Rectangular Electrode Characteristic in Electrodynamic Solid Particle Measurement

Electrodynamic sensor was used in process industry because of lower price and robust designed. It is also used to increase the efficiency of energy and raw materials usage and to improve product quality and process efficiency. Three types of electrode are available in particular application such as pin shape, quarter ring shape and ring shape. This paper focused on the investigation of the pin shape structure and the characteristic of the rectangular shape by using different structure sizes of various lengths and with fixed width. Non-instrusive method was applied to the design of rectangular electrode. The characteristic based on sensitivity of electrode and the spatial filtering effect of sensor will be investigated by using different size of electrodes.Then, the model will be proposed and compared with experimental result

Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm

This study focused on data-driven tools and controller structure in the data-driven control scheme. Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. Meanwhile, the controller structure refers to the controller design that is highly dependent on the input and output system. The existing data-driven neuroendocrine-PID (NEPID) utilizes the simultaneous perturbation stochastic approximation (SPSA) algorithm as the data-driven tool. However, this SPSA-based method is unable to find the optimal value of the design parameter due to unstable convergence obtained that degrades the controller performance in MIMO systems. Thus, a safe experimentation dynamics (SED) algorithm is selected to solve this unstable convergence but still not enough to achieve high accuracy because the update designed parameter only depends on the fixed step size gain. For the controller structure, the hormone secretion rate parameter of the existing NEPID is constant during the experimental time. However, control accuracy is insufficient because the secretion rate and control variable error are not able to interact directly and limits the controller capability. Besides, in the existing NEPID controller structure of the SISO system, only a single node of hormone regulation is used due to a single control variable. Meanwhile, in the MIMO systems, many control variables available that interact with each other, and the single node hormone regulation of NEPID is still inadequate in producing better control accuracy of nonlinear MIMO systems. Therefore, this study proposed the adaptive safe experimentation dynamics (ASED) algorithm to improve the SED algorithm performance accuracy by minimizing its objective function in terms of mean, best, worst, and standard deviation analysis. In order to increase the control accuracy of the existing NEPID controller, this study also established the sigmoid-based secretion rate neuroendocrine- PID (SbSR-NEPID) controller structure by varying the hormone secretion rate according to the change of error. Finally, this study also focused on developing a multiple node hormone regulation neuroendocrine-PID (MnHR–NEPID) controller structure to improve the control accuracy of existing NEPID by prioritizing the control regulation of each node from their level of error. The performance of PID and NEPID controllers was compared with those of SbSR-NEPID and MnHR-NEPID performances based on error and input tracking. The results show that the ASED- and SED-based methods produced stable convergence. The ASED-based method provided better tracking performance than the SED method by obtaining the objective function’s lower values. Besides, from the simulation work, the SbSR-NEPID and MnHR-NEPID designs provided better control accuracy in terms of lower objective function, total norm of error, and total norm of input compared to those of the PID and NEPID controllers. Moreover, the SbSR-NEPID controller achieved control accuracy improvement of 4.95% and 5.89% for the container gantry crane and TRMS systems, respectively. Besides, the MnHR-NEPID controller achieved control accuracy improvement of 5.7% and 5.1% for the container gantry crane and TRMS systems, respectively. The ASED-based method significantly improved the SED method’s accuracy by using adaptive terms based on changing the objective function in the updated procedure. Besides, the SbSR-NEPID was effective in reducing the error in a transient state, and MnHR-NEPID provided effective interaction between nodes available in MIMO systems which contributed to accuracy improvement

Safe Experimentation Dynamics Algorithm for Identification of Cupping Suction Based on the Nonlinear Hammerstein Model

The use of cupping therapy for various health benefits has increased in popularity recently. Potential advantages of cupping therapy include pain reduction, increased circulation, relaxation, and skin health. The increased blood flow makes it easier to supply nutrients and oxygen to the tissues, promoting healing. Nevertheless, the effectiveness of this technique greatly depends on the negative pressure's ability to create the desired suction effect on the skin. This research paper suggests a method to detect the cupping suction model by employing the Hammerstein model and utilizing the Safe Experimentation Dynamics (SED) algorithm. The problem is that the cupping suction system experiences pressure leaks and is difficult to control. Although, stabilizing the suction pressure and developing an effective controller requires an accurate model. The research contribution lies in utilizing the SED algorithm to tune the parameters of the Hammerstein model specifically for the cupping suction system and figure out the real system with a continuous-time transfer function. The experimental data collected for cupping therapy exhibited nonlinearity attributed to the complex dynamics of the system, presenting challenges in developing a Hammerstein model. This work used a nonlinear model to study the cupping suction system. Input and output data were collected from the differential pressure sensor for 20 minutes, sampling every 0.1 seconds. The single-agent method SED has limited exploration capabilities for finding optimum value but excels in exploitation. To address this limitation, incorporating initial values leads to improved performance and a better match with the real experimental observations. Experimentation was conducted to find the best model parameters for the desired suction pressure. The therapy can be administered with greater precision and efficacy by accurately identifying the suction pressure. Overall, this research represents a promising development in cupping therapy. In particular, it has been demonstrated that the proposed nonlinear Hammerstein models improve accuracy by 84.34% through the tuning SED algorithm

Non-Intrusive Electrodynamic Characteristic Measurement for Circular Shape Electrode

Abstract—The electrostatic sensor was used in process industry because of low cost and robust designed.Three types of electrode available in particular application such as pin shape, quarter ring shape and ring shape. The paper was focused on the investigation of the pin shape structure and the characteristic of the circular shape by using different size of structure. Non-instrusive method with circular electrode will be designed and applied to the shape.The sensitivity and spatial filtering effect of sensor will be investigated by using different size of electrodes.Then, the model will be proposed and compared with experimental result

