Fuzzy Controller Implemented for Movement of a Tendon-Driven 3D Robotic Lumbar Spine Mechanism.

Notable efforts have been devoted to the development of biomechanical models of the spine, so the development of a motion system to control the spine becomes expressively relevant. This paper presents a fuzzy controller to manipulate the movement of a 3D robotic mechanism of the lumbar spine, which is driven by tendons. The controller was implemented in Matlab/Simulink R2023a software, MathWorks (Brazil), considering mathematical modeling based on the Lagrangian methodology for simulating the behavior of the lumbar spine dynamic movement. The fuzzy controller was implemented to perform movements of two joints of the 3D robotic mechanism, which consists of five vertebrae grouped into two sets, G1 and G2. The mechanism's movements are carried out by four servomotors which are driven by readings from two sensors. For control, the linguistic variables of position, velocity and acceleration were used as controller inputs and the torque variables were used for the controller output. The experimental tests were carried out by running the fuzzy controller directly on the 3D physical model (external to the simulation environment) to represent flexion and extension movements analogous to human movements.

Fuzzy Control Application to an Irrigation System of Hydroponic Crops under Greenhouse: Case Cultivation of Strawberries (Fragaria Vesca).

Hydroponics refers to a modern set of agricultural techniques that do not require the use of natural soil for plant germination and development. These types of crops use artificial irrigation systems that, together with fuzzy control methods, allow plants to be provided with the exact amount of nutrients for optimal growth. The diffuse control begins with the sensorization of the agricultural variables that intervene in the hydroponic ecosystem, such as the environmental temperature, electrical conductivity of the nutrient solution and the temperature, humidity, and pH of the substrate. Based on this knowledge, these variables can be controlled to be within the ranges required for optimal plant growth, reducing the risk of a negative impact on the crop. This research takes, as a case study, the application of fuzzy control methods to hydroponic strawberry crops (Fragaria vesca). It is shown that, under this scheme, a greater foliage of the plants and a larger size of the fruits are obtained in comparison with natural cultivation systems in which irrigation and fertilization are carried out by default, without considering the alterations in the aforementioned variables. It is concluded that the combination of modern agricultural techniques such as hydroponics and diffuse control allow us to improve the quality of the crops and the optimization of the required resources.

Fuzzy Synchronization of Chaotic Systems with Hidden Attractors.

Chaotic systems are hard to synchronize, and no general solution exists. The presence of hidden attractors makes finding a solution particularly elusive. Successful synchronization critically depends on the control strategy, which must be carefully chosen considering system features such as the presence of hidden attractors. We studied the feasibility of fuzzy control for synchronizing chaotic systems with hidden attractors and employed a special numerical integration method that takes advantage of the oscillatory characteristic of chaotic systems. We hypothesized that fuzzy synchronization and the chosen numerical integration method can successfully deal with this case of synchronization. We tested two synchronization schemes: complete synchronization, which leverages linearization, and projective synchronization, capitalizing on parallel distributed compensation (PDC). We applied the proposal to a set of known chaotic systems of integer order with hidden attractors. Our results indicated that fuzzy control strategies combined with the special numerical integration method are effective tools to synchronize chaotic systems with hidden attractors. In addition, for projective synchronization, we propose a new strategy to optimize error convergence. Furthermore, we tested and compared different Takagi-Sugeno (T-S) fuzzy models obtained by tensor product (TP) model transformation. We found an effect of the fuzzy model of the chaotic system on the synchronization performance.

Fuzzy Control of Pressure in a Water Supply Network Based on Neural Network System Modeling and IoT Measurements.

As hydroenergetic losses are inherent to water supply systems, they are a frequent issue which water utilities deal with every day. The control of network pressure is essential to reducing these losses, providing a quality supply to consumers, saving electricity and preserving piping from excess pressure. However, to obtain these benefits, it is necessary to overcome some difficulties such as sensing the pressure of geographically distant consumer units and developing a control logic that is capable of making use of the data from these sensors and, at the same time, a good solution in terms of cost benefit. Therefore, this work has the purpose of developing a pressure monitoring and control system for water supply networks, using the ESP8266 microcontroller to collect data from pressure sensors for the integrated ScadaLTS supervisory system via the REST API. The modeling of the plant was developed using artificial neural networks together with fuzzy pressure control, both designed using the Python language. The proposed method was tested by considering a pumping station and two reference units located in the city of João Pessoa, Brazil, in which there was an excess of pressure in the supply network and low performance from the old controls, during the night period from 12:00 a.m. to 6:00 a.m. The field results estimated 2.9% energy saving in relation to the previous form of control and a guarantee that the pressure in the network was at a healthy level.

