multiscale analysis corresponds to the best performance of the controller. Therefore, our results show that the proposed methodology represents an easy-to-implement alternative that provides information on the most suitable zone for the placement of temperature sensors to improve the performance of cascade control in a pre-designed distillation column.

An LSTM-PSO-Based Predictive Strategy and Its Application in the Main Steam Temperature Control in Power Plants

We proposed an LSTM-PSO predictive controller strategy to overcome the large delay and strong disturbance during main steam temperature control. First, the long short-term memory (LSTM) network model was developed to forecast the future trend of mainstream temperature, and the deviation between the model output and the expected value after feedback correction was minimized by the particle swarm optimization (PSO) algorithm. Then, the LSTM-PSO predictive controller was taken as the primary controller to maintain the steam temperature of the coal-fired boiler. A comparative simulation with conventional PID cascade control and dynamic matrix controller strategies was given, and the test calculations indicate that the adjustment time was shortened and the overshoot was reduced. Finally, the LSTM – PSO predictive control strategy was deployed into the actual boiler operation process of a 300 MW coal-fired power plant, within 0.5 °C steady-state error and 2 °C dynamic error.

An adaptive cascade predictive control strategy for connected and automated vehicles

SummaryConnectivity is a key element enabling intelligent vehicles to communicate with each other and the Smart Road. In general, the connectivity is allowed by an On‐Board Unit enabling the Vehicle to Everything communication. This paper proposes an innovative unit acting not only as a device allowing connectivity but also as an intelligent electronic control unit to perform advanced and adaptive control strategies able to give reference trajectories and actuator set‐points to the low‐level control systems of power‐train and vehicle dynamics. In particular, based on a cascade model predictive control, an adaptive control strategy is proposed, considering time‐varying parameters and information related to vehicle kinematics and dynamics. Such a strategy allows the vehicle to follow a certain origin‐destination path in the inertial frame, based on an upper controller that considers a vehicle kinematic model so as to give speed references and target values for the steering angle at the wheels to the inner predictive control loop acting on both longitudinal and lateral vehicle dynamics. To check the effectiveness of the proposed approach, a comparison is made with existing cascade control strategies. The results show better safety and lane‐keeping performance. Then, using Hardware‐In‐the‐Loop testing for the proposed Intelligent On‐Board Unit, the considered approach demonstrates robustness against parametric variations, signal delay and noise both in the Global Positioning System and in the yaw rate sensor. The achieved results show good robustness properties, safety performances and confirm the real‐time execution of the cascade control strategy, paving the way to future developments necessary before tests in a real road scenario.

Vision-Based Hierarchical Impedance Control of an Aerial Manipulator

This paper presents an image-based impedance control scheme for an under-actuated aerial manipulator. Unlike the existing Cartesian cascade control (admittance control) scheme, we design an image-space visual servoing controller at the dynamic level to achieve compliant interaction with unknown environments. Furthermore, compared with the state of the art in aerial interaction control, feedback of both the external wrench and the Cartesian position of the aerial manipulator are not required. To cope with the under-actuation property of the system, an attitude tracking control task is designed in such a way that it is dynamically decoupled with the visual impedance control task. Convergence of the task-space tracking error is proven based on the Lyapunov theory. The finite-gain <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\mathcal{L}}_2$</tex-math></inline-formula> stability of the system regarding external force/disturbance is also proven. Indoor experiments are conducted to demonstrate the proposed method.

Design and Development of SECU Converter Cascaded Control for EV Applications

A power factor correction-based hybrid converter operating in continuous conduction mode with high efficiency and voltage conversion ratio is presented in this publication. The proposed converter is obtained by integrating the single-ended primary inductance converter (SEPIC) and the Cuk converter to produce a DC symmetrical balanced dual output voltage across the load without a common ground between source and load. The modeling of the converter by state space model is derived using the state space averaging technique. The cascaded control strategy using a multiplier approach with a cascaded controller and PI-Hysteresis-based controller is employed for shaping the source current and load voltage. The performance analysis of the suggested converter under steady state and transient conditions is carried out in MATLAB/Simulink software tool. The observed result displays that cascaded control yields excellent performance compared to PI-Hysteresis control in satisfying the IEC 61000-3-2 standard by maintaining a power factor close to unity, and reduced total harmonic distortion.