H∞ Controller with Graphical LMI Region Profile for Gantry Crane System

This paper presents investigations into the development of H∞ controller with pole clustering based on LMI techniques to control the payload positioning of INTECO 3D crane system with very minimal swing. The linear model of INTECO 3D crane system is obtained using the system identification process. Using LMI approach, the regional pole placement known as LMI region combined with design objective in H∞ controller guarantee a fast input tracking capability, precise payload positioning and very minimal sway motion. A graphical profile of the transient response of crane system with respect to pole placement is very useful in giving more flexibility to the researcher in choosing a specific LMI region. The results of the response with the controllers are presented in time domains. The performances of control schemes are examined in terms of level of input tracking capability, sway angle reduction and time response specification. Finally, the control techniques is discussed and presented

Safe experimentation dynamics algorithm for identification of cupping suction based on the nonlinear Hammerstein model

The use of cupping therapy for various health benefits has increased in popularity recently. Potential advantages of cupping therapy include pain reduction, increased circulation, relaxation, and skin health. The increased blood flow makes it easier to supply nutrients and oxygen to the tissues, promoting healing. Nevertheless, the effectiveness of this technique greatly depends on the negative pressure's ability to create the desired suction effect on the skin. This research paper suggests a method to detect the cupping suction model by employing the Hammerstein model and utilizing the Safe Experimentation Dynamics (SED) algorithm. The problem is that the cupping suction system experiences pressure leaks and is difficult to control. Although, stabilizing the suction pressure and developing an effective controller requires an accurate model. The research contribution lies in utilizing the SED algorithm to tune the parameters of the Hammerstein model specifically for the cupping suction system and figure out the real system with a continuous-time transfer function. The experimental data collected for cupping therapy exhibited nonlinearity attributed to the complex dynamics of the system, presenting challenges in developing a Hammerstein model. This work used a nonlinear model to study the cupping suction system. Input and output data were collected from the differential pressure sensor for 20 minutes, sampling every 0.1 seconds. The single-agent method SED has limited exploration capabilities for finding optimum value but excels in exploitation. To address this limitation, incorporating initial values leads to improved performance and a better match with the real experimental observations. Experimentation was conducted to find the best model parameters for the desired suction pressure. The therapy can be administered with greater precision and efficacy by accurately identifying the suction pressure. Overall, this research represents a promising development in cupping therapy. In particular, it has been demonstrated that the proposed nonlinear Hammerstein models improve accuracy by 84.34% through the tuning SED algorithm

A data-driven neuroendocrine-PID controller for underactuated systems based on safe experimentation dynamics

This paper presents a data-driven neuroendocrine-PID controller for underactuated systems. Safe Experimentation Dynamics (SED) is employed to find the optimum neuroendocrine-PID parameters such that the control tracking performance and input energy are minimized. The advantage of the proposed approach is that it can generate fast neuroendocrine-PID parameter tuning by measuring the input and output data of the system without using the plant mathematical model. Moreover, the combination of neuroendocrine structure with PID has a great potential in improving the control performance as compared to the PID controller. An underactuated container crane model is considered to validate the proposed data-driven design. In addition, the performance of the proposed method is investigated in terms of the trolley position, hoist rope length and sway angle trajectory tracking. The simulation results show that the data-driven neuroendocrine-PID approach provides better control performance as compared to the PID controller

Using adaptive safe experimentation dynamics algorithm for maximizing wind farm power

This research presents a model-free strategy for increasing wind farm power generation based on the Adaptive Safe Experimentation Dynamics Algorithm (ASEDA). The ASEDA method is an improved version of the Safe Experimentation Dynamics (SED) algorithm that modifies the current tuning variable to respond to the changes in the objective function. The convergence accuracy is predicted to be enhanced further by adding the adaptive element to the modified SED equation. The ASEDA-based technique is used to determine the ideal control parameter for each turbine to maximize a wind farm's total power generation. A single single-row wind farm prototype with turbulence coupling among turbines is employed to validate the proposed approach. Simulation findings show that the ASEDA-based approach provides more total power generation than the original SED technique

Simple Pole Placement Controller for Elastic Joint Manipulator

This paper presents investigations into the development of simple pole placement controller for tip angular position tracking and deflection reduction of an elastic joint manipulator system. A Quanser elastic joint manipulator is considered and the dynamic model of the system is derived using the Euler-Lagrange formulation. The pole placement controller is designed based on integral state feedback structure and the feedback gain is computed based on the desired time response specifications of tip angular position. The proposed control scheme is also compared with a hybrid Linear Quadratic Regulator (LQR) with input shaper control scheme. The performances of the control schemes are assessed in terms of tip angular tracking capability, level of deflection angle reduction and time response specifications. Finally, a comparative assessment of the control techniques is presented and discussed

Data-driven neuroendocrine-PID controller design for twin rotor MIMO system

This paper presents the design of a data-driven neuroendocrine-PID controller based on adaptive safe experimentation dynamics (ASED) method for a twin-rotor MIMO system (TRMS). Neuroendocrine-PID is deemed a compatible controller, often due to its biological-inspired mechanism from a human's endocrine system that promotes control effectiveness and accuracy. In assessing the robustness of the proposed controller, its parameters were optimized through the ASED method, by tracking both error and input control performances. In particular, the ASED method is a game-theoretic method that randomly perturbs several elements of its controller parameters to search for the optimal controller parameters. Comparison was further made alongside performance of a standard PID controller. Following the simulation conducted, findings with regards to total norm error and total norm input have hereby suggested neuroendocrine-PID as a better controller, following a 13.2% improvement in control accuracy to that of a standard PID controller for TRMS system