Improved Third Order PID Sliding Mode Controller for Electrohydraulic Actuator Tracking Control

An electrohydraulic actuator (EHA) system is a combination of hydraulic systems and electrical systems which can produce a rapid response, high power-to-weight ratio, and large stiffness. Nevertheless, the EHA system has nonlinear behaviors and modeling uncertainties such as frictions, internal and external leakages, and parametric uncertainties, which lead to significant challenges in controller design for trajectory tracking. Therefore, this paper presents the design of an intelligent adaptive sliding mode proportional integral and derivative (SMCPID) controller, which is the main contribution toward the development of effective control on a third-order model of a double-acting EHA system for trajectory tracking, which significantly reduces chattering under noise disturbance. The sliding mode controller (SMC) is created by utilizing the exponential rule and the Lyapunov theorem to ensure closed-loop stability. The chattering in the SMC controller has been significantly decreased by substituting the modified sigmoid function for the signum function. Particle swarm optimization (PSO) was used to lower the total of absolute errors to adjust the controller. In order to demonstrate the efficacy of the SMCPID controller, the results for trajectory tracking and noise disturbance rejection were compared to those obtained using the proportional integral and derivative (PID), the proportional and derivative (PD), and the sliding mode proportional and derivative (SMCPD) controllers, respectively. In conclusion, the results of the extensive research given have indicated that the SMCPID controller outperforms the PD, PID, and SMCPD controllers in terms of overall performance.

Third-order robust fuzzy sliding mode tracking control of a double-acting electrohydraulic actuator

In the industrial sector, an electrohydraulic actuator (EHA) system is a common technology. This system is often used in applications that demand high force, such as the steel, automotive, and aerospace industries. Furthermore, since most mechanical actuators' performance changes with time, it is considerably more difficult to assure its robustness over time. Therefore, this paper proposed a robust fuzzy sliding mode proportional derivative (FSMCPD) controller. The sliding mode controller (SMC) is accomplished by utilizing the exponential law and the Lyapunov theorem to ensure closed loop stability. By replacing the fuzzy logic control (FLC) function over the signum function, the chattering in the SMC controller has been considerably reduced. By using the sum of absolute errors as the objective function, particle swarm optimization (PSO) was used to optimize the controller parameter gain. The experiment results for trajectory tracking and the robustness test were compared with the sliding mode proportional derivative (SMCPD) controller to demonstrate the performance of the FSMCPD controller. According to the findings of the thorough study, the FSMCPD controller outperforms the SMCPD controller in terms of mean square error (MSE) and robustness index (RI)

Performance Analysis of Position Tracking Control With PID Controller Using An Improved Optimization Technique

An Electro-Hydraulic Actuator (EHA) system is usually utilized in production industry such as automotive industry which requires precision, high force and long operating hours. When dealing with the production of engineering parts that require precision, high force and long operating hours, a controller is usually required. It is observed from the literature, an appropriate tuning technique is essential in order to obtain optimal controller’s performance. Therefore, a computational tuning technique, namely Priority-based Fitness Particle Swarm Optimization (PFPSO) is proposed to obtain the parameters of the Proportional-Integral-Derivative (PID) controller in this paper. The performance of the EHA system will be evaluated and compared based on the priority characters of the PFPSO tuning technique, which included settling time and overshoot percentage that affect the output results of the EHA system. As a result, it is observed that the priority based on settling time produced a better result, which enhances the steady-state performance of the EHA system that fulfills the requirement of the precision contro

Modeling and fault tolerant control of an electro-hydraulic actuator

In the modern industry, electro-hydraulic actuators (EHAs) have been applied to various applications for precise position pressure/ force control tasks. However, operating EHAs under sensor faults is one of the critical challenges for the control engineers. For its enormous nonlinear characteristics, sensor fault could lead the catastrophic failure to the overall system or even put human life in danger. Thus in this paper, a study on mathematical modeling and fault tolerant control (FTC) of a typical EHA for tracking control under sensor-fault conditions has been carried out. In the proposed FTC system, the extended Kalman-Bucy unknown input observer (EKBUIO) -based robust sensor fault detection and identification (FDI) module estimates the system states and the time domain fault information. Once a fault is detected, the controller feedback is switched from the faulty sensor to the estimated output from the EKBUIO owing to mask the sensor fault swiftly and retains the system stability. Additionally, considering the tracking accuracy of the EHA system, an efficient brain emotional learning based intelligent controller (BELBIC) is suggested as the main control unit. Effectiveness of the proposed FTC architecture has been investigated by experimenting on a test bed using an EHA in sensor failure conditions