Finite-time target localization and multicircular circumnavigation with bearing-only measurements

This paper studies the finite-time localization and multicircular circumnavigation problem of an unknown stationary target via a networked multi-agent system using bearing-only measurements. To enhance the convergence rate of estimation, a novel estimator is developed to enable the agent to localize the target in finite time. At the same time, with the estimated target position, a distributed controller is designed such that the agents circumnavigate the target along different orbits with any prescribed angular spacing in finite time. In terms of Lyapunov theory and cascade control strategy, finite-time stability of the overall system including the estimator and controller are analyzed rigorously. Besides, the proposed algorithms guarantee that the agents can keep a safe distance from the target in the whole movement process, and high angular velocity can be avoided even if the circumnavigation radius becomes small. Finally, to corroborate the theoretical results, two simulation examples are given.

Distributed bearing-based formation maneuver control of fixed-wing UAVs by finite-time orientation estimation

This paper investigates the bearing-based formation maneuver control problem for a group of fixed-wing unmanned aerial vehicles. Unlike the existing works that only steer UAV swarm to achieve a fixed geometric pattern, our objective is to enable UAV swarm to maneuver as a group such that the centroid, scale and orientation of the formation can be continuously changed. The underlying graph of UAV swarm is assumed to satisfy a leader-first-follower structure, and the desired formation maneuvering parameters are only accessible to the leader. To address such issue, a cascaded control scheme is proposed. Firstly, we propose a distributed quaternion-based observer for each follower to estimate the desired orientation of the formation in finite time. Secondly, a bearing-based formation control law is developed to achieve the maneuvering formation, in which an adaptive-gain finite-time disturbance observer is synthesized to reject the deformations which vary the bearing constraints. It is demonstrated that the closed-loop formation tracking error converges to zero exponentially. Comparative simulations are preformed to demonstrate the effectiveness of the proposed method.

A Robust Fractional-Order Control Scheme for PV-Penetrated Grid-Connected Microgrid

This article presents a new cascaded control strategy to control the power flow in a renewable-energy-based microgrid operating in grid-connected mode. The microgrid model is composed of an AC utility grid interfaced with a multi-functional grid interactive converter (MF-GIC) acting as a grid-forming converter, a photovoltaic (PV) power-generation system acting as grid-feeding distributed generation unit, and various sensitive/non-sensitive customer loads. The proposed control strategy consists of a fractional order PI (FO-PI) controller to smoothly regulate the power flow between the utility grid, distributed generation unit, and the customers. The proposed controller exploits the advantages of FO (Fractional Order) calculus in improving the steady-state and dynamic performance of the renewable-energy-based microgrid under various operating conditions and during system uncertainties. To tune the control parameters of the proposed controller, a recently developed evaporation-rate-based water-cycle algorithm (ERWCA) is utilized. The performance of the proposed control strategy is tested under various operating conditions to show its efficacy over the conventional controller. The result shows that the proposed controller is effective and robust in maintaining all the system parameters within limits under all operating conditions, including system uncertainties.

Robust cascade control strategy for trajectory tracking to decouple disturbances using 3-degree-of-freedom inertial stabilized platform and its experimental validation

Inertial stabilized platform (ISP) is a vital component in modern tracking system which can segregate unsettling influence, keep altitude reference and rapidly realize identification and tracking of the target. For accurate tracking, the platform should be able to continuously point towards the target in presence of disturbances as well as parametric uncertainties associated with system modelling which normally degrade system performance. To tackle these challenges, different kinds of control strategies have been reported to achieve desired performance. However, there is an inevitable design trade-off between tracking and disturbance rejection capability as control performance decreases with the increase in system robustness. To alleviate this problem, the present work proposes a robust two-loop cascade control strategy where genetic algorithm (GA) optimized proportional–integral–derivative (PID) in the outer-loop facilitates precision tracking of the target. In the inner loop, lower-order robust controller designed by approximate generalized time moment (AGTM)/approximate generalized Markov parameter (AGMP) model matching approach is used to retain the robustness characteristics of [Formula: see text] controller to mitigate disturbances and model parametric uncertainties. System performance is verified through simulation as well as hardware implementation on a laboratory-fabricated three-axis gimbal platform prototype. The results show 48% improvement in tracking performance and 39.69% improvement in the rejection time of step disturbance in comparison with conventional PID control strategy.