Design and Implementation of a Position, Speed and Orientation Fuzzy Controller Using a Motion Capture System to Operate a Wheelchair Prototype.

The design and implementation of an electronic system that involves head movements to operate a prototype that can simulate future movements of a wheelchair was developed here. The controller design collects head-movements data through a MEMS sensor-based motion capture system. The research was divided into four stages: First, the instrumentation of the system using hardware and software; second, the mathematical modeling using the theory of dynamic systems; third, the automatic control of position, speed, and orientation with constant and variable speed; finally, system verification using both an electronic controller test protocol and user experience. The system involved a graphical interface for the user to interact with it by executing all the controllers in real time. Through the System Usability Scale (SUS), a score of 78 out of 100 points was obtained from the qualification of 10 users who validated the system, giving a connotation of "very good". Users accepted the system with the recommendation to improve safety by using laser sensors instead of ultrasonic range modules to enhance obstacle detection.

A PID-Type Fuzzy Logic Controller-Based Approach for Motion Control Applications.

Motion control is widely used in industrial applications since machinery, robots, conveyor bands use smooth movements in order to reach a desired position decreasing the steady error and energy consumption. In this paper, a new Proportional-Integral-Derivative (PID) -type fuzzy logic controller (FLC) tuning strategy that is based on direct fuzzy relations is proposed in order to compute the PID constants. The motion control algorithm is composed by PID-type FLC and S-curve velocity profile, which is developed in C/C++ programming language; therefore, a license is not required to reproduce the code among embedded systems. The self-tuning controller is carried out online, it depends on error and change in error to adapt according to the system variations. The experimental results were obtained in a linear platform integrated by a direct current (DC) motor connected to an encoder to measure the position. The shaft of the motor is connected to an endless screw; a cart is placed on the screw to control its position. The rise time, overshoot, and settling time values measured in the experimentation are 0.124 s, 8.985% and 0.248 s, respectively. These results presented in part 6 demonstrate the performance of the controller, since the rise time and settling time are improved according to the state of the art. Besides, these parameters are compared with different control architectures reported in the literature. This comparison is made after applying a step input signal to the DC motor.

In vitro evaluation of multi-objective physiological control of the centrifugal blood pump.

Left ventricular assist devices (LVADs) have been used as a bridge to transplantation or as destination therapy to treat patients with heart failure (HF). The inability of control strategy to respond automatically to changes in hemodynamic conditions can impact the patients' quality of life. The developed control system/algorithm consists of a control system that harmoniously adjusts pump speed without additional sensors, considering the patient's clinical condition and his physical activity. The control system consists of three layers: (a) Actuator speed control; (b) LVAD flow control (FwC); and (c) Fuzzy control system (FzC), with the input variables: heart rate (HR), mean arterial pressure (MAP), minimum pump flow, level of physical activity (data from patient), and clinical condition (data from physician, INTERMACS profile). FzC output is the set point for the second LVAD control schemer (FwC) which in turn adjusts the speed. Pump flow, MAP, and HR are estimated from actuator drive parameters (speed and power). Evaluation of control was performed using a centrifugal blood pump in a hybrid cardiovascular simulator, where the left heart function is the mechanical model and right heart function is the computational model. The control system was able to maintain MAP and cardiac output in the physiological level, even under variation of EF. Apart from this, also the rotational pump speed is adjusted following the simulated clinical condition. No backflow from the aorta in the ventricle occurred through LVAD during tests. The control algorithm results were considered satisfactory for simulations, but it still should be confirmed during in vivo tests.

Aplicacao de tecnicas Fuzzy no controle de pressao em sistemas de abastecimento de agua / Application of Fuzzy techniques to control pressure in water supply systems

O trabalho apresenta o desenvolvimento de um sistema Fuzzy para o controle de pressão de redes de distribuição de água, por meio da utilização de conversores de frequência acoplados aos conjuntos motor-bomba. Todo o estudo foi desenvolvido em uma bancada experimental instrumentalizada, simulando um sistema de abastecimento real. A utilização de conjuntos motor-bomba em paralelo gerou ao sistema um grande número de possibilidades de combinação das variações de velocidade dos conjuntos motor-bomba, com velocidades de rotação diferentes. O controlador Fuzzy identifica a melhor opção, referente ao consumo energético do sistema, e toma a decisão alusiva ao estado dos motores (ligado, desligado ou com rotação parcial). Todo esse processo é realizado na condição de atender a demanda de vazão do sistema, além de manter a pressão constante com o menor consumo energético possível. .

