A novel technique for load frequency control of multi-area power systems

In this paper, an adaptive type-2 fuzzy controller is proposed to control the load frequency of a two-area power system based on descending gradient training and error back-propagation. The dynamics of the system are completely uncertain. The multilayer perceptron (MLP) artificial neural network structure is used to extract Jacobian and estimate the system model, and then, the estimated model is applied to the controller, online. A proportional–derivative (PD) controller is added to the type-2 fuzzy controller, which increases the stability and robustness of the system against disturbances. The adaptation, being real-time and independency of the system parameters are new features of the proposed controller. Carrying out simulations on New England 39-bus power system, the performance of the proposed controller is compared with the conventional PI, PID and internal model control based on PID (IMC-PID) controllers. Simulation results indicate that our proposed controller method outperforms the conventional controllers in terms of transient response and stability

The predictive functional control and the management of constraints in GUANAY II autonomous underwater vehicle actuators

Autonomous underwater vehicle control has been a topic of research in the last decades. The challenges addressed vary depending on each research group's interests. In this paper, we focus on the predictive functional control (PFC), which is a control strategy that is easy to understand, install, tune, and optimize. PFC is being developed and applied in industrial applications, such as distillation, reactors, and furnaces. This paper presents the rst application of the PFC in autonomous underwater vehicles, as well as the simulation results of PFC, fuzzy, and gain scheduling controllers. Through simulations and navigation tests at sea, which successfully validate the performance of PFC strategy in motion control of autonomous underwater vehicles, PFC performance is compared with other control techniques such as fuzzy and gain scheduling control. The experimental tests presented here offer effective results concerning control objectives in high and intermediate levels of control. In high-level point, stabilization and path following scenarios are proven. In the intermediate levels, the results show that position and speed behaviors are improved using the PFC controller, which offers the smoothest behavior. The simulation depicting predictive functional control was the most effective regarding constraints management and control rate change in the Guanay II underwater vehicle actuator. The industry has not embraced the development of control theories for industrial systems because of the high investment in experts required to implement each technique successfully. However, this paper on the functional predictive control strategy evidences its easy implementation in several applications, making it a viable option for the industry given the short time needed to learn, implement, and operate, decreasing impact on the business and increasing immediacy.Peer ReviewedPostprint (author's final draft

Wiener modelling and model predictive control for wastewater applications

The research presented in this paper aims to demonstrate the application of predictive control to an integrated wastewater system with the use of the wiener modeling approach. This allows the controlled process, dissolved oxygen, to be considered to be composed of two parts: the linear dynamics, and a static nonlinearity, thus allowing control other than common approaches such as gain-scheduling, or switching, for series of linear controllers. The paper discusses various approaches to the modelling required for control purposes, and the use of wiener modelling for the specific application of integrated waste water control. This paper demonstrates this application and compares with that of another nonlinear approach, fuzzy gain-scheduled control

Hybrid Takagi‐Sugeno Fuzzy FED PID Control of Nonlinear Systems

The new method of proportional‐integral‐derivative (PID) controller is proposed in this paper for a hybrid fuzzy PID controller for nonlinear system. The important feature of the proposed approach is that it combines the fuzzy gain scheduling method and a fuzzy fed PID controller to solve the nonlinear control problem. The resultant fuzzy rule base of the proposed controller contains one part. This single part of the rules uses the Takagi–Sugeno method for solving the nonlinear problem. The simulation results of a nonlinear system show that the performance of a fed PID Hybrid Takagi‐Sugeno fuzzy controller is better than that of the conventional fuzzy PID controller or Hybrid Mamdani fuzzy FED PID controller

A New Approach of the Online Tuning Gain Scheduling Nonlinear PID Controller Using Neural Network

This chapter presents the design, development and implementation of a novel proposed online-tuning Gain Scheduling Dynamic Neural PID (DNN-PID) Controller using neural network suitable for real-time manipulator control applications. The unique feature of the novel DNN-PID controller is that it has highly simple and dynamic self-organizing structure, fast online-tuning speed, good generalization and flexibility in online-updating. The proposed adaptive algorithm focuses on fast and efficiently optimizing Gain Scheduling and PID weighting parameters of Neural MLPNN model used in DNN-PID controller. This approach is employed to implement the DNN-PID controller with a view of controlling the joint angle position of the highly nonlinear pneumatic artificial muscle (PAM) manipulator in real-time through Real-Time Windows Target run in MATLAB SIMULINK® environment. The performance of this novel proposed controller was found to be outperforming in comparison with conventional PID controller. These results can be applied to control other highly nonlinear SISO and MIMO systems. Keywords: highly nonlinear PAM manipulator, proposed online tuning Gain Scheduling Dynamic Nonlinear PID controller (DNN-PID), real-time joint angle position control, fast online tuning back propagation (BP) algorithm, pneumatic artificial muscle (PAM) actuator