Road preview MPC of semi‐active suspension with magneto‐rheological damper

In this article, a road preview model predictive control scheme for semi-active suspension system with magneto-rheological damper (MRD) is suggested. In order to improve the comprehensive performance of the semi-active suspension, studies of both the actuator and control algorithm have been carried out. For the actuator, e.t. MRD, a cascade control strategy is proposed based on a Hammerstein model, compared with the traditional open-loop control methods, the tracking accuracy of the damping force has been improved. For the control algorithm, in contrast to existing works which define all requirements in a single cost functional and minimize it, in this work a road preview model predictive controller is adopted for semi-active suspension to provide optimal ride comfort by keeping constrained variables within specified limits. The road excitation is a measurable external input rather than an unknown disturbance. Finally, the optimization issue with hard constrains is converted into a quadratic programming problem. Simulation results show that the desired damping force of the MRD is realized by using the cascade control strategy. Meanwhile, vehicles with the proposed road preview model predictive control scheme can achieve better performance compared with a H ∞ $$ {H}_{\infty } $$ /generalized H 2 $$ {H}_2 $$ controller.

Reinforced temperature control of a reactive double dividing-wall distillation column

The mass and thermal coupling makes the control of the reactive double dividing-wall distillation column (R-DDWDC) an especially challenging issue with a highly interactive nature. With reference to the separation of an ideal endothermic quaternary reversible reaction with the most unfavorable ranking of relative volatilities (A + B ↔ C + D with α A > α C > α D > α B ), the operation rationality of the R-DDWDC is studied in this contribution. The four-point single temperature control system leads to great steady-state discrepancies in the compositions of products C and D and the reason stems essentially from the failure in keeping strictly the stoichiometric ratio between reactants A and B. A temperature plus temperature cascade control scheme is then employed to reinforce the stoichiometric ratio control and helps to secure a substantial abatement in the steady-state discrepancies. A temperature difference plus temperature cascade control scheme is finally synthesized and leads even to better performance than the most effective double temperature difference control scheme. These outcomes reveal not only the operation feasibility of the R-DDWDC but also the general significance of the proposed temperature difference plus temperature cascade control scheme to the inferential control of any other complicated distillation columns.

Adaptive Multiple-Model-Based Fault-Tolerant Control for Non-minimum Phase Hypersonic Vehicles With Input Saturations and Error Constraints

In this article, an adaptive multiple-model-based fault-tolerant controller is developed for nonminimum phase air-breathing hypersonic vehicles (HSVs) in the presence of parametric uncertainties, elevator faults, input saturations, and time-varying error constraints. Compared with the existing works, the elevator-to-lift couplings are taken into account, which makes the HSV longitudinal models exhibit unstable internal-dynamics that impedes the applicability of common nonlinear control methods for control design. In order to solve this problem, a two-layer cascade control strategy is proposed in which the external inputs control the external states and the external state deviations control the internal states: 1) A multiple-model linear quadratic control strategy, based on gap metric, is proposed to guarantee the stability of the internal dynamics; 2) a fault-tolerant control scheme, based on tan-barrier Lyapunov functions, is developed by using a low-pass filter and an auxiliary system in conjunction with adaptive backstepping design. In the control law, the uncertain parameters are replaced by their estimates updated by adaptive laws. Additionally, the stability of the whole system is rigidly proved through standard Lyapunov approach, while the other states and signals in the closed-loop system are guaranteed to be bounded. Simulation results are provided to illustrate the effectiveness of the proposed adaptive multiple-model-based fault-tolerant controller.

