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Abstract Using renewable energy is increasingly prevalent as part of a global effort to safeguard the environment, with a reduction in $${\mathrm{CO}}_{2}$$ CO 2 being one of the primary objectives. A biogas plant provides an opportunity to produce green energy, but its profitability prevents it from being utilized more frequently. A suitable response to this economic issue would be flexible biogas production to exploit fluctuating energy prices. Nevertheless, the complex nature of the anaerobic digestion process that proceeds within the biogas plant and the wide range of substrates that may be utilized as the plant’s feeds make it challenging to achieve flexible biogas production truly. Most plant operators will rely on their experience and intuition to run the plant without knowing exactly how much biogas they will produce with the feed substrate. This work combines a system model estimation and feedback controller to provide an intuitive yet precise feedback control system. The system model estimation represents the biogas plant mathematically, and a total of six distinct approaches have been compared and evaluated. A PT1 model most accurately approximated the step-down and the step-up by the time percentage method, with the Akaike Information Criterion as the primary evaluation criterion for selecting the best model. The downward model was controlled by a discrete PI controller modified with the Root Locus Method and an Anti-Windup scheme, and the upward model was controlled by a state space controller. The quality of the controller was evaluated in both simulation and at the actual biogas plant in Grub, and the controller was able to reduce the biogas production rate approaching the setpoint in the expected period. Furthermore, the developed feedback control system is effortless enough to be installed in many biogas plants.

Feedback control systems consist of components such as sensory systems, state estimators, controllers, and actuators. By transmitting signals between these components across insecure transmission channels, feedback control systems become vulnerable to cyber-physical attacks. For example, passive eavesdropping attacks may result in a leak of confidential system and control parameters. Active deception attacks may manipulate the behavior of the state estimators, controllers, and actuators through the injection of spoofed data. To prevent such attacks, we must ensure that the transmitted signals remain confidential across the transmission channels, and that spoofed data is not allowed to enter the feedback control system. We can achieve both these goals by using cryptographic tools. By encrypting the signals, we achieve confidential signal transmission. By applying message authentication codes (MACs), we assert the authenticity of the data before allowing it to enter the components of the feedback control system. In this paper, a toolbox containing implementations of state-of-the-art high-performance algorithms such as the Advanced Encryption Standard (AES), the AEGIS stream cipher, the Keyed-Hash Message Authentication Code (HMAC), and the stream ciphers from the eSTREAM portfolio, is introduced. It is shown how the algorithm implementations can be used to ensure secure signal transmission between the components of the feedback control system, and general guidelines that the users must adhere to for safe operation are provided.

The present tutorial paper constitutes the second of a series of tutorials on manifold calculus with applications in system theory and control. The aim of the present tutorial, in particular, is to explain and illustrate some key concepts in manifold calculus such as covariant derivation and manifold curvature. Such key concepts are then applied to the formulation, to the control, and to the analysis of non-linear dynamical systems whose state-space are smooth (Riemannian) manifolds. The main flow of exposition is enriched by a number of examples whose aim is to clarify the notation used and the main theoretical findings through practical calculations.

Modular multilevel converters (MMCs) are primarily adopted for high-voltage applications, and are highly desired to be operated even under fault conditions. Researchers focused on improving current controllers to reduce the adverse effects of faults. Vector control in the DQ reference domain is generally adopted to control the MMC applications. Under unstable grid conditions, it is challenging to control double-line frequency oscillations in the DQ reference frame. Therefore, active power fluctuations are observed in the active power due to the uncontrolled AC component’s double line frequency component. This paper proposes removing the active power’s double-line frequency under unbalanced grid conditions during DQ transformation. Feedforward and feedback control methods are proposed to eliminate ripple in active power under fault conditions. An extraction method for AC components is also proposed for the power ripple control to eliminate the phase error occurring with the conventional high-pass filters. The system’s stability with the proposed controller is tested and compared with a traditional MMC controller using the Nyquist stability criterion. A real-time digital simulator (RTDS) and Xilinx Virtex 7-based FPGA were used to verify the proposed control methods under single-line-to-ground (SLG) faults.

