Cascade Control Structure Research Articles

Variable universe fuzzy control of once-through steam generator feedwater

The feedwater control of once-through steam generators (OTSGs) is critical to the safety and stability of nuclear power plants. As traditional PID control methods are difficult to ensure good control of OTSGs under flexible operating conditions, a variable universe fuzzy control (VUFC) method is proposed for OTSG feedwater. The widely-used cascade control structure was first adopted for the OTSG feedwater control system. Then the outer-loop pressure and inner-loop feedwater controllers were designed as fuzzy controllers with their fuzzy universes adjusted adaptively during plant operations. To assess the performance of the VUFC method, dynamic responses of an OTSG employing the fuzzy controllers were compared with those adopting the well-designed PID controllers under typical load change transients. Comparison results illustrate that the VUFC method can provide much better OTSG pressure control with smaller overshoots and shorter settling times, demonstrating the applicability of the VUFC method for OTSGs to provide excellent feedwater control.

Design of an Intelligent Cascade Control Scheme Using a Hybrid Adaptive Neuro-Fuzzy PID Controller for the Suppression of Drill String Torsional Vibration

Eliminating the excessive stick–slip torsional vibrations of drill strings by utilizing an effective controller can significantly increase penetration rates and reduce drilling operation costs. The present study aims to develop a fast and intelligent cascade control structure for a multi-degree-of-freedom drill string system under torsional vibrations. The proposed control configuration consists of two control loops in a cascade arrangement. The first controller estimates the top drive velocity reference from the actual drill bit velocity and its reference. The role of the second controller is to regulate the top drive velocity to its reference by generating the necessary torque for the drilling operation process to progress. Each control loop is designed based on a hybrid adaptive neuro-fuzzy PID and feedforward term. The latter assures fast regulation when there are sudden changes in operation. To evaluate the performance of the suggested cascade feedforward neuro-fuzzy PID (CFF-NFPID) control structure, extensive simulations were conducted using Matlab/Simulink. The simulation results clearly showed that the proposed CFF-NFPID controller provided high-performance control with variations in the weight on the bit and the desired drill bit rotary speed in comparison with that of cascade feedforward fuzzy PID, sliding-mode, cascade feedforward PID, cascade PID, and conventional PID controllers. Furthermore, the control robustness is very suitable despite the change in the system parameters.

Unified Control of Flight Dynamics and Actuators Using Local Accelerations

Control surface actuators usually come with their own servo control algorithm, which ensures that the deflection commanded by the flight control laws is quickly achieved. Therefore, flight control and servo control together form a cascaded control structure. Traditionally, the flight control laws (outer loop) and servo control laws (inner loop) are designed independently. However, recent applications demand an increasingly dynamic design of flight control, with actuator dynamics becoming a limiting factor. In this paper, a unified control design for actuators and flight dynamics is investigated. The local acceleration at the lifting surface (empennages and wing), close to the actuator, is fed back within an inner actuator control loop, allowing for faster compensation. The theoretical properties of the suggested control structure are discussed analytically first. Later, the concept is applied to a linear model for longitudinal aircraft motion. A classical state controller serves as a reference for comparison of the proposed strategy against the standard one with the actuator internal control law. Both controllers are designed using eigenstructure assignment, and the pole locations are numerically optimized. The closed-loop behavior is assessed in the time and frequency domains. The results promise significant improvements in terms of disturbance rejection and robustness.

Research on current harmonic suppression of permanent magnet synchronous motor using smith predictive controller

Abstract Due to the dead time added to the operation of the motor inverter, the generated current harmonics are introduced into the synchronous motor, increasing the harmonic content of the motor. The higher harmonic content is the 5th, 7th, 11th, and 13th current harmonics, which can cause motor torque ripple [1]. To suppress the current harmonics that cause torque ripple, a control method of using a PI controller and a quasi-proportional resonant controller in parallel is considered to suppress current harmonics. However, the introduction of a proportional resonant controller can cause greater overshoots in the current response, and external environmental influences can also generate current disturbances. Therefore, a method based on Smith prediction-PID and quasi-proportional resonance controller cascade control structure is proposed to suppress current harmonics and current overshoot in response to this problem. Finally, the effectiveness of this method was verified through simulation experiments, thereby improving the stability of synchronous motor operation.