Engine coolant temperature regulation via superheating control of an Organic Rankine Cycle

Waste Heat Recovery (WHR) systems based on the Organic Rankine Cycle (ORC) are an interesting technology to increase fuel efficiency of vehicles. This paper proposes a cascade control scheme to regulate the temperature of the cooling system of an electrically turbocharged natural gas engine for a heavy duty vehicle, using an ORC. To do so, the LPV framework is used to both identify a model and control ORC superheat. Then, an additional loop is used to control the reference superheat. The resulting control system allows correct operation of the ORC under investigation.

SSA‐optimized cascade optimal‐PIDN controller for multi‐area power system with RFB under deregulated environment

AbstractIn today's rapidly evolving interconnected electric power system network, ancillary service such as automatic generation control (AGC) plays a critical and important role in safeguarding the system's power supply quality by establishing an equilibrium between generation and load demanded plus losses. A power system with a robust and smart AGC strategy is obligatory for better power quality and system security. Cascade control schemes cope up better with nonlinearity by tuning the gain of controller of power system amid continuous load changing. Therefore, in this article, a supplementary control approach that is, cascade optimal controller‐proportional integral with derivative filter (COC‐PIDN) is suggested for AGC performance advancement of the power systems under deregulated environment. The OC designed consuming full state feedback control approach acts as master controller and PIDN plays the role of slave controller. The nature inspired salp swarm algorithm is employed to adjust the PIDN parameters. Initially, the efficacy of the COC‐PIDN control‐method is explored on a two‐area restructured reheat thermal system and then to validate its excellence and extensibility, the study is protracted to restructured two‐area thermal‐hydro system. Extensive analysis of the findings establishes that the dynamic performance of the COC‐PIDN controller is more valuable than the OC and COC‐PID approaches. The results of COC‐PIDN get further improved in presence of redox flow battery. Finally, the sensitivity analysis as well the acquired results with the COC‐PIDN controller with system nonlinearities demonstrate its robustness.

Cascade Control Method of Sliding Mode and PID for PEMFC Air Supply System

Proton exchange membrane fuel cells (PEMFC) are vulnerable to oxygen starvation when working under variable load. To address these issues, a cascade control strategy of sliding mode control (SMC) and Proportion Integration Differentiation (PID) control is proposed in this study. The goal of the control strategy is to enhance the PEMFC’s net power by adjusting the oxygen excess ratio (OER) to the reference value in the occurrence of a load change. In order to estimate the cathode pressure and reconstruct the OER, an expansion state observer (ESO) is developed. The study found that there is a maximum error of about 2200Pa between the estimated cathode pressure and the actual pressure. Then the tracking of the actual OER to the reference OER is realized by the SMC and PID cascade control. The simulation study, which compared the control performance of several methods—including PID controller, adaptive fuzzy PID controller and the proposed controller, i.e., the SMC and PID cascade controller—was carried out under various load-changing scenarios. The outcomes demonstrate that the proposed SMC and PID cascade controller method really does have a faster response time. The overshoot is reduced by approximately 3.4% compared to PID control and by about 0.09% compared to fuzzy adaptive PID. SMC and PID cascade control reference OER performs more effectively in terms of tracking compared to PID control and adaptive fuzzy PID control.

Experimental Study of the Model Predictive Control for a Residential Split Air Conditioner

Buildings consume 60% of the total building energy consumption for space heating and cooling purposes, and even more with inefficient and outdated air-conditioners (AC) - which are most common in developing countries. Although there are already conventional control strategies like ON/OFF control and PID in practice, their performance worsens once the building’s complexity increases and they cannot cope-up with the stochastic nature of the inside and outside environment. So one of the most efficient and preferred control strategies in complex systems like a building would be model predictive control (MPC). This study uses MPC to predict and control a 1.5 tonne inverter-based air conditioner. A cascaded control strategy - including various control methods, i.e., hysteresis, bang-bang, MPC, and an adaptive MPC, is implemented over the inbuilt thermostat-based control. MPC minimizes the setpoint tracking error and optimizes real-time thermal comfort by generating optimal temperature setpoints. An automated hardware setup is developed using Arduino Mega-2560, Raspberry Pi 3 B+ model, calibrated temperature, and humidity sensors that set the optimal setpoints to the air-conditioner via an infrared remote controller. Both MPC and adaptive MPC are able to maintain thermal comfort strictly within the desirable range, i.e., ±0.5 PMV throughout the experimental day, with thermal comfort hours of 24 hrs. and 23.67 hrs., respectively. On the contrary, with regular thermostat-based control, the thermal comfort is not maintained at any manually set temperature setpoint. With an adaptive MPC, energy saving of more than 7.06% is achieved as compared to the air-conditioner’s regular operation, running at a constant 24∘C - that is taken as the baseline for this study.

