Controller design for servo motor

Closed-loop identification with routine operating data: Effect of time delay and sampling time

Temperature control is desirable in heat exchanger system due to fact that chemical processing plants requires certain level of temperature for a given for a particular processing. This research aims at the development of a PID controller for outlet temperature control of a heat exchanger system. The proposed controller was developed based on MIGO (M-Constrained integral gain optimisation) tuning algorithm and simulated using MATLAB/Simulink. The system model is represented using discrete time domain approach at specific interval of sampling time, the results obtained showed that an increase in sampling time gives a resultant increase in settling time for all operating conditions considered. Similarly the values of rise time increases with the increase of sampling time at no disturbance condition but decreases during the application of disturbance. Also the occurrence of overshoot and undershoot decreases as the sampling time increases at no disturbance condition except for a sampling time of 1.0 second, but for the disturbed condition, the overshoot and undershoot are not experienced as the sampling time increase.

Closed-Loop Identification using Routine Operating Data: the Effect of Time Delay

Parameter estimation and speed control of a PMDC motor used in wheelchair

This paper presents a real-time implementation of a genetic-based hybrid fuzzy-PID controller for industrial motor drives. Both the design of fuzzy-PID controller and its integration with the conventional PID in global control system to produce a hybrid design is demonstrated. A genetic optimization technique is used to determine the optimal values of the scaling factors of the output variables of the fuzzy-PID controller. The objective is to utilize the best attributes of the PID and fuzzy-PID controllers to provide a controller, which will produce better response than either the PID or the fuzzy-PID controller. The principle of the hybrid controller is to use a PID controller, which performs satisfactorily in most cases, while keeping in the background, a fuzzy-PID controller, which, is ready to take over the PID controller when severe disturbs occur. The hybrid controller is formulated and implemented in real-time, using the speed control of a brushless drive system as a testbed. The design, analysis, and implementation stages are carried out entirely using a dSPACE DS1104 digital signal processor (DSP)-based real-time data acquisition control (DAC) system, and MATLAB/Simulink environment. Experimental results show that the proposed fuzzy- PID controller-based genetic optimization produces better control performance than the conventional PID controllers, particularly in handling nonlinearities and external disturbances.

Effects of time and sampling location on concentrations of β-hydroxybutyric acid in dairy cows

Chapter 13 - The PID Controller

15 - The PID controller

The hardware used for software implementation on a physical system introduces uncertainty into the controller. If neglected during design, this uncertainty can lead to poor controller performance, resulting in significant design and verification iterations. In this work, the effect of sampling time, quantization, and fixed-point computation are directly accounted for in the control design. Sampling time is compensated for by a discrete-time controller. A generic methodology is developed for modeling the worst-case scenario effect of quantization and fixed-point computation on the control commands. The cold-start emission control problem is used as a case study, and a discrete-time sliding surface controller is developed. Verification is performed to ensure the estimated worst-case scenario uncertainty bounds are accurate. The bounds are incorporated into a modified version of the control laws. During simulation the modified controller demonstrates significant reduction in tracking error in the presence of hardware imprecisions.

Seasonal variation in testis size, gonadotrophin secretion and pituitary responsiveness to GnRH in rams of two breeds differing in time of onset of the breeding season

Replacement of the generator set (genset) gasoline fuel using LPG fuel causes several problems. One of the problems is that the engine rotation speed is not stable. The problem is caused by the influence of the ratio of air and fuel mixture to the internal combustion engine. By using the electronic control unit (ECU), the ratio of air and fuel mixture can be adjusted to the needs of the engine so that the engine speed is maintained. Controlling the actuator based on sensing parameter with using ECU on engine. This paper focuses on a simple design of ECU to adjust the ratio of air and fuel mixture and frequency output in the genset. Control of servo motor and injector using ECU based microcontroller Cortex-M3. Setting the duration of injection using second degree polynomial function obtained based on regression analysis on injection mapping. Control of frequency output using PI and PID controls can maintain response time according to the characteristics when using gasoline. In 3 scenarios of dynamic conditions, the application of PI and PID controls gives a good effect in maintaining the output frequency in the generator.

This paper aimed on showing how efficient a Fuzzy-PID controller can control the speed and vibration of an Induction motor and how it can replace the conventional PID controllers. This testing is performed in MATLABSimulink software. The three phase Induction motor’s transfer function is framed and the PID controller values are auto-tuned. The output of PID and Fuzzy-PID Inference system controller show the Speed-Time waveforms. From these waveforms, the properties can be found leading to the conclusion which helps us decide which control system is efficient over the other. Wave properties such as rise-time, peak time, settling time and maximum overshoot values of the control systems are calculated and tabulated. The end comparative results show us that the Fuzzy-PID Inference system has better and safe wave characteristics compared to PID controller. This way Fuzzy-PID controller is much preferred and safe in the long run compared to PID controllers.

Variability of biofouling communities on fish cage nets: A 1-year field study at a Norwegian salmon farm

Arbuscular mycorrhizal fungal communities in buffelgrass pasture under intercropping and shading systems in Brazilian semiarid conditions

This paper suggests a new fuzzy PID controller with variable parameters which improves the shortage of the fuzzy PID controller with fixed parameters suggested in [9]. The derivation procedure follows the general design procedure of the fuzzy logic controller, while the resultant control law is the form of the conventional PID controller. Therefore, the suggested controller has two advantages. One is that it has only four fuzzy linguistic rules and analytical form of control laws so that the real-time control system can be implemented based on low-price microprocessors. The other is that the PID control action can always be achieved with time-varying PID controller gains only by adjusting the input and output scalers at each sampling time.