Cascaded Feedback Control Research Articles

Analysis and control strategy of standalone PV system with various reference frames

Abstract Renewable energy sources like solar power are the more convenient source of renewable energy. Nowadays, increasing the energy demand may create many disturbances in power system distribution. To overcome the necessity of power demand, all are focusing on generation of more energy from clean technologies with increased development in power distribution systems using the renewable energy sources. This work aims to propose a standalone PV system with an LCL filter, with two cascaded feedback control loops with an appropriate controller for three reference frame. This work concerns the topology for three reference frames such as synchronous, standalone, and natural reference frames with the respective controllers (PI and PR). The topology contains two cascaded feedback control loops such as DC-link voltage control loop (PI) cascaded with the internal current loop (PI and PR). These commonly used controllers are implemented in various well-known reference frames for the PV system and their steady-state performance is also evaluated in terms of total harmonic distortion. Finally, the simulation results from a two-stage 5.5 kW, 440 V (L–L), three-phase standalone PV system are provided to confirm the theoretical analysis and effectiveness of the control schemes.

Reinforcement Learning-Based Cascade Motion Policy Design for Robust 3D Bipedal Locomotion

This paper presents a novel reinforcement learning (RL) framework to design cascade feedback control policies for 3D bipedal locomotion. Existing RL algorithms are often trained in an end-to-end manner or rely on prior knowledge of some reference joint or task space trajectories. Unlike these studies, we propose a policy structure that decouples the bipedal locomotion problem into two modules that incorporate the physical insights from the nature of the walking dynamics and the well-established Hybrid Zero Dynamics approach for 3D bipedal walking. As a result, the overall RL framework has several key advantages, including lightweight network structure, sample efficiency, and less dependence on prior knowledge. The proposed solution learns stable and robust walking gaits from scratch and allows the controller to realize omnidirectional walking with accurate tracking of the desired velocity and heading angle. The learned policies also perform robustly against various adversarial forces applied to the torso and walking blindly on a series of challenging and unstructured terrains. These results demonstrate that the proposed cascade feedback control policy is suitable for navigation of 3D bipedal robots in indoor and outdoor environments.

Design, development, and flight testing of a tube-launched coaxial-rotor based micro air vehicle

This paper describes the development and flight testing of a compact, re-configurable, hover-capable rotary-wing micro air vehicle that could be tube launched for increasing mission range. The vehicle design features a coaxial rotor with foldable blades, thrust-vectoring mechanism for pitch/roll control and differential rpm for yaw control. The vehicle was stabilized using a cascaded feedback controller implemented on a 1.7-gram custom-designed autopilot. Wind tunnel tests conducted using a single-degree-of-freedom stand demonstrated gust-tolerance up to 5 m/s, which was verified via flight testing. Finally, the 366-gram vehicle was launched vertically from a pneumatic cannon followed by a stable projectile phase, passive rotor unfolding, and transition to a stable hover from arbitrarily large attitude angles demonstrating the robustness of the controller.

Evaluation of Process Control Schemes for Sour Water Strippers in Petroleum Refining

For the sour water strippers in petroleum refinery plants, three prediction models were developed first, including the estimators of sour water feed concentrations using convenient online measurements, the minimum reboiler duty and the corresponding internal temperature at a specific location (Tstage,29). Feedforward control schemes were developed based on these prediction models. Four categories of control schemes, including feedforward, feedback, feedback with external reset, and feedforward-feedback, were proposed and evaluated by the rigorous dynamic simulation model of the sour water stripper for their dynamic responses to the sour water feed stream disturbances. The comparison of control performance, in terms of the settling time, integrated absolute error (IAE) of the NH3 concentration of the stripped sour water and IAE of the specific reboiler duty, reveals that FFT (feedforward control of Tstage,29) and FBA-DT3 (feedback control with 3 min concentration measurement delay) are the best control schemes. The second-best control scheme is FBAT (cascade feedback control of concentration with temperature).

Cascade Integral Predictors and Feedback Control for Nonlinear Systems with Unknown Time-varying Input-delays

In this paper, we consider the problem of predictor design for nonlinear systems in the presence of unknown time-varying input-delays. A cascade integral high-gain predictor is proposed to estimate the future state. With a distinctive structure, the predictor can handle unknown delays and eliminate the “peaking phenomenon” during the transient period. Then, a predictor-based output feedback control is designed to guarantee the boundedness of system states. Lyapunov-Krasovskii functional and perturbation theories are used to prove the convergence of the estimation error and the closed-loop system. Finally, simulation results illustrate the superior performance of the cascade integral predictor compared to the standard high-gain predictor.