Safety Flight Control for a Quadrotor UAV Using Differential Flatness and Dual-Loop Observers

Focusing on a quadrotor unmanned aerial vehicle (UAV), the presence of unintended actuator faults and external disturbances increases the risk of a crash. Although plenty of efforts have been devoted, how to integrate capability analysis into safety control design is still an open issue. This article presents the design of a safety control system for quadrotor UAVs. Firstly, a system capability analysis method based on a differential flatness algorithm is developed, so that the derivatives (i.e., velocity, jerk, and snap) of flight trajectory can be formulated as flat variables. A tradeoff between system capability and permissible flight maneuverability is made to avoid actuator saturation. Secondly, dual-loop nonlinear disturbance observers are exploited to identify the actuator faults and disturbances, which can thereby be handled by a cascade control scheme. Moreover, the trajectory is regenerated online at the expense of degraded flight maneuverability or even emergency landing, in view of the remaining actuator control authority. When comparing to the existing methods, the gap among safety control, trajectory generation, and system capability analysis is bridged to ameliorate practical flight safety. Finally, flight tests are carried out to demonstrate the unique merits of the proposed system.

A Grid Connected Solar Photovoltaic System with Multilevel Shunt Active Power Filter for Power Quality Enhancement

This paper presents a shunt active power filter based on a three-phase 3-level Neutral Point Clamped (NPC) inverter for grid-connected Photovoltaic (PV) systems. The main objectives to be met are: i) Ensuring maximum power extraction from the PV panels, by forcing the voltage across the PV panel to track a suitable reference provided by P&amp;O algorithm; ii) Assuring Power Factor Correction (PFC) by forcing grid currents to be sinusoidal and in phase (or opposite phase) with grid voltages. In order to achieve these objectives, a cascade control strategy with two imbricated loops is designed. Lyapunov approach and sliding mode control are used in the inner loop to meet the PFC requirement. As for the outer loop, it is designed using the PI regulator and P&amp;O algorithm to satisfy the voltage regulation objective. Lastly, simulation results are performed in the MATLAB/SimPowerSystems environment to demonstrate the effectiveness of the proposed controller.

Integrated energy scheduling using wind-storage cascade control strategy in dynamic peak regulation right

• Wind-storage integration and electric-heat units participate in dynamic peak regulation right transaction. • Establish wind-storage cascade control strategy for deeply peak regulation. • Based on whole process peak regulation model of electric-heat units to establish scheduling model. • Quantitatively analyzed the benefits of the participants in different scenarios. • Verified the new scheduling strategy can reduce wind curtailment In view of the serious problem of wind curtailment in heating season of the "Three North Regions" in China, an intraday rolling optimization scheduling method is carried out according to wind-storage cascade control strategy combined with the dynamic peak regulation rights transaction which is based on the wind curtailment situation. Determine the operation state of the energy storage by judging when the wind curtailment is generated, and dynamically adjust the capacity of peak regulation rights transaction in-day according to the amount of wind curtailment. Considering the whole process peak regulation cost model of electric-heat units and wind-storage integration cost, and the goal is to maximize the overall benefit in the scheduling cycle, optimize the operation. Finally modeling by YALMIP and solved by CPLEX. The simulation results shown that the benefit improvement verifies the market feasibility, and the reduction of wind curtailment verifies the technical feasibility.