Optimal pneumatic actuator positioning and dynamic stability using prescribed performance control with particle swarm optimization: A simulation study

This paper introduces an optimal control strategy for pneumatic servo systems (PSS) positioning using Finite-time Prescribed Performance Control (FT-PPC) with Particle Swarm Optimization (PSO). Pneumatic servo systems are widely used in industrial automation, as well as medical and cybernetics systems that involve robotics applications. Precision in pneumatic control is crucial not only for the sake of efficiency but also safety. The primary goal of the proposed control strategy is to optimize the convergence rate and finite time of the prescribed performance function in error transformation of the FT-PPC, as well as the Proportional, Integral and Derivative (PID) controller as the inner-loop controller for this system. The study utilizes a dynamic model of a pneumatic proportional valve with a double-acting cylinder (PPVDC) as the targeted plant and performs simulations with a multi-step input trajectory. This offline tuning method is essential for such nonlinear systems to be safely optimized, avoiding major damage to the real-time fine-tuned works on the controller. The results demonstrate that the proposed control strategy surpasses the performance of FT-PPC with a PID controller alone, significantly improving the system's performance, including suppressing overshoot and oscillation in the responses. Further validation through the actual system of PPVDC using the fine-tuned values of FT-PPC and PID with PSO is a future task and more challenging to come, as hardware constraints may vary with different environments such as temperatures

Position Control of Pneumatic Actuator Using Self-Regulation Nonlinear PID

The enhancement of nonlinear PID (N-PID) controller for a pneumatic positioning system is proposed to improve the performance of this controller. This is executed by utilizing the characteristic of rate variation of the nonlinear gain that is readily available in N-PID controller. The proposed equation, namely, self-regulation nonlinear function (SNF), is used to reprocess the error signal with the purpose of generating the value of the rate variation, continuously. With the addition of this function, a new self-regulation nonlinear PID (SN-PID) controller is proposed. The proposed controller is then implemented to a variably loaded pneumatic actuator. Simulation and experimental tests are conducted with different inputs, namely, step, multistep, and random waveforms, to evaluate the performance of the proposed technique. The results obtained have been proven as a novel initiative at examining and identifying the characteristic based on a new proposal controller resulting from N-PID controller. The transient response is improved by a factor of 2.2 times greater than previous N-PID technique. Moreover, the performance of pneumatic positioning system is remarkably good under various loads

Metaheuristics algorithms to identify nonlinear Hammerstein model: A decade survey

Metaheuristics have been acknowledged as an effective solution for many difficult issues related to optimization. The metaheuristics, especially swarm’s intelligence and evolutionary computing algorithms, have gained popularity within a short time over the past two decades. Various metaheuristics algorithms are being introduced on an annual basis and applications that are more new are gradually being discovered. This paper presents a survey for the years 2011-2021 on multiple metaheuristics algorithms, particularly swarm and evolutionary algorithms, to identify a nonlinear block-oriented model called the Hammerstein model, mainly because such model has garnered much interest amidst researchers to identify nonlinear systems. Besides introducing a complete survey on the various population-based algorithms to identify the Hammerstein model, this paper also investigated some empirically verified actual process plants results. As such, this article serves as a guideline on the fundamentals of identifying nonlinear block-oriented models for new practitioners, apart from presenting a comprehensive summary of cutting-edge trends within the context of this topic area

Invited Review: Recent developments in vibration control of building and bridge structures

This paper presents a state-of-the-art review of recent articles published on active, passive, semi-active and hybrid vibration control systems for structures under dynamic loadings primarily since 2013. Active control systems include active mass dampers, active tuned mass dampers, distributed mass dampers, and active tendon control. Passive systems include tuned mass dampers (TMD), particle TMD, tuned liquid particle damper, tuned liquid column damper (TLCD), eddy-current TMD, tuned mass generator, tuned-inerter dampers, magnetic negative stiffness device, resetting passive stiffness damper, re-entering shape memory alloy damper, viscous wall dampers, viscoelastic dampers, and friction dampers. Semi-active systems include tuned liquid damper with floating roof, resettable variable stiffness TMD, variable friction dampers, semi-active TMD, magnetorheological dampers, leverage-type stiffness controllable mass damper, semi-active friction tendon. Hybrid systems include shape memory alloys-liquid column damper, shape memory alloy-based damper, and TMD-high damping rubber

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

Model Identification And Controller Design For An Electro-Pneumatic Actuator System With Dead Zone Compensation

Pneumatic actuator system is inexpensive, high power to weight ratio, cleanliness and ease of maintenance make it’s a choice compared to hydraulic actuator and electromagnetic actuator. Nonetheless, the steady state error of the system is high due to the dead zone of the valve. In this paper, an Auto-Regressive with External Input (ARX) model structure is chosen to represent the pneumatic actuator system. The recursive least square method is used to estimate the model parameters. The pole-assignment controller is then developed for position tracking. To cater the problem of high in steady state error, the dead zone compensation is added to the system. The dead zone controller was designed based on the inverse dead zone model and the dead zone compensation designed based on the desired error. The proposed method is then experimentally with varies load and compares with Nonlinear PID controller. The result shows that the proposed controller reduced the overshoot and steady state error of the pneumatic actuator system to no overshoot and 0.025mm respectively. Index terms: System identification, recursive least square, ARX, dead zone compensator, pneumatic actuato

Evolutionary swarm algorithm for modelling and control of horizontal flexible plate structures