Cascade PID Control for Altitude and Angular Position Stabilization of 6-DOF UAV Quadcopter

UAVs are commonly used in transportation, especially in the express delivery of light cargo parcels. However, controlling UAVs is difficult because of their complex structure and wide range of operations in space. The research contribution is proposed a cascade control structure using six PID controllers for the 6-DOF UAV quadcopter, that ensures the altitude angulars positions control at the desired values and maintains flight balance stability for the 6-DOF UAV quadcopter. First, the mathematical dynamic models for the 6-DOF UAV quadcopter have been researched and developed, including the translational dynamic mathematical model and the rotational dynamic mathematical model of the 6-DOF UAV quadcopter. This is a complex object with strong nonlinearity and difficult control. And then, the article introduces the method of designing six PID controllers for 6-DOF UAV quadcopter to meet the requirements, based on applying the Ziegler-Nichols experimental method. Applying the Ziegler-Nichols experimental method makes the process of designing a UAV quadcopter control system simple, straightforward and heuristics with fast controller parameters tuning. Next, the article presents the results of modeling and simulation of the 6-DOF UAV quadcopter control system on Matlab/Simulink. The simulation results show that the six proposed PID controllers have ensured the flight balance stability at the desired altitude and angular positions with overshoot less than 20%, steady-state error less than 1%. This shows the prospect of applying the proposed PID control method to physical UAVs, easily adjusting PID parameters to suit the flight environment.

Robust Fractional-Order PI/PD Controllers for a Cascade Control Structure of Servo Systems

In this paper, a cascade control structure is suggested to control servo systems that normally include a servo motor in coupling with two kinds of mechanism elements, a translational or rotational movement. These kinds of systems have high demands for performance in terms of fastest response and no overshoot/oscillation to a ramp function input. The fractional-order proportional integral (FOPI) and proportional derivative (FOPD) controllers are addressed to deal with those control problems due to their flexibility in tuning rules and robustness. The tuning rules are designed in the frequency domain based on the concept of the direct synthesis method and also ensure the robust stability of controlled systems by using the maximum sensitivity function. The M-Δ structure, using multiplicative output uncertainties for both control loops simultaneously, is addressed to justify the robustness of the controlled systems. Simulation studies are considered for two kinds of plants that prove the effectiveness of the proposed method, with good tracking of the ramp function input under the effects of the disturbances. In addition, the robustness of the controlled system is illustrated by a structured singular value (µ) plot in which its value is less than 1 over the frequency range.

Wind–PV–Battery Hybrid Off-Grid System: Control Design and Real-Time Testing

The paper presents the design and implementation of decentralized control for a PV–wind–battery hybrid off-grid system with limited power electronics devices and sensors. To perform well without using any maximum power point tracking (MPPT) technique from the wind turbine (WT) based on a permanent-magnet brushless DC generator (PMBLDCG) and solar panels (PVs) and balance the power in the system, a cascade control structure strategy based on a linear active disturbance rejection controller (LADRC) is developed for the two-switch DC-DC buck-boost converter. Moreover, to ensure an uninterruptible power supply to the connected loads with a constant voltage and frequency, a cascade d-q control structure based on LADRC is developed for the interfacing single-phase inverter. Furthermore, the modeling and controller parameters design are presented. The performance under all operation conditions of the hybrid off-grid configuration and its decentralized control is validated by simulation using MATLAB/Simulink and in real-time using a small-scale hardware prototype.