The paper presents the development of a Fuzzy system for the pressure control of distribution of water through the use of frequency converters coupled to the motor-pump assemblies. The entire study was conducted in an instrumentalized bench trial simulating a real supply system. The use of pump-motor sets in parallel with the system generated a great number of combination possibilities of variations in speed of the motor-pump assemblies, with different speeds of rotation. The Fuzzy controller identifies the best option for the energy consumption of the system and makes the decision alluding to the state of the engines (on, off or partial rotation). This entire process is performed under the condition of meeting the demand flow system, and maintain constant pressure with the lowest possible energy consumption.

A fuzzy-split range control system applied to a fermentation process.

In this study it was proposed the application of a fuzzy-PI controller in tandem with a split range control strategy to regulate the temperature inside a fermentation vat. Simulations were carried out using different configurations of fuzzy controllers and split range combinations for regulatory control. The performance of these control systems were compared using conventional integral of error criteria, the demand of utilities and the control effort. The proposed control system proved able to adequately regulate the temperature in all the tests. Besides, considering a similar ITAE index and using the energetically most efficient split range configuration, fuzzy-PI controller provided a reduction of approximately 84.5% in the control effort and of 6.75% in total demand of utilities by comparison to a conventional PI controller.

Sistema de controle de velocidade sincronizada entre dois veículos agrícolas / Synchronized speed control system between two agricultural vehicles

Este trabalho apresenta uma proposta para o controle automático de velocidade entre dois veículos que necessitam trafegar em paralelo durante operações agrícolas. É descrito o desenvolvimento e os testes de campo de um sistema de controle de velocidade para um trator escravo baseado na velocidade de um trator mestre, utilizando um controlador desenvolvido em lógica fuzzy. Para esses testes, os tratores foram instrumentados com GPS, encoder, computador e transmissor de radiofrequência, sendo instalado ainda no trator escravo um motor de passo para o controle da velocidade de deslocamento. Para avaliar o sistema, realizaram-se dois testes: no primeiro, a resposta do trator escravo à variação de velocidade foi avaliada a partir de simulações de variação na velocidade de entrada; no segundo, foram utilizados dois tratores variando a velocidade do trator mestre e observando a resposta do trator escravo. No primeiro teste, o trator escravo acompanhou a simulação da variação da velocidade com um erro quadrático médio (EQM) não significativo e erro médio percentual (EMP) máximo de 1,3 por cento. No segundo teste, o trator escravo acompanhou a variação de velocidade do trator mestre com o (EMP) de deslocamento variando em módulo de 0,2 por cento a 2,9 por cento.

This paper presents a proposal for automatic speed control of vehicles that requires working in synchronism with each other during agricultural operations. It describes the development and field tests of a control system for a slave tractor based on the master tractor speed, using a fuzzy controller. For the tests the master tractor was instrumented with GPS, encoders, computer and radio transmitter. The slave tractor was instrumented in the same way, and included also a stepper motor to act on the tractor throttle. To evaluate the system two tests were conducted. In the first, the master tractor speed was simulated using only the slave tractor. In the second test, two tractors were used varying the master tractor speed and registering the slave tractor response. In the first test the slave tractor followed the speed variation simulated with a mean square error (MSE) non-significant and a maximum mean percentage error (MPE) of 1.3 percent. In the second test the slave tractor followed the master tractor speed variation with a displacement (MPE) ranging in magnitude from 0.2 percent to 2.9 percent.

Sistema de controle de velocidade sincronizada entre dois veículos agrícolas

This paper presents a proposal for automatic speed control of vehicles that requires working in synchronism with each other during agricultural operations. It describes the development and field tests of a control system for a slave tractor based on the master tractor speed, using a fuzzy controller. For the tests the master tractor was instrumented with GPS, encoders, computer and radio transmitter. The slave tractor was instrumented in the same way, and included also a stepper motor to act on the tractor throttle. To evaluate the system two tests were conducted. In the first, the master tractor speed was simulated using only the slave tractor. In the second test, two tractors were used varying the master tractor speed and registering the slave tractor response. In the first test the slave tractor followed the speed variation simulated with a mean square error (MSE) non-significant and a maximum mean percentage error (MPE) of 1.3%. In the second test the slave tractor followed the master tractor speed variation with a displacement (MPE) ranging in magnitude from 0.2% to 2.9%.

Este trabalho apresenta uma proposta para o controle automático de velocidade entre dois veículos que necessitam trafegar em paralelo durante operações agrícolas. É descrito o desenvolvimento e os testes de campo de um sistema de controle de velocidade para um trator escravo baseado na velocidade de um trator mestre, utilizando um controlador desenvolvido em lógica fuzzy. Para esses testes, os tratores foram instrumentados com GPS, encoder, computador e transmissor de radiofrequência, sendo instalado ainda no trator escravo um motor de passo para o controle da velocidade de deslocamento. Para avaliar o sistema, realizaram-se dois testes: no primeiro, a resposta do trator escravo à variação de velocidade foi avaliada a partir de simulações de variação na velocidade de entrada; no segundo, foram utilizados dois tratores variando a velocidade do trator mestre e observando a resposta do trator escravo. No primeiro teste, o trator escravo acompanhou a simulação da variação da velocidade com um erro quadrático médio (EQM) não significativo e erro médio percentual (EMP) máximo de 1,3%. No segundo teste, o trator escravo acompanhou a variação de velocidade do trator mestre com o (EMP) de deslocamento variando em módulo de 0,2% a 2,9%.

