Modelling and Dynamic Response Characteristics Study of a PAM Bionic Kangaroo Leg Suspension

Label-free immunosensors are well suited for detection of microorganisms because of their fast response and reasonable sensitivity comparable to infection doses of common pathogens. Active (lever oscillator and frequency counter) and passive (impedance analyzer) modes of quartz crystal microbalance (QCM) were used and compared for rapid detection of three strains of E. coli. Different approaches for antibody immobilization were compared, the immobilization of reduced antibody using Sulfo‐SMCC was most effective achieving the limit of detection (LOD) 8 × 104 CFU·mL−1 in 10 min. For the passive mode, software evaluating impedance characteristics in real-time was developed and used. Almost the same results were achieved using both active and passive modes confirming that the sensor properties are not limited by the frequency evaluation method but mainly by affinity of the antibody. Furthermore, reference measurements were done using surface plasmon resonance. Effect of condition of cells on signal was observed showing that cells ruptured by ultrasonication provided slightly higher signal changes than intact microbes.

The progressive failure and scale effect of trap-door problems were evaluated, by comparing experimental results with finite element analyses employing the elasto-plastic model including the shear band effect. The experiments were performed in passive and active mode by measuring load-displacement relationships and observing shear band developments using two sizes of apparatus (the trap-door width of the smaller one was 5 cm and of the larger one 10 cm.) The load was measured with soil stress measurement cells embedded in the face of the trap-door. The shear band developments were observed using thin horizontal colored sand layers placed in the sand mass. The distribution of earth pressure by finite element analysis achieved good agreement with experimental results. The localized narrow zone of shear strain by the analysis was approximately identical with the observed shear band in both passive and active modes. The scale effect was recognized by the analysis and the experiment only in passive mode.

To study human motor control and learning in upper extremities, scientists widely use robotic arms to apply external forces to subject’s hand interactively. In this work, we describe the design procedure of a planar parallel manipulandum with five links and 2-DoF in a vertical plane (e.g. sagittal or frontal plane). The manipulandum works in two active and passive modes. In the passive mode, the robotic arm follows the movements of the human arm; while in the active mode, the robotic endeffector guides subject’s hand in any desired direction. In both active and passive conditions, the robot arm can be programmed to apply unexpected disturbances to the subjects hand. To control the movement of the manipulandum, we used two PID controllers with local shaft angle feedback to control the manipulandum. For the active mode, we used also a global feedback from endeffector position. As the first step for proof of concept, the whole system was simulated in MATLAB.

A portable solar still's productivity boost combining a magnetic stirrer and thermoelectric

In the process of frozen food production, its refrigeration system is a typical large inertia, nonlinear, strongly coupled system, which is prone to large overshooting during operation, resulting in cost increase and quality control problems. This paper solves the problem of large overshoot in the digital PID control process by designing a fuzzy control, and designs a practical fuzzy controller so that the design method of the fuzzy PID controller can be realized in the simulation and actual control of the freezing system. A genetic algorithm optimization scheme is also designed for the fuzzy PID control system to optimize the fuzzy controller’s affiliation function, control rules, as well as proportionality and quantization factors, to enhance the model’s dynamic characteristics and robustness. Design of food quick-freezing simulation experiments and use the model in the refrigeration system control in practice, compare the performance of this model with the PID, fuzzy PID model, and found that the temperature difference set value of 4 ℃ and 3 ℃, respectively, the parameters of the traditional PID controller in the commissioning stage of the system after the end of the rectification to remain fixed, which makes the actual quality of the cooling water temperature difference control degradation. And the fuzzy genetic PID controller still has good control quality. In this paper, the model curve converges rapidly, the overshoot is only 3.9%, and the regulation time is only 450M seconds. The designed method of the study is feasible and has high industrial application value.

Sensitive measurements require a vibration isolation system to safeguard against detrimental tremble. Two types of vibration isolation systems - passive and active - are currently implemented. The spring-based passive designs usually accompany with ineffective low-frequency response. Therefore, the active designs, consisting of sensors, feedback control systems, and actuators, are consolidated to improve the total effectiveness of the cancellation performance. In this work, we focus on developing the actuator founded on electromagnetic spring to be incorporated into our compact quantum gravimeter. Each spring-actuated part comprises two repelling Nd magnets positioned face to face inside a solenoid. With this configuration, the spring can also work in the passive mode via repulsive magnetic force. In the active mode, the exerted force is a result of magnetic fields formed by the magnets and the current-controlled solenoid coils. By changing the coil current, the stiffness of the spring can be modified, and thus the displacement can be controlled. Different sizes of magnets are explored, and their force behaviors in passive and active modes are characterized. The implementation scheme of the actuator in the quantum gravimeter is also discussed.

Fuzzy logic control based on the Takagi–Sugeno inference method has been applied for the yeast alcoholic fermentation running in a continuous-time biochemical reactor in this paper. A type-1 fuzzy PID controller was designed to temperature control in a biochemical reactor. The fuzzy PID controller was also designed using type-2 fuzzy sets. The advantage of the fuzzy control is that it can be used very successfully for control of strongly non-linear processes and processes that are difficult to model because of complicated reaction kinetics. Obtained simulation results confirm this fact. The disadvantage of the fuzzy control design lies in the time-consuming tuning of controllers. The subtractive clustering method was used to identify the rule base. This approach was chosen to minimize the number of rules of the designed fuzzy logic controllers and to simplify the fuzzy controller design. Simulation results confirm that fuzzy PID controllers can assure better performance than conventional PID controllers. Yeast alcoholic fermentation is an exothermic process and the cooling is necessary to maintain the optimal temperature in the reactor. Fuzzy PID control reduces coolant consumption in comparison with conventional PID control and so it assures energy-efficient control of continuous-time alcoholic fermentation. Using type-2 fuzzy sets in the fuzzy PID controller design is very promising as the type-2 fuzzy controller offers even better results than the type-1 fuzzy controller.