Finite‐time sliding mode fault‐tolerant control of PEM fuel cell air supply system

AbstractProton exchange membrane (PEM) fuel cell air supply system is primarily responsible for delivering air to the fuel cell at a specific stoichiometric ratio for chemical reaction. The stoichiometric ratio will be impacted by the sudden change in load and system failure. Under the aforementioned circumstances, precise and timely air supply regulation is required to avoid irreparable PEM damage. In order to enhance the robustness and performance of the fuel cell, a cascaded finite time sliding mode fault‐tolerant control method is proposed for the air supply system of PEMFC. The control objective is to adjust the oxygen excess ratio at the cathode flow field, which can avoid the occurrence of oxygen starvation in the PEM fuel cell when the load current changes rapidly or when fault occurs. A cascaded controller structure is introduced, where, in the inner loop, an adaptive sliding mode controller is designed to reconstruct fault signal and track the optimal output trajectory and, in the outer loop, a finite‐time observer is employed to obtain the expected output trajectory. The proposed control scheme is capable of fault‐tolerant tracking of the optimal oxygen excess ratio within finite time. The effectiveness of proposed fault‐tolerant control algorithm is verified through hardware‐in‐the‐loop (HIL) studies.

Optimizing the series cascade control structure for nonminimum phase system regulation

AbstractThis work elucidates the control of integrating a nonminimum phase system via a series cascade scheme with fractional‐order P.I. (Proportional–Integral) plus D (Derivative) controller. The traditional Internal Model Control (IMC) is adopted for inner loop controller design. The feedback D controller is synthesized with the outer loop process model, showing the proposed work's universality. The outer loop controller is suggested in the IMC framework after the accountability of fractional‐filter and inverse response compensator. This combination is revealed to enhance performance without compromising robustness. The Riemann sheet principle is explored to compute the stability of the suggested controller. The sensitivity analysis has asserted the robustness. More importantly, the optimal value of controller settings is achieved via the Teaching Learning Based Optimization (TLBO) algorithm. This TLBO algorithm uses an objective function that minimizes Integral Square Error. Two illustrative problems are utilized to examine the recommended control structure's virtue.

Cascade NMPC-PID control strategy of active heave compensation system for ship-mounted offshore crane

In this paper, the problem associated with active heave motion compensation during heavy-lift operations performed by ship-mounted offshore cranes beneath rough marine environment is investigated. To effectively decouple the correlated motion of the suspended payload from the support vessel via the secondary regulated active heave compensation (SRAHC) system, a novel hierarchical control strategy is proposed by integrating a cascade control structure with an adaptive robust control scheme that incorporates a vertical motion forecast algorithm based on autoregressive integrated moving average (ARIMA) model, a conventional proportional-integral-derivative (PID) framework, and a nonlinear model predictive control (NMPC) method. The introduction of the cascade structure is motivated by its prompt error response against control lag and efficient system order reduction for computational burden alleviation, which forms a crucial foundation for the NMPC-based real-time regulation of PID gains, ensuring optimal evolution of the SRAHC system while improving its practical feasibility. Furthermore, the enhancements in heave compensation and trajectory tracking performance, noise resistance, constraint satisfaction, and engineering application potential of the proposal are demonstrated through a thorough comparative analysis conducted in a practical co-simulation research system.

Adaptive Control of Quadrotors in Uncertain Environments

The problem addressed in this article consists of the motion control of a quadrotor affected by model disturbances and uncertainties. In order to tackle model uncertainty, adaptive control based on reinforcement learning is used. The distinctive feature of this article, in comparison with other works on quadrotor control using reinforcement learning, is the exploration of the underlying optimal control problem in which a quadratic cost and a linear dynamics allow for an algorithm that runs in real time. Instead of identifying a plant model, adaptation is obtained by approximating the performance index given by the Q-function using directional forgetting recursive least squares that rely on a linear regressor built from quadratic functions of input/output data. The adaptive algorithm proposed is tested in simulation in a cascade control structure that drives a quadrotor. Simulations show the improvement in performance that results when the proposed algorithm is turned on.