Overcoming fundamental limitations of wind turbine individual blade pitch control with inflow sensors

AbstractIndividual pitch control (IPC) provides an important means of attenuating harmful fatigue and extreme loads upon the load bearing structures of a wind turbine. Conventional IPC architectures determine the additional pitch demand signals required for load mitigation in response to measurements of the flap‐wise blade‐root bending moments. However, the performance of such architectures is fundamentally limited by bandwidth constraints imposed by the blade dynamics. Seeking to overcome this problem, we present a simple solution based upon a local blade inflow measurement on each blade. Importantly, this extra measurement enables the implementation of an additional cascaded feedback controller that overcomes the existing IPC performance limitation and hence yields significantly improved load reductions. Numerical demonstration upon a high‐fidelity and nonlinear wind turbine model reveals (1) 60% reduction in the amplitude of the dominant 1P fatigue loads and (2) 59% reduction in the amplitude of extreme wind shear‐induced blade loads, compared with a conventional IPC controller with the same robust stability margin. This paper therefore represents a significant alternative to wind turbine IPC load mitigation as compared with light detection and ranging‐based feedforward control approaches.

Multi-layer perception based model predictive control for the thermal power of nuclear superheated-steam supply systems

Nuclear superheated-steam supply systems (Su-NSSS) produces superheated steam flow for electricity generation or process heat. Although the current Su-NSSS control law can guarantee satisfactory closed-loop stability, which regulates the neutron flux, primary coolant temperature and live steam temperature by adjusting the control rod speed as well as primary and secondary flowrates, however, the control performance needs to be further optimized. Motivated by the necessity of optimizing the thermal power response, a novel multi-layer perception (MLP) based model predictive control (MPC) is proposed in this paper, which is constituted by a MLP-based prediction model and the control input designed along the direction opposite to the gradient of a given performance index. It is proved theoretically that this MLP-based MPC guarantees globally-bounded closed-loop stability. Finally, this newly-built MLP-based MPC is applied to the thermal power control of a Su-NSSS, whose implementation is given by forming a cascaded feedback control loop with the currently existing Su-NSSS power-level control in the inner loop for stabilization and with this new MPC in the outer loop for optimization. Numerical simulation results verify the correctness of theoretical result, and show the satisfactory improvement in optimizing the thermal power response.

Optimized Thermal Power Control for Nuclear Superheated-Steam Supply Systems Based on Multi-Layer Perception

Abstract Nuclear superheated-steam supply systems (Su-NSSS) produces superheated steam flow for electricity generation or process heat. Though the current Su-NSSS control law can guarantee satisfactory closed-loop stability, which regulates the nuclear power, primary coolant temperature and live steam temperature through adjusting the control rod speed as well as primary and secondary flowrates, however, the control performance needs to be further optimized. Motivated by the necessity of optimizing the thermal power response, a novel multi-layer perception (MLP) based model predictive control (MPC) is proposed in this paper. The thermal power of Su-NSSS is predicted by an MLP with online learning algo-rithm, and the control input is designed in the direction opposite to the gradient of a given performance index. Then, it is proved that this MLP-based MPC guarantees globally-bounded closed-loop stability. Finally, this newly-built MLP-based MPC for thermal power is implemented by forming a cascaded feedback control loop with the current Su-NSSS controller in the inner loop and this MPC in the outer loop. Numerical simulation results verify the correctness of theoretical result, and show the satisfactory improvement in optimizing the thermal power response.

Concurrent Task Scheduling and Dynamic Voltage and Frequency Scaling in a Real-Time Embedded System With Energy Harvesting

Energy harvesting is a promising technique to overcome the limit on energy availability and increase the lifespan of battery-powered embedded systems. In this paper, the question of how one can achieve the prolonged lifespan 1 of a real-time embedded system with energy harvesting capability (RTES-EH) is investigated. The RTES-EH comprises a photovoltaic (PV) panel for energy harvesting, a supercapacitor for energy storage, and a real-time sensor node as the embedded load device. A global controller performs simultaneous optimal operating point tracking for the PV panel, state-of-charge (SoC) management for the supercapacitor, and energy-harvesting-aware real-time task scheduling with dynamic voltage and frequency scaling (DVFS) for the sensor node, while employing a precise solar irradiance prediction method. The controller employs a cascaded feedback control structure, where an outer supervisory control loop performs real-time task scheduling with DVFS in the sensor node while maintaining the optimal supercapacitor SoC for improved system availability, and an inner control loop tracks the optimal operating point of the PV panel on the fly. Experimental results show that the proposed global controller lowers the task instance drop rate by up to 63% compared with the baseline controller within the same service time (i.e., from sunrise to sunset). 1 The lifetime of a battery is usually less than five years, and in this paper we propose to use supercapacitor instead of battery for embedded systems to prolong the lifespan of the whole system to more than 20 years.

