Comparison Of Different Control Methods Research Articles

Comparison of different control methods on the thermally activated building system (TABS) with large energy flexibility

Thermally Activated Building Systems (TABS) has great energy flexibility potential for the effective demand response, but the inherent large thermal inertia creates challenges for the control. Model Predictive Control (MPC) can improve the control efficiency while achieving certain objectives. However, the modeling mechanism of the TABS thermal behavior can lead to the difference in the controller performances. In this study, the white-box model, grey-box model, and black-box model based MPCs (referred to as W-MPC, G-MPC, and B-MPC) are developed and analyzed in depth for a case TABS with high heat flexibility potential. The performances of MPC strategies are investigated together with the baseline Rule Based Control (RBC) strategy under normal conditions as well as a variety of uncertainty events. In general, MPC strategies show better performance compared to the RBC. The prediction-based control can effectively maintain the indoor temperature within the constraints considering the uncertain disturbances and the gradual outdoor climate change. Moreover, MPC strategies help to increase the cost savings due to the effective load shifting by 30%-50%, and enhance the flexible energy utilization by 14%-29%. In terms of the comparison among the different MPC strategies, W-MPC shows better performance in the room temperature control, which reduces the violation of the indoor temperature constraint by 30% and 15% compared to G-MPC and B-MPC, respectively. G-MPC shows slight superiority concerning the economy and flexible energy usage. The normalized cost saving of G-MPC is approximately 3% and 8% lower compared to the W-MPC and B-MPC, respectively, while the utilization efficiencies of the flexible energy are approximately 6% and 12% higher.

Reviewing Control Paradigms and Emerging Trends of Grid-Forming Inverters—A Comparative Study

Grid-forming inverters (GFMs) have emerged as crucial components in modern power systems, facilitating the integration of renewable energy sources and enhancing grid stability. The significance of GFMs lies in their ability to autonomously establish grid voltage and frequency, enabling grids to form and improve system flexibility. Discussing control methods for grid-forming inverters is paramount due to their crucial role in shaping grid dynamics and ensuring reliable power delivery. This paper explores the fundamental and advanced control methods employed by GFMs, explaining their operational principles and performance characteristics. Basic control methods typically involve droop control, voltage and frequency regulation, and power-balancing techniques to maintain grid stability under varying operating conditions. Advanced control strategies encompass predictive control, model predictive control (MPC), and adaptive control, which influence advanced algorithms and real-time data for enhanced system responsiveness and efficiency. A detailed analysis and performance comparison of different control methods for GFM is presented, highlighting their strengths, limitations, and suitability for diverse grid environments. Through comprehensive studies, this research interprets the ability of various control strategies to mitigate grid disturbances, optimize power flow, and enhance overall system stability.

Distributed adaptive prescribed-time orbit containment control for satellite cluster flight

The distributed prescribed-time orbit containment control for the satellite cluster flight with multiple dynamic leaders is investigated. The directed information communication topology between followers is taken into account in the overall paper. When the satellite mass is assumed to be constant, a distributed prescribed-time orbit containment controller is, firstly, presented to drive the followers into the dynamic convex hull produced by multiple leaders. Then, the parameter uncertainty is considered, and a prescribed-time sliding mode estimator is introduced to estimate the desired velocity of each follower. Based on the estimated state, a novel distributed adaptive prescribed-time orbit containment control scheme is proposed. The Lyapunov stability theory is utilized to prove the prescribed-time stability of the closed-loop system. Finally, several numerical simulations and comparison of different control methods are provided to verify the effectiveness and superiority of the proposed control method.

Adaptive Fuzzy PID Car Control using a Bilateral Teleoperator

This paper investigates the application of Adaptive Fuzzy PID Control in the context of car control using a bilateral teleoperator. A bilateral teleoperator allows the operator to operate a remote car using his own controls and at the same time receive feedback on the car’s condition. The goal of the research is the analysis and comparison of different control methods, including PID controller, Adaptive Fuzzy PID controller, and the use of energy and wave variables of the bilateral teleoperator. The paper presents a car control model by means of a bilateral teleoperator, which was implemented in a simulation environment. Then performance comparisons of different control methods were made. The PID controller was used as the basic method, while the Adaptive Fuzzy PID controller was additionally included to achieve system adaptivity. Also, the use of energy and wave variables of the bilateral teleoperator was additionally investigated. The results of the comparison show that the use of bilateral teleoperator wave variables gave the best response of the control system. The analysis of signal waveforms and frequencies enabled more precise monitoring of the car’s condition and the detection of possible problems or instability in the system. This knowledge can be of great importance for improving the performance of car control by means of a bilateral teleoperator.

A Benchmarking Framework for Control Methods of Maritime Cranes Based on the Functional Mockup Interface

A benchmark framework for advanced control methods of maritime cranes is presented based on the use of the functional mockup interface. The system integrates different manipulator models, all the corresponding hydraulic systems, various vessels, and the surrounding environment for visualization. Different control methods can be transparently implemented and tested. A set of routine tests, different cost functions, and metrics are provided—taking into account several factors, including position accuracy, energy consumption, quality, and safety for both the cranes and the surrounding environment. The concept of operational profiles is introduced, allowing for definition of different standard transporting and lifting operations. By considering task-oriented routines, this benchmark suite allows the comparison of different control methods independently from the specific crane model to be controlled. Two alternative control methods for maritime cranes based on the use of artificial intelligence are extensively compared. The first method is based on the use of genetic algorithms, while the second method involves the use of particle swarm optimization. Simulation results are presented for both methods.

Comparison of Different Control Methods in Switched Reluctance Drive System

Comparison of Different Control Methods in Switched Reluctance Drive System

Simulation Based Performance Comparison of Different Control Methods of ZSI Feeding Industrial Drives

Simulation Based Performance Comparison of Different Control Methods of ZSI Feeding Industrial Drives

Pulse density modulated control patterns for inductively powered implantable devices based on energy injection control

High power inductively powered implantable devices (5–15 W) such as an artificial heart demand continuous power over widely varying coupling and loading conditions. An energy injection converter is suitable for driving the power transfer coil of an inductive power transfer system for this application because of its ability to control power flow over a large coupling range without any additional power stages. In addition it allows this to be done while maintaining soft-switching at all times. Here the authors propose a new control method based on pulse density modulation patterns. The proposed control is compared with other energy injection control methods, and it is found to have superior performance in terms of control action and linearity. It is also shown to improve the practical control range and decreases the component stress with improved resonant waveforms. The comparison of different control methods was performed through simulation and verified through practical implementation.