Sistema de controle de velocidade sincronizada entre dois veículos agrícolas

This paper presents a proposal for automatic speed control of vehicles that requires working in synchronism with each other during agricultural operations. It describes the development and field tests of a control system for a slave tractor based on the master tractor speed, using a fuzzy controller. For the tests the master tractor was instrumented with GPS, encoders, computer and radio transmitter. The slave tractor was instrumented in the same way, and included also a stepper motor to act on the tractor throttle. To evaluate the system two tests were conducted. In the first, the master tractor speed was simulated using only the slave tractor. In the second test, two tractors were used varying the master tractor speed and registering the slave tractor response. In the first test the slave tractor followed the speed variation simulated with a mean square error (MSE) non-significant and a maximum mean percentage error (MPE) of 1.3%. In the second test the slave tractor followed the master tractor speed variation with a displacement (MPE) ranging in magnitude from 0.2% to 2.9%.

Este trabalho apresenta uma proposta para o controle automático de velocidade entre dois veículos que necessitam trafegar em paralelo durante operações agrícolas. É descrito o desenvolvimento e os testes de campo de um sistema de controle de velocidade para um trator escravo baseado na velocidade de um trator mestre, utilizando um controlador desenvolvido em lógica fuzzy. Para esses testes, os tratores foram instrumentados com GPS, encoder, computador e transmissor de radiofrequência, sendo instalado ainda no trator escravo um motor de passo para o controle da velocidade de deslocamento. Para avaliar o sistema, realizaram-se dois testes: no primeiro, a resposta do trator escravo à variação de velocidade foi avaliada a partir de simulações de variação na velocidade de entrada; no segundo, foram utilizados dois tratores variando a velocidade do trator mestre e observando a resposta do trator escravo. No primeiro teste, o trator escravo acompanhou a simulação da variação da velocidade com um erro quadrático médio (EQM) não significativo e erro médio percentual (EMP) máximo de 1,3%. No segundo teste, o trator escravo acompanhou a variação de velocidade do trator mestre com o (EMP) de deslocamento variando em módulo de 0,2% a 2,9%.

Sistema de controle de velocidade sincronizada entre dois veículos agrícolas

This paper presents a proposal for automatic speed control of vehicles that requires working in synchronism with each other during agricultural operations. It describes the development and field tests of a control system for a slave tractor based on the master tractor speed, using a fuzzy controller. For the tests the master tractor was instrumented with GPS, encoders, computer and radio transmitter. The slave tractor was instrumented in the same way, and included also a stepper motor to act on the tractor throttle. To evaluate the system two tests were conducted. In the first, the master tractor speed was simulated using only the slave tractor. In the second test, two tractors were used varying the master tractor speed and registering the slave tractor response. In the first test the slave tractor followed the speed variation simulated with a mean square error (MSE) non-significant and a maximum mean percentage error (MPE) of 1.3%. In the second test the slave tractor followed the master tractor speed variation with a displacement (MPE) ranging in magnitude from 0.2% to 2.9%.

Este trabalho apresenta uma proposta para o controle automático de velocidade entre dois veículos que necessitam trafegar em paralelo durante operações agrícolas. É descrito o desenvolvimento e os testes de campo de um sistema de controle de velocidade para um trator escravo baseado na velocidade de um trator mestre, utilizando um controlador desenvolvido em lógica fuzzy. Para esses testes, os tratores foram instrumentados com GPS, encoder, computador e transmissor de radiofrequência, sendo instalado ainda no trator escravo um motor de passo para o controle da velocidade de deslocamento. Para avaliar o sistema, realizaram-se dois testes: no primeiro, a resposta do trator escravo à variação de velocidade foi avaliada a partir de simulações de variação na velocidade de entrada; no segundo, foram utilizados dois tratores variando a velocidade do trator mestre e observando a resposta do trator escravo. No primeiro teste, o trator escravo acompanhou a simulação da variação da velocidade com um erro quadrático médio (EQM) não significativo e erro médio percentual (EMP) máximo de 1,3%. No segundo teste, o trator escravo acompanhou a variação de velocidade do trator mestre com o (EMP) de deslocamento variando em módulo de 0,2% a 2,9%.