Dynamic Pricing for Toll Lanes - a Case Study

Abstract: This paper reports about the development, analysis, simulation, and real-life measurements of the dynamic toll fee control algorithm for the recently opened Fast Lane, i.e. the additional parallel HOT lane on the part of the Jerusalem - Tel Aviv Highway 1 with three free lanes that runs westwards between the Ben Gurion Airport and Tel Aviv. It was found that cascaded feedback control is suitable, where the inner loop determines the toll fee increment with the inflow to the HOT lane as feedback signal, while the outer loop determines the inflow reference based on the average speed on the HOT lane as the feedback signal, and the government mandated lower average speed as its reference. Measured morning rush hour data for the toll lane under manual and automatic control are presented.

Hierarchical Constraint‐Based Singularity Avoidance for Multi‐Axis Robots

AbstractA generalized reflexive approach for Hierarchical Constraint‐Based Singularity Avoidance (HCB‐SA) is proposed and demonstrated for the multi‐axis robot control of a six Degrees Of Freedom (DOF) hybrid manipulator system. The concept utilizes a dynamic adaptation of virtual constraints by introducing virtual damped actuation on the velocity control level and an anisotropic reflexive trajectory deflection depending on the robot constraints on the position control level. Redundant or low priority DOFs can be used to minimize the pose error in the more important DOFs reflexively without calculating new trajectories. Accordingly, the end‐effector can be safely controlled in the vicinity of singularities and all constraints in the task and joint space can be surely hold. Furthermore, the proposed cascaded feedback control with the generalized HCB‐SA algorithm is able to react on the presence of external disturbances which is validated using software‐in‐the‐loop simulation on the real‐time control system. (© 2014 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Neural network model predictive control of a styrene polymerization plant: online testing using an electronic worksheet

AbstractThe batch styrene polymerization process presents transient and nonlinear temperature behavior. In this work, manual control and open loop experiments were carried out in order to build a process knowledge database. Initially, a cascade feedback control loop was implemented by manipulating the thyristor unit of the electrical heater in the thermal fluid tank. Aiming at the MPC development, algebraic equations of a neural network and its adjusted parameters were implemented in an electronic worksheet. Every five seconds, the worksheet was updated with measurements (reactor temperature, thermal fluid temperature and thyristor position) by means of the OLE for the Process Control protocol (OPC). The one-step-ahead temperature prediction was then employed in the objective function of the worksheet solver which used Visual Basic Applications programming. The manipulated variable action was then calculated and sent to the process. A hybrid controller (cascade feedback and MPC) outperformed the pure strategies since the time-integral performance indexes, IAE and ITAE, were reduced by around 22 % and 32 %, respectively. Methodology for the Model Predictive Control presented in this study was considered feasible because the solver of Microsoft Office Excel (2007) is very friendly, easy to understand and ready to implement using VBA.

Cascaded Feedback Control Scheme for Trajectory Tracking of Robot Manipulator Systems with Actuator Dynamics

Control of nonlinear mechanical systems that have complex actuator dynamics is difficult, because the actuator dynamics are highly nonlinear and the entire system, including both the robot manipulators and actuators, is of a high order. In this study, we propose a feedback control scheme for motion control of nonlinear high-order systems and prove that it can improve the trajectory tracking performance of a robot manipulator system with actuator dynamics. Simulations and experimental results demonstrate the efficacy of the proposed control scheme.

Development of a cascaded controller for temperature and core growth rate in vapour-phase axial deposition

A cascaded feedback control strategy for an industrial vapour-phase axial deposition (VAD) process is investigated in this paper. VAD is a widely used process in the creation of high-purity glass for optical fibre. In previous work a soot tip surface temperature controller was developed for the VAD process to reduce the effects of core soot temperature variation on deposition geometry, leading to a more stable process. However, it is desired to regulate both the core soot and clad soot such that they deposit at the same axial rate to provide a more uniform product. This paper presents the development of a cascaded controller strategy and process model to couple and regulate the surface temperature and deposition rates of core and clad soot. Simulation studies demonstrate a potential improvement in the uniformity of the core and clad soot geometry over the soot product length.

