Comparison of cascade P-PI controller tuning methods for PMDC motor based on intelligence techniques

In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.

NITRATE REMOVAL IN WOODCHIP DENITRIFICATION BIOREACTOR – AN APPROACH COMBINING MATHEMATICAL MODELLING AND PI CONTROL

A mathematical model of nitrate removal in woodchip denitrification bioreactor based on field experiment measurements was developed in this study. The approach of solving inverse problem for nonlinear system of differential convection-reaction equations was applied to optimize the efficiency of nitrate removal depending on bioreactor’s length and flow rate. The approach was realized through the developed algorithm containing a nonlocal condition with an incorporated PI controller. This allowed to adjust flow rate for varying inflow nitrate concentrations by using PI controller. The proposed model can serve as a useful tool for bioreactor design. The main outcome of the model is a mathematical relationship intended for bioreactor length selection when nitrate concentration at the inlet and the flow rate are known. Custom software was developed to solve the system of differential equations aiming to ensure the required nitrate removal efficiency.

An Angle-Compensating, Complex-Coefficient PI Controller Used for Decoupling Control of a Permanent-Magnet Synchronous Motor

An asymmetric, cross-coupling effect, as well as digital control delays, in a permanent-magnet synchronous motor (PMSM) will deteriorate its current-control performance in the high-speed range, especially for electric motors used in electric vehicles (EVs) with features such as high-power density and a low carrier/modulation frequency ratio. In this paper, an angle-compensating, complex-coefficient, proportional-integrator (ACCC-PI) controller is proposed, which aims to provide an excellent decoupling performance even with considerable digital control delay. Firstly, the current open and closed loop complex-coefficient transfer functions were established in the synchronous rotation coordinate system. The proposed method, along with existing ones, were then evaluated and theoretically compared. On this basis, the parameter-tuning method of the ACCC-PI controller was presented. Finally, simulation and experimental results proved the correctness of the theoretical analysis and the proposed method.

Implicit multilinear modeling

The paper introduces a subclass of nonlinear differential-algebraic models of interest for applications. By restricting the nonlinearities to multilinear polynomials, it is possible to use modern tensor methods. This opens the door to new approximation and complexity reduction methods for large scale systems with relevant nonlinear behavior. The modeling procedures including composition, decomposition, normalization, and multilinearization steps are shown by an example of a local energy system with a nonlinear electrolyzer, a linear buck converter and a PI controller with saturation.

Automatic delivery-scam prevention using Raspberry-Pi

The word ‘automatic’ is unavoidable in this modern technical era. Automation facilitates not only technical advancement and time reduction to several processes, but also provides protection in various aspects. Delivery scam is a commonly occurring crime and it has to be reduced. Product delivery is a long process which involves various people to ensure correct delivery to the customer, providing chances for scam to occur. This paper discusses on an automatic delivery-scam prevention system with the help of Raspberry-Pi controller. This system provides safety to the ordered goods by limiting the authorisation of opening the packages to company and the customer only. It assures the safe and correct delivery of the ordered product.

Extended state observer-based control with an adjustable parameter for a large ground-based telescope

The high-precision requirements will always be constrained due to the complicated operating conditions of the ground-based telescope. Owing to various internal and external disturbances, it is necessary to study a control method, which should have a good ability on disturbance rejection and a good adaptability on system parameter variation. The traditional proportional-integral (PI) controller has the advantage of simple and easy adjustment, but it cannot deal with the disturbances well in different situations. This paper proposes a simplified active disturbance rejection control law, whose debugging is as simple as the PI controller, and with better disturbance rejection ability and parameter adaptability. It adopts a simplified second-order extended state observer (ESO) with an adjustable parameter to accommodate the significant variation of the inertia during the different design stages of the telescope. The gain parameter of the ESO can be adjusted online with a recursive least square estimating method once the system parameter has changed significantly. Thus, the ESO can estimate the total disturbances timely and the controller will compensate them accordingly. With the adjustable parameter of the ESO, the controller can always achieve better performance in different applications of the telescope. The simulation and experimental verification of the control law was conducted on a 1.2-meter ground based telescope. The results verify the necessity of adjusting the parameter of the ESO, and demonstrate better disturbance rejection ability in a large range of speed variations during the design stages of the telescope.

Optimal Fractional-Order PI Control Design for a Variable Speed PMSG-Based Wind Turbine

This paper focusses on the design of optimal control strategies for a variable-speed wind energy system based on Permanent Magnet Synchronous Generator (PMSG). The fractional order PI controller, denoted PIλ, is an extension of the classical PI controller, which provides greater flexibility, better performance and robustness, however the tuning of the controller parameters is challenging. In this work, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) provide approximate solutions to various problems and form a good optimization. In our system, they are used to have the PI regulator parameters and tune the parameters of the proposed controllers. The proposed controllers have been applied as maximum power point (MPPT) controllers for the wind turbine and to regulate the PMGS currents under variable weather conditions and. The results show that, among all these controllers, the fractional order PI controller optimized by the PSO leads to better performance in terms of the transient response characteristics such overshoot, rise time and settling time.