Neurofuzzy controller based full vehicle nonlinear active suspension systems

To design a robust controller for active suspension systems is very important for guaranteeing the riding comfort for passengers and road handling quality for a vehicle. In this thesis, the mathematical model of full vehicle nonlinear active suspension systems with hydraulic actuators is derived to take into account all the motions of the vehicle and the nonlinearity behaviours of the active suspension system and hydraulic actuators. Four robust control types are designed and the comparisons among the robustness of those controllers against different disturbance types are investigated to select the best controller among them. The MATLAB SIMULINK toolboxes are used to simulate the proposed controllers with the controlled model and to display the responses of the controlled model under different types of disturbance. The results show that the neurofuzzy controller is more effective and robust than the other controller types. The implementation of the neurofuzzy controller using FPGA boards has been investigated in this work. The Xilinx ISE program is employed to synthesis the VHDL codes that describe the operation of the neurofuzzy controller and to generate the configuration file used to program the FPGA. The ModelSim program is used to simulate the operation of the VHDL codes and to obtain the expected output data of the FPGA boards. To confirm that FPGA the board used as the neurofuzzy controller system operated as expected, a MATLAB script file is used to compare the set of data obtained from the ModelSim program and the set of data obtained from the MATLAB SIMULINK model. The results show that the FPGA board is effective to be used as a neurofuzzy controller for full vehicle nonlinear active suspension systems. The active suspension system has a great performance for vibration isolation. However the main drawback of the active suspension is that it is high energy consumptive. Therefore, to use this suspension system in the proposed model, this drawback should be solved. Electromagnetic actuators are used to convert the vibration energy that arises from the rough road to useful electrical energy to reduce the energy consumption by the active suspension systems. The results show that the electromagnetic devices act as a power generator, i.e. the vibration energy excited by the rough road surface has been converted to a useful electrical energy supply for the actuators. Furthermore, when the nonlinear damper models are replaced by the electromagnetic actuators, riding comfort and the road handling quality are improved. As a result, two targets have been achieved by using hydraulic actuators with electromagnetic suspension systems: increasing fuel economy and improving the vehicle performance

Comparison Of Fractional Order PID Controller And Sliding Mode Controller With Computational Tuning Algorithm

The industry processes involving punching, lifting, and digging usually require high precision, high force and long operating hours that increase the prestige in the usage of the electrohydraulic actuator (EHA) system. These processes with the companion of the EHA system usually possess high dynamic complexities that are hard to be controlled and require well-designed and powerful control system. Therefore, this paper will involve the examination of the designed controllers which is applied to the EHA system. Firstly, the conventional proportional-integral-derivative (PID) controller which is the famous controller in the industry is designed. Then, the improved PID controller, which is known as the fractional order PID (FO-PID) controller is designed. After that, the design of the gradually famous robust controller in the education field, which is the sliding mode controller (SMC) is performed. Since the controller’s parameters are essentially influencing the performance of the controller, the meta-heuristic optimization method, which is the particle swarm optimization (PSO) tuning method is applied. The variation in the system’s parameter is applied to evaluate the performance of the designed controllers. Referring to the outcome analysis, the increment of 59.3% is obtained in the comparison between PID and FOPID, while the increment of 67.13% is obtained in the comparison of the PID with the SMC controller. As a conclusion, all of the controllers perform differently associated with their own advantages and disadvantag

Review On Controller Design In Pneumatic Actuator Drive System

A pneumatic actuator is a device that converts compressed air into mechanical energy to perform varieties of work. It exhibits high nonlinearities due to high friction forces, compressibility of air and dead band of the spool movement which is difficult to manage and requires an appropriate controller for better performance. The purpose of this study is to review the controller design of pneumatic actuator recommended by previous researchers from the past years. Initially, the basic views of the pneumatic will be presented in terms of introduction to the pneumatic actuator and its applications in industries. At the end of this review, discussions on the design of the controllers will be concluded and further research will be proposed along with the improvement of control strategies in the pneumatic actuator systems

Fuzzy sliding mode control for erection mechanism with unmodelled dynamics

Erection mechanism is a complicated system suffering from nonlinearities, uncertainties and disturbances. It is difficult to establish mathematical model and perform a high precision control using linear control methods. In this study, adaptive fuzzy sliding mode control algorithm was designed to control erection mechanism. The proposed method combines the advantages of fuzzy logic and sliding mode control. The structure of the system is partially unknown and does not require the bounds of uncertainty to be known. Fuzzy logic is used to approximate the unknown parts of the system. The chattering phenomenon of sliding mode control is eliminated without deteriorating the system robustness. Experimental results of the position control under various reference trajectories are obtained. The proposed method can achieve favourable tracking performance for erection mechanism in the presence of unmodelled dynamics and disturbances