Background: In developing countries, despite large public companies’ reliance on master data for decision-making, there is scant evidence to demonstrate their effective use of transactional data in decision-making because of its volatility and complexity. For the state-owned enterprise (SOE) studied, the complexity of generating high-quality transactional data manifests in relationships between customer call transactional data related to an electricity supply problem (captured by call centre agents, i.e. data creators) and technician-generated feedback (i.e. data consumers). Objectives: To establish the quality of customer calls transactional data captured using source system measurements. To compare this data set with field technicians’ downstream system transactions that indicated incorrect transactional data. Method: The study compared historical customer calls transactional data (i.e. source system data) with field technician-generated feedback captured on work orders (i.e. receiving system) in a power generation SOE, to ascertain transactional data quality generated and whether field technicians responded to authentic customer calls exclusively to mitigate operational expenses. Results: Mean values of customer call transactional data quality from the source system and technician-generated feedback on work orders varied by 1.26%, indicating that data quality measurements at the source system closely resembled data quality experiences of data consumers. The SOE’s transactional data quality from the source system was 80.05% and that of historical data set from evaluating feedback was 81.31% – percentages that exceeded average data quality measurements in literature. Conclusion: Using a feedback control system (FCS) to integrate feedback generated by data consumers to data creators presents an opportunity to increase data quality to higher levels than its current norm.

The aim of the present tutorial paper is to recall notions from manifold calculus and to illustrate how these tools prove useful in describing system-theoretic properties. Special emphasis is put on embedded manifold calculus (which is coordinate-free and relies on the embedding of a manifold into a larger ambient space). In addition, we also consider the control of non-linear systems whose states belong to curved manifolds. As a case study, synchronization of non-linear systems by feedback control on smooth manifolds (including Lie groups) is surveyed. Special emphasis is also put on numerical methods to simulate non-linear control systems on curved manifolds. The present tutorial is meant to cover a portion of the mentioned topics, such as first-order systems, but it does not cover topics such as covariant derivation and second-order dynamical systems, which will be covered in a subsequent tutorial paper.

This paper presents a dynamic modeling and control of doubly fed induction-generator (DFIG) based on the wind turbine systems. Active and reactive power control of the DFIG are based on the feedback technique by using the suitable voltage vectors on the rotor side. The rotor flux has no impact on the changes of the stator active and reactive power. The proposed controller is based on the feedback technique in order to reduce the oscillation of the generator. The control approach is estimated through the simulation result of the feedback controller assembled with DFIG wind turbines. It is applied by the feedback control based techniques in order to control the power flowing of DFIG and the power grid. Hence, an improved feedback control technique is adopted to get a better power flow transfer and to improve the dynamic system and transient stability. In stable condition, the improved performance of the controller, the proposed method is verified for the effectiveness of the control method is done in stable conditions.

Conventional continuous bladder irrigation (CBI) systems used in Urology have been labor-intensive and challenging for healthcare workers to manage consistently due to inter-observer variability in interpreting the blood concentration in the drainage fluid. The team has come up with a feedback system to control the saline flow-rate. It consists of a sensor probe that measures blood concentration in drainage fluid by measuring the light intensity absorbed by the samples. The other component is a gripper that adjusts the saline flow-rate based on the blood concentration detected. Results have shown that probe utilizing green color LED light can measure blood concentration between 0 and 18 percent. Besides, the gripper actuates to the blood concentration values detected accordingly. The quantification process reduces or even eradicates human error due to the subjective assessment of individual medical professionals.

Gallium-based liquid metal alloys have been attracting attention from both industry and academia as soft, deformable, reconfigurable and multifunctional materials in microfluidic, electronic and electromagnetic devices. Although various technologies have been explored to control the morphology of liquid metals, there is still a lack of methods that can achieve precise morphological control over a free-standing liquid metal droplet without the use of mechanical confinement. Electrochemical manipulation can be relatively easy to apply to liquid metals, but there is a need for techniques that can enable automatic and precise control. Here, we investigate the use of an electrochemical technique combined with a feedback control system to automatically and precisely control the morphology of a free-standing liquid metal droplet in a sodium hydroxide solution. We establish a proof-of-concept platform controlled by a microcontroller to demonstrate the reconfiguration of a liquid metal droplet to desired patterns. We expect that this method will be further developed to realize future reconfigurable liquid metal-enabled soft robots.

Exploiting the flux concentration configuration is a good alternative for designing a relatively low cost synchronous motor based on ferrite magnets. This paper discusses the design of a motor drive system based on a three-phase permanent magnet motor in which both the use of low cost ferrite and minimization of cogging torque have been adopted as design criteria. The dynamic modeling, parameter identification, and experimental characterization of the motor as well as the overall control system design have been performed. Simulation and experimental results are presented to demonstrate the correctness of the methodology and the feasibility of proposed motor drive solution and its related feedback control laws.