1A2-C05 フィードバック階層制御による空気圧駆動システムの軌道追従制御実験(アクチュエータの機構と制御)

1A2-C05 フィードバック階層制御による空気圧駆動システムの軌道追従制御実験(アクチュエータの機構と制御)

フィードバック階層制御による空気圧駆動システムの軌道追従制御

Generally speaking, pneumatic systems have the merit of high power-to-mass ratio. However, the entire system becomes high-order and non-linear due to the compressibility of air and valve dynamics. In this paper, we propose a cascaded feedback control scheme for trajectory tracking of pneumatic drive systems. We mathematically prove that the proposed scheme can effectively reduce trajectory tracking error even though nonlinear dynamics of air compressibility is considered. Through some simulation and experimental results, the trajectory tracking performance is demonstrated.

The bifurcation behavior of a polyurethane continuous stirred tank reactor

In this work the open-loop nonlinear bifurcation analysis of a continuous stirred tank reactor where polyurethane polymerization reactions take place is carried out. The effect of potential manipulated, disturbance and design variables on the reactor nonlinear behavior is addressed. Moreover, the impact of cascade feedback control on the steady-state multiplicity pattern is also discussed. It is shown that cascade control introduces new nonlinearity patterns increasing closed-loop sensitivity.

Controlling the nitrite:ammonium ratio in a SHARON reactor in view of its coupling with an Anammox process

The combined SHARON-Anammox process for treating wastewater streams with high ammonia load is the focus of this paper. In particular, partial nitritation in the SHARON reactor should be performed to such an extent that a nitrite:ammonium ratio is generated which is optimal for full conversion in an Anammox process. In the simulation studies performed in this contribution, the nitrite:ammonium ratio produced in a SHARON process with fixed volume, as well as its effect on the subsequent Anammox process, is examined for realistic influent conditions and considering both direct and indirect pH effects on the SHARON process. Several possible operating modes for the SHARON reactor, differing in control strategies for O2, pH and the produced nitrite:ammonium ratio and based on regulating the air flow rate and/or acid/base addition, are systematically evaluated. The results are quantified through an operating cost index. Best results are obtained by means of cascade feedback control of the SHARON effluent nitrite:ammonium ratio through setting an O2 set-point that is tracked by adjusting the air flow rate, combined with single loop pH control through acid/base addition.

A Cascade Feedback Control Approach for Hypnosis

This article studies the problem of controlling the drug administration during an anesthesia process, where muscle relaxation, analgesia, and hypnosis are regulated by means of monitored administration of specific drugs. On the basis of a seventh-order nonlinear pharmacokinetic-pharmacodynamic representation of the hypnosis process dynamics, a cascade (master/slave) feedback control structure for controlling the bispectral index (BIS) is proposed. The master controller compares the measured BIS with its reference value to provide the expired isoflurane concentration reference to the slave controller. In turn, the slave controller manipulates the anesthetic isoflurane concentration entering the anesthetic system to achieve the reference from the master controller. The advantage of the proposed cascade control structure with respect to its noncascade counterpart is that the former provides operation protection against BIS measurement failures. In fact, under a BIS measurement fault, the master control feedback is broken and the slave controller operates under a safe reference value. Extensive numerical simulations are used to illustrate the functioning of the proposed cascade control structure.

Coupling the SHARON process with Anammox: Model-based scenario analysis with focus on operating costs

The combined SHARON-Anammox process for treating wastewater streams with high ammonia concentration is discussed. Partial nitritation in the SHARON reactor should be performed to such an extent that an Anammox-optimal nitrite:ammonium ratio is generated. The SHARON process is typically applied to sludge digestion rejection water in order to relieve the ammonium load recycled to the main plant. A simulation study for realistic influent conditions on a SHARON reactor with a fixed volume and operated with constant air flow rate reveals that the actual nitrite:ammonium ratio might deviate significantly from the ideal ratio and might endanger operation of the subsequent Anammox reactor. It is further examined how the nitrite:ammonium ratio might be optimized. A cascade pH control strategy and a cascade O2 control strategy are tested. Simulation results are presented and the performance of the different strategies is assessed and quantified in an economic way by means of an operating cost index. Best results are obtained by means of cascade feedback control of the SHARON effluent nitrite:ammonium ratio through setting an O2-set-point that is tracked by adjusting the air flow rate.