Robust Two-Layer Control of DC Microgrids With Fluctuating Constant Power Load Demand

This paper proposes a cascaded control structure for the regulation of DC Microgrids (MG). It is well-known that the negative impedance characteristics of a constant power load (CPL) adversely affect the stability of the network, and can cause problems such as voltage collapse or damage the electronic components. To mitigate this, we propose a two-layer control structure, where at the inner layer, the proposed controller achieves fast tracking of the supplied reference points and ultimate boundedness of the trajectories in a desired set. The outer layer generates the inner layer reference points, accounts for system constraints, and introduces robustness of the voltage dynamics to unknown perturbations of the CPL demand. For the first time, an investigation of the nonlinear geometric behaviour of the CPL is carried out to derive necessary conditions that ensure boundedness of the network dynamics and feasible regulation to a desired equilibrium set. Finally, Control Lyapunov functions are formulated to prove the stability and estimate the region of attraction of the closed loop dynamics. A simulated scenario of a meshed MG network is presented to confirm the validity of the results.

A reinforcement learning-based temperature control of fluidized bed reactor in gas-phase polyethylene process

This study investigates using deep reinforcement learning (DRL) with proportional-integral-derivative (PID) control for temperature cascade control in a fluidized bed reactor within a commercial gas-phase polyethylene process. The heat exchange system's nonlinearity and frequent disturbances pose challenges for PID controllers, particularly under varying conditions. To address this, a PID-DRL cascade control scheme is developed, where a DRL controller is used in the secondary loop. The DRL controller, designed using the actor-critic framework, is trained using the Deep Deterministic Policy Gradient algorithm. The DRL controller is evaluated in three stand-alone secondary loop experiments, as well as three cascade control experiments. Results reveal the DRL controller surpass the traditional PID controller in both scenarios. The DRL controller shows better set point tracking and interference suppression, indicated by lower integral absolute error (IAE) values. The proposed cascade control structure can be used to enhance reactor stability and product quality in gas-phase polyethylene processes.

Relocated internal model control based cascade control strategy for stable and unstable systems with delay

To control unstable and stable plants a new series cascade control structure (SCCS) is proposed. The proposed SCCS incorporates two or three controllers (setpoint tracking controller, secondary disturbance rejection controller and stabilising controller for only unstable plants). Internal model control scheme (IMCS) augmented with integration of square error (ISE) minimisation along with robustness considerations are applied to design the secondary loop disturbance rejection controller. In contrast, relocated IMCS augmented with ISE minimisation is applied for the outer loop or setpoint tracking controller. Routh Hurwitz stability criteria and maximum sensitivity considerations are used to design the proportional-derivative (PD) controller, which stabilises the unstable plant. It is important to note that the suggested SCCS only needs four controller parameters to be tuned, which is less than the recently reported techniques. Robust stability analysis of the proposed SCCS is performed in the presence of uncertainty. The simulation results depict that the suggested approach imparts pre-eminent improvement in closed-loop performance such as faster setpoint tracking and better disturbance rejection for nominal and perturbed plants.

Cascaded reinforcement learning based supply temperature control

In this work, a Q-learning based supply temperature control approach for a demonstrator building is proposed. The purpose is to improve the temperature behaviour inside the building and to tackle comfort problems such as overheating and undercooling which cannot be coped with by the standard heating curve. The Q-learning controller considers predicted future weather data as system states. This can be shown to be superior to Q-learning controllers without weather prediction. Furthermore, in order for the controller to capture different thermal effects of different time constants, a cascaded control structure is designed: An inner Q-learning based controller deals with thermal effects of smaller time constants. It is wrapped by an outer slower Q-learning controller which can tackle effects of larger time constants. Therewith, further improvement of comfort can be achieved.

Direct Predictive Voltage Control for Grid-Connected Permanent Magnet Synchronous Generator System

In this paper, a direct predictive voltage control (DPVC) is proposed for the grid-connected permanent magnet synchronous generator (PMSG) system. In the proposed strategy, the dc-link voltage regulation and power regulation terms are merged into one cost function, thereby eliminating the conventional cascade control structure. The strategy selects the voltage vector that not only will generate a dc-link voltage closer to the setpoint at instant <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$k+2$</tex-math></inline-formula> , but will generate an active power that can further reduce that voltage error for the future instant. To cope with the mismatch between the actual and nominal parameters, Kalman filter has been added to compensate for the steady-state error. Besides, to enhance the dynamic performance and to save the effort of parameter tuning, the weighting factor is further eliminated from the cost function by sorting the terms into two groups and independently evaluating each group in turn. To fully validate the effectiveness of the proposed strategy, the experimental test waveforms of the DPVC strategy with and without weighting factor have been presented and compared with that of the conventional PI-MPC strategy in various testing conditions.