A novel type of semi-active jet turbulence grid

The trap door problem is a useful model for providing a clearer understanding of the stress distribution around civil engineering structures such as anchor plates and tunnels. The passive mode can be used either to compute the uplift force of anchors or any buried structure which may be idealized as an anchor; the active mode can be used to compute the gravitational flow of a granular material between vertical walls or the soil reaction curve for tunnel design. Both modes of displacement are modelled numerically in this Paper using the finite element method. The results are presented in the form of influence charts, which may be used for both the passive and active modes to provide failure loads for a range of geometries and soil properties, using non-dimensionalized parameters. The use of these equations is compared with results obtained from other sources using both physical and numerical models. Le probleme de la trappe représente un modéle utile pour l'obtention d'une compréhension plus claire de la distribution des contraintes autour de structures du génie civil telles que les plaques d'ancrage et les tunnels. Le mode passif peut s'employer pour calculer la force d'arrachement des éléments d'ancrage ou d'une construction quel-conque ayant la fonction d'un element d'ancrage, tandis que le mode actif peut être utilisé pour calculer l'écoulement gravitationnel d'une matière granulée entre des murs verticaux ou la courbe de réaction du sol dans le cas d'un tunnel. Dans cet article les deux modes de déplacement sont model-és de fa&cidel;on numérique à l'aide de la méthode aux éléments finis. Les résultats sont présentés dans la forme de graphiques d'influence qui peuvent s'employer pour les modes passif et actif dans le but d'obtenir des chargements de rupture pour une serie de géométries et de propriétés du sol en uti-lisant des paramétres non-dimensionnes. L'emploi de ces équations est comparé aux résultats obtenus à partir d'autres sources en utilisant des modèles physiques et numériques.

Because of the existing hybrid fuzzy PID controller does not perform, using electric hydraulic servo system application (SEHS). Therefore, when the system parameters change will require a new adjustment of PID controller variable. Therefore, a hybrid fuzzy and fuzzy self-tuning PID control was put forward. With this control scheme was divided into two parts, and the fuzzy controller and fuzzy self-tuning PID controller. Fuzzy controller is used to control the output of the system of the values of the system away from target value. We proved that the performance of the control scheme through the experiment of the motor speed control SEHS. The experimental results show that the proposed a hybrid fuzzy PID controller and fuzzy self-tuning effect is better than that of a hybrid fuzzy and PID controller.

In CNC lathe servo feed system, many parameters are uncertain, so it is difficult to establish accurate mathematical model of the feed system, and parameters of conventional PID controller can not change the parameters to adjust with the controlled object. Fuzzy PID controller, which has the advantages of conventional PID control and fuzzy control, can solve these problems very well. So we can make it applied in CNC lathe servo feed system. This paper has made a simulation of fuzzy self-turning PID controller in the MATLAB environment. The simulation shows that the fuzzy self-turning PID controller has a better control capability and a higher stability, and it improved the servo feed system dynamic performance.

Cascade fuzzy control of a tubular chemical reactor

Aiming at the limitation of traditional PID algorithm in the field of control, the fuzzy control theory and traditional PID control algorithm are combined to realize parameter self-tuning function, a fuzzy self-tuning PID controller, and this algorithm is analyzed in-depth study. It provides a new solution of modern industrial control problem that combining with fuzzy control technology and PID control technology. The FPGA has high integration, short development cycle, the characteristics of strong reusability; fuzzy PID controller has a good practical value and optimistic application prospect based on FPGA.

The paper is concerned with two types of fuzzy PID controllers, the rule-based fuzzy PID controller and the learning fuzzy PID controller. Initially, the development of the rule-based fuzzy PID controller is studied, and subsequently, the development of the learning fuzzy PID controller is outlined. For the rule-based fuzzy PID controller, the PID gains are firstly tuned using a conventional tuning method. The rule buffer of the rule-based fuzzy then readjusts the PID gains during the system operation. The learning fuzzy PID controller not only readjusts the PID gains, it also creates and updates the rules in the rule-buffer automatically during the application of the learning fuzzy PID controller to the process. The rule-based fuzzy PID controller and the learning fuzzy PID controller are both applied to a non-linear revolute-joint robot-arm for path tracking experiments. The results of the experiments for the rule-based fuzzy PID controller and the learning fuzzy controller are compared with a conventional PID controller in order to evaluate the results.

PID and fuzzy PID controller are applied into the wind turbine with nonlinear mathematical model. PID control has simple principle and its parameters setting are rather easy. Fuzzy control need not to establish the mathematical of the control system and has strong robustness. Fuzzy PID control is combined with PID control and fuzzy control. The advantages of fuzzy PID control are simple, easy in setting parameters and strong robustness. Fuzzy PID controller combines with closed-loop optimal fuzzy reasoning (COFR), which can effectively improve the robustness, when the robustness is special requirement. MATLAB software is used for simulations, results display that fuzzy PID controller which combines with COFR has better performances than PID controller when errors exist, especially robustness performance.