Nonlinear Controller for the Set-Point Regulation of a Buck Converter System

In this paper, we present a nonlinear PID controller based on saturation functions with variable parameters in order to regulate the output voltage of a buck converter in the presence of changes in the input voltage. The main feature of the proposed controller is to bound the control input with a variable parameter to avoid the windup effect generated by the combination of the integral control action and some operation conditions. The main advantages of the proposed nonlinear PID controller are its low computing cost and the simple tuning task to implement the control strategy in an embedded system. The acceptable behavior of the closed-loop system is presented through the simulation and experimental results.

A Wiener Model Based Closed Loop FES for Positional Control During Wrist Flexion

Functional electrical stimulation is an assistive technique used to produce functional movements in patients suffering from neurological impairments. However, existing open-loop clinical FES systems are not adequately equipped to compensate for the nonlinear, time-varying behaviour of the muscles. On the other hand, closed-loop FES systems can compensate for the aforementioned effects by regulating the stimulation to induce desired contractions. Therefore, this work aims to present an approach to implement a closed-loop FES system to enable angular positional control during wrist flexion. First, a Wiener model describing the response of the wrist flexor to pulse width modulated stimulation was identified for two healthy volunteers. Second, a nonlinear PID controller (subject-specific) was designed based on the identified models to enable angular positional control during wrist flexion. Subsequently, the controller was implemented in real-time and was tested against two reference angles on healthy volunteers. This study shows promise that the presented closed-loop FES approach can be implemented to control the angular position during wrist flexion or a novelty of the work when compared with the existing work.

Multi-Parameter Estimation of Uncertain Systems Based on the Extended PID Control Method

Parameter estimation is an important step in the identification of systems. With the extension of systems, there needs the multi-parameter estimation of systems. The estimation of multi parameters of complex systems based on the extended PID controllers is considered in this chapter. As the related references proved that the integral item of the nonlinear PID controller could deal with the uncertain part of the complex system (which can also be called new stripping principle, simple notes as NSP). Based on this theory, new multi-parameter estimation method is given. Firstly, the unknown parameters are expanded to new states of the system. Two cases, parameters are constant or changing with time, are separately analyzed. In the time-variant case, the unknown parameters are extended to functions which actual forms are uncertain. Secondly the method NSP could be applied to cope with the uncertain part, and then reconstruction state observation to estimate the states. If the states are observed, the unknown parameters are obtained at the same time. Finally the convergence analysis of the error systems and some simulations will be given in this chapter to indicate the effectiveness of the proposed method.

Enhanced Nonlinear PID Controller for Positioning Control of Maglev System

Magnetic levitation (maglev) is a way of using electromagnetic fields to levitate objects without any noise or the need for petrol or air. Due to its highly nonlinear and unstable behavior, numerous control solutions have been proposed to overcome it. However, most of them still acquire precise dynamic model parameters, or deep understanding of control theory. To account the complexity in the design procedure, a practical controller consists of classical and modern control approaches are proposed. This chapter presents a practical controller for high positioning performance of a magnetic levitation system. Three strategies of the proposed controller where the PI-PD controller is to enhance transient response, the model-based feedforward control (FF) is incorporated with the PI-PD controller to enhance the overshoot reduction characteristic in attaining a better transient response, and lastly the disturbance compensator (Kz) is integrated as an additional feedback element to reduce the sensitivity function magnitude for robustness enhancement. The proposed controller - FF PI-PD + Kz has a simple and straightforward design procedure. The usefulness of the proposed controller is evaluated experimentally.

A Self-Tuning NPID Control Method for FOPTD Processes

Owing to the time-varying characteristics and nonlinearities of industrial processes, control has higher difficulties and results in challenges for advanced technology. In this paper, a self-tuning controller that includes a nonlinear proportional-integral-derivative (NPID) control function as well as a self-tuning function is proposed for first-order plus time delay (FOPTD) process control. The NPID control function is implemented using the nonlinear PID controller whose optimum parameters are adapted by a neural network (NN). The self-tuning function is able to identify the process dynamics using a short period of process behavior and tune NPID parameters based on the identified parameters. The advantage of the proposed method is validated with a set of simulation works on three processes and the comparison results are presented.