Nonlinear control of permanent magnet synchronous generators (PMSG) using feedback linearization

This paper presents nonlinear control of permanent magnet synchronous generators using feedback linearization. Permanent-magnet synchronous generators (PMSGs) are commonly used for small variable-speed wind turbines to produce highefficiency, high-reliability, and low-cost wind power generation. To eliminate the effects of nonlinearity caused by magnetic saturation, an input–output feedback linearization technique is applied to design the high-performance nonlinear current controllers. With this nonlinear control scheme, output voltage responses become faster than those in cascade control structures. Thus, the size of the output filter capacitor can be much reduced since fast voltage control is feasible. As with usual PWM power converters, in addition, the input current is regulated in a sinusoidal waveform. The proposed control scheme provides the wind generation system with the maximum efficiency and high dynamic performance.

Cascaded Control System Design for Quadrotor UAV through Relay with Embedded Integrator-Based Automatic Tuning Approach

Due to their enormous characteristics and applicability, quadrotor unmanned aerial vehicles (UAVs) have enjoyed much popularity lately. However, designing a stable control strategy for quadrotors still remains one of the major concerns mainly due to the requirement of an accurate system model. They are naturally underactuated systems, with complex and nonlinear dynamics as well as interaxes couplings. Considering the dynamical complexities of these vehicles, one of the efficient methods is to utilize the relay feedback experiments and automatic tuning approach to tackle these issues. This paper investigates the employment of the relay with embedded integrator approach, wherein the quadrotor dynamics are estimated effectively with minimal parameters as compared to previously utilized relay with hysteresis technique. Frequency sampling filter (FSF) is further utilized for the extraction of the needful data through the signals obtained using the relay experiments, followed by the estimation of the plant dynamics. PID controllers have then been developed using the approximated quadrotor models. Which are used in the proposed cascade control structure for the quadrotor. The demonstrated results and analysis present the efficacy of designed control system technique for the quadrotor UAV.

A cascaded NPID/PI scheme for the regulation of stack voltage in proton exchange membrane fuel cell

In this work, a higher-order Proton Exchange Membrane (PEM) Fuel Cell system is controlled using a cascaded control approach. The primary and secondary controllers, NPID/PI, are non-linear proportional-integral-derivative and proportional-integral, respectively. The suggested cascade approach controls the stack voltage by adjusting the air compressor voltage to maintain the oxygen excess ratio value within limits. Two additional cascade control structures, PID/PI and FOPID/FOPI (fractional order PID and fractional order PI), are also created for a fair comparison. A genetic algorithm is used to determine the controller's optimal parameters by minimising the time integral absolute error of the primary controller. Results show that NPID/PI control structure achieves the minimum value of settling time and overshot (0.9514 s, 0.021%) compared to FOPID/PI (1.8980 s, 0.036%) and PID/PI (3.2308 s, 0.092%), respectively. Finally, it can be concluded from the result of setpoint tracking, disturbance rejection, and noise suppression that the proposed controller is efficient and robust compared to other designed controllers.

Tracking control for a cascade perturbed control system using the active disturbance rejection paradigm

In this paper the stability of a closed-loop cascade control system in the trajectory tracking task is addressed. The considered plant consists of underlying second-order fully actuated perturbed dynamics and the first order system which describes dynamics of the input. The main theoretical result presented in the paper concerns stability conditions formulated based on the Lyapunov analysis for the cascade control structure taking advantage of the active rejection disturbance approach. In particular, limitations imposed on a feasible set of an observer bandwidth are discussed. In order to illustrate characteristics of the closed-loop control system simulation results are presented. Furthermore, the controller is verified experimentally using a two-axis telescope mount. The obtained results confirm that the considered control strategy can be efficiently applied for mechanical systems when a high tracking precision is required.