Numerous advantages offered by the horizontal flexible structure have attracted increasing industrial applications in many engineering fields particularly in the airport baggage conveyor system, micro hand surgery and semiconductor manufacturing industry. Nevertheless, the horizontal flexible structure is often subjected to disturbance forces as vibration is easily induced in the system. The vibration reduces the performance of the system, thus leading to the structure failure when excessive stress and noise prevail. Following this, it is crucial to minimize unwanted vibration so that the effectiveness and the lifetime of the structure can be preserved. In this thesis, an intelligent proportional-integral-derivative (PID) controller has been developed for vibration suppression of a horizontal flexible plate structure. Initially, a flexible plate experimental rig was designed and fabricated with all clamped edges boundary conditions at horizontal position. Then, the data acquisition and instrumentation systems were integrated into the experimental rig. Several experimental procedures were conducted to acquire the input-output vibration data of the system. Next, the dynamics of the system was modeled using linear auto regressive with exogenous, which is optimized with three types of evolutionary swarm algorithm, namely, the particle swarm optimization (PSO), artificial bee colony (ABC) and bat algorithm (BAT) model structure. Their effectiveness was then validated using mean squared error, correlation tests and pole zero diagram stability. Results showed that the PSO algorithm has superior performance compared to the other algorithms in modeling the system by achieving lowest mean squared error of 6103947.4 , correlation of up to 95 % confidence level and good stability. Next, five types of PID based controllers were chosen to suppress the unwanted vibration, namely, PID-Ziegler Nichols (ZN), PID-PSO, PID-ABC, Fuzzy-PID and PID-Iterative Learning Algorithm (ILA). The robustness of the controllers was validated by exerting different types of disturbances on the system. Amongst all controllers, the simulation results showed that PID tuned by ABC outperformed other controllers with 47.60 dB of attenuation level at the first mode (the dominant mode) of vibration, which is equivalent to 45.99 % of reduction in vibration amplitude. By implementing the controllers experimentally, the superiority of PID-ABC based controller was further verified by achieving an attenuation of 23.83 dB at the first mode of vibration and 21.62 % of reduction in vibration amplitude. This research proved that the PID controller tuned by ABC is superior compared to other tuning algorithms for vibration suppression of the horizontal flexible plate structure

Design and development of intelligent actuator control methodologies for morphing wing in wind tunnel

In order to protect our environment by reducing the aviation carbon emissions and making the airline operations more fuel efficient, internationally, various collaborations were established between the academia and aeronautical industries around the world. Following the successful research and development efforts of the CRIAQ 7.1 project, the CRIAQ MDO 505 project was launched with a goal of maximizing the potential of electric aircraft. In the MDO 505, novel morphing wing actuators based on brushless DC motors are used. These actuators are placed chord-wise on two actuation lines. The demonstrator wing, included ribs, spars and a flexible skin, that is composed of glass fiber. The 2D and 3D models of the wing were developed in XFOIL and Fluent. These wing models can be programmed to morph the wing at various flight conditions composed of various Mach numbers, angles of attack and Reynolds number by allowing the computation of various optimized airfoils. The wing was tested in the wind tunnel at the IAR NRC Ottawa. In this thesis actuators are mounted with LVDT sensors to measure the linear displacement. The flexible skin is embedded with the pressure sensors to sense the location of the laminar-to-turbulent transition point. This thesis presents both linear and nonlinear modelling of the novel morphing actuator. Both classical and modern Artificial Intelligence (AI) techniques for the design of the actuator control system are presented. Actuator control design and validation in the wind tunnel is presented through three journal articles; The first article presents the controller design and wind tunnel testing of the novel morphing actuator for the wing tip of a real aircraft wing. The new morphing actuators are made up of BLDC motors coupled with a gear system, which converts the rotational motion into linear motion. Mathematical modelling is carried out in order to obtain a transfer function based on differential equations. In order to control the morphing wing it was concluded that a combined position, speed and current control of the actuator needs to be designed. This controller is designed using the Internal Model Control (IMC) method for the linear model of the actuator. Finally, the bench testing of the actuator is carried out and is further followed by its wind testing. The infra red thermography and kulite sensors data revealed that on average on all flight cases, the laminar to turbulent transition point was delayed close to the trailing edge of the wing. The second journal article presents the application of Particle Swarm Optimization (PSO) to the control design of the novel morphing actuator. Recently PSO algorithm has gained reputation in the family of evolutionary algorithms in solving non-convex problems. Although it does not guarantee convergence, however, by running it several times and by varying the initialization conditions the desired results were obtained. Following the successful computation of controller design, the PSO was validated using successful bench testing. Finally, the wind tunnel testing was performed based on the designed controller, and the Infra red testing and kulite sensor measurements results revealed the expected extension of laminar flows over the morphing wing. The third and final article presents the design of fuzzy logic controller. The BLDC motor is coupled with the gear which converts the rotary motion into linear motion, this phenomenon is used to push and pull the flexible morphing skin. The BLDC motor itself and its interaction with the gear and morphing skin, which is exposed to the aerodynamic loads, makes it a complex nonlinear system. It was therefore decided to design a fuzzy controller, which can control the actuator in an appropriate way. Three fuzzy controllers were designed each of these controllers was designed for current, speed and position control of the morphing actuator. Simulation results revealed that the designed controller can successfully control the actuator. Finally, the designed controller was tested in the wind tunnel; the results obtained through the wind tunnel test were compared, and further validated with the infra red and kulite sensors measurements which revealed improvement in the delay of transition point location over the morphed wing