A PROPOSED CONTROL SOLUTION FOR THE CAL POLY WIND ENERGY CAPTURE SYSTEM

The focus of this thesis is to research, analyze, and design a reliable and economical control system for the Cal Poly Wind Energy Capture System (WECS). A dynamic permanent magnet generator model is adopted from [1] and [2] and combined with an existing wind turbine model to create a non-linear time varying model in MATLAB. The model is then used to analyze potentially harmful electrical disturbances, and to define safe operating limits for the WECS. An optimal operating point controller utilizing a PID speed loop is designed with combined optimization criteria and the final controller design is justified by comparing performance measures of energy efficiency and mitigation of mechanical loads. The report also discusses implications for a WECS when blade characteristics are mismatched with the generator. Finally, possible ways to improve the performance of the Cal Poly WECS are addressed

Speed and Torque Estimation of BLDC using DTC and Sliding Mode Observer

This paper presents speed and torque estimation for Brushless DC (BLDC) motors with non-sinusoidal back electromotive force using six switch inverter and DTC technique. The 180 conduction mode is the more popular method used for three-phase drives but here we use two-phase conduction mode. A simple approach is discussed n how to reduce ripples in the estimated torque at low frequency operation. A simple look-up table at a pre-defined sampling time is used to select the inverter voltage space vectors and the quasi-wave current is obtained. Estimation of electromagnetic torque for BLDC drives is the key issue and so sensor-less control method are used. The sliding mode observer estimates the back-EMF and generates torque, as under sliding mode observer error equation is reduced and it makes stability easier. Only the measurements of the stator currents is used in the estimation of back-EMF waveform. The electromagnetic torque and the rotor speed is estimated using values from Sliding Mode Observer. Fuzzy Gain Scheduling method is used to tune the parameters because this scheme uses human expertise on PID gain scheduling can be represented in fuzzy rules. Furthermore, better control performance can be expected in the proposed method than that of the PID controllers with fixed parameters and the gains of the sliding mode observer are tuned manually. The effectiveness of the proposed scheme is verified by using simulation results. Keywords: BLDC, DTC, Sliding Mode Observer(SMO), PID Controller, Fuzzy Gain Scheduling, Estimated Rotor speed, Estimated Torque, Estimated Back-EMF

Hybrid Optimized Fuzzy Pitch Controller of a Floating Wind Turbine with Fatigue Analysis

Floating offshore wind turbines (FOWTs) are systems with complex and highly nonlinear dynamics; they are subjected to heavy loads, making control with classical strategies a challenge. In addition, they experience vibrations due to wind and waves. Furthermore, the control of the blade angle itself may generate vibrations. To address this issue, in this work we propose the design of an intelligent control system based on fuzzy logic to maintain the rated power of an FOWT while reducing the vibrations. A gain scheduling incremental proportional–derivative fuzzy controller is tuned by genetic algorithms (GAs) and combined with a fuzzy-lookup table to generate the pitch reference. The control gains optimized by the GA are stored in a database to ensure a proper operation for different wind and wave conditions. The software Matlab/Simulink and the simulation tool FAST are used. The latter simulates the nonlinear dynamics of a real 5 MW barge-type FOWT with irregular waves. The hybrid control strategy has been evaluated against the reference baseline controller embedded in FAST in different environmental scenarios. The comparison is assessed in terms of output power and structure stability, with up to 23% and 33% vibration suppression rate for tower top displacement and platform pitch, respectively, with the new control scheme. Fatigue damage equivalent load (DEL) of the blades has been also estimated with satisfactory results.This work has been partially supported by the Spanish Ministry of Science and Innovation under the project MCI/AEI/FEDER number RTI2018-094902-B-C21 and PDI2021-123543OB-C21