Design and implementation of fuzzy logic controllers

The main objectives of our research are to present a self-contained overview of fuzzy sets and fuzzy logic, develop a methodology for control system design using fuzzy logic controllers, and to design and implement a fuzzy logic controller for a real system. We first present the fundamental concepts of fuzzy sets and fuzzy logic. Fuzzy sets and basic fuzzy operations are defined. In addition, for control systems, it is important to understand the concepts of linguistic values, term sets, fuzzy rule base, inference methods, and defuzzification methods. Second, we introduce a four-step fuzzy logic control system design procedure. The design procedure is illustrated via four examples, showing the capabilities and robustness of fuzzy logic control systems. This is followed by a tuning procedure that we developed from our design experience. Third, we present two Lyapunov based techniques for stability analysis. Finally, we present our design and implementation of a fuzzy logic controller for a linear actuator to be used to control the direction of the Free Flight Rotorcraft Research Vehicle at LaRC

Control techniques for mechatronic assisted surgery

The treatment response for traumatic head injured patients can be improved by using an autonomous robotic system to perform basic, time-critical emergency neurosurgery, reducing costs and saving lives. In this thesis, a concept for a neurosurgical robotic system is proposed to perform three specific emergency neurosurgical procedures; they are the placement of an intracranial pressure monitor, external ventricular drainage, and the evacuation of chronic subdural haematoma. The control methods for this system are investigated following a curiosity led approach. Individual problems are interpreted in the widest sense and solutions posed that are general in nature. Three main contributions result from this approach: 1) a clinical evidence based review of surgical robotics and a methodology to assist in their evaluation, 2) a new controller for soft-grasping of objects, and 3) new propositions and theorems for chatter suppression sliding mode controllers. These contributions directly assist in the design of the control system of the neurosurgical robot and, more broadly, impact other areas outside the narrow con nes of the target application. A methodology for applied research in surgical robotics is proposed. The methodology sets out a hierarchy of criteria consisting of three tiers, with the most important being the bottom tier and the least being the top tier. It is argued that a robotic system must adhere to these criteria in order to achieve acceptability. Recent commercial systems are reviewed against these criteria, and are found to conform up to at least the bottom and intermediate tiers. However, the lack of conformity to the criteria in the top tier, combined with the inability to conclusively prove increased clinical benefit, particularly symptomatic benefit, is shown to be hampering the potential of surgical robotics in gaining wide establishment. A control scheme for soft-grasping objects is presented. Grasping a soft or fragile object requires the use of minimum contact force to prevent damage or deformation. Without precise knowledge of object parameters, real-time feedback control must be used to regulate the contact force and prevent slip. Moreover, the controller must be designed to have good performance characteristics to rapidly modulate the fingertip contact force in response to a slip event. A fuzzy sliding mode controller combined with a disturbance observer is proposed for contact force control and slip prevention. The robustness of the controller is evaluated through both simulation and experiment. The control scheme was found to be effective and robust to parameter uncertainty. When tested on a real system, however, chattering phenomena, well known to sliding mode research, was induced by the unmodelled suboptimal components of the system (filtering, backlash, and time delays). This reduced the controller performance. The problem of chattering and potential solutions are explored. Real systems using sliding mode controllers, such as the control scheme for soft-grasping, have a tendency to chatter at high frequencies. This is caused by the sliding mode controller interacting with un-modelled parasitic dynamics at the actuator-input and sensor-output of the plant. As a result, new chatter-suppression sliding mode controllers have been developed, which introduce new parameters into the system. However, the effect any particular choice of parameters has on system performance is unclear, and this can make tuning the parameters to meet a set of performance criteria di cult. In this thesis, common chatter-suppression sliding mode control strategies are surveyed and simple design and estimation methods are proposed. The estimation methods predict convergence, chattering amplitude, settling time, and maximum output bounds (overshoot) using harmonic linearizations and invariant ellipsoid sets

Evolutionary learning and global search for multi-optimal PID tuning rules

With the advances in microprocessor technology, control systems are widely seen not only in industry but now also in household appliances and consumer electronics. Among all control schemes developed so far, Proportional plus Integral plus Derivative (PID) control is the most widely adopted in practice. Today, more than 90% of industrial controllers have a built-in PID function. Their wide applications have stimulated and sustained the research and development of PID tuning techniques, patents, software packages and hardware modules. Due to parameter interaction and format variation, tuning a PID controller is not as straightforward as one would have anticipated. Therefore, designing speedy tuning rules should greatly reduce the burden on new installation and ‘time-to-market’ and should also enhance the competitive advantages of the PID system under offer. A multi-objective evolutionary algorithm (MOEA) would be an ideal candidate to conduct the learning and search for multi-objective PID tuning rules. A simple to implement MOEA, termed s-MOEA, is devised and compared with MOEAs developed elsewhere. Extensive study and analysis are performed on metrics for evaluating MOEA performance, so as to help with this comparison and development. As a result, a novel visualisation technique, termed “Distance and Distribution” (DD)” chart, is developed to overcome some of the limitations of existing metrics and visualisation techniques. The DD chart allows a user to view the comparison of multiple sets of high order non-dominated solutions in a two-dimensional space. The capability of DD chart is shown in the comparison process and it is shown to be a useful tool for gathering more in-depth information of an MOEA which is not possible in existing empirical studies. Truly multi-objective global PID tuning rules are then evolved as a result of interfacing the s-MOEA with closed-loop simulations under practical constraints. It takes into account multiple, and often conflicting, objectives such as steady-state accuracy and transient responsiveness against stability and overshoots, as well as tracking performance against load disturbance rejection. These evolved rules are compared against other tuning rules both offline on a set of well-recognised PID benchmark test systems and online on three laboratory systems of different dynamics and transport delays. The results show that the rules significantly outperform all existing tuning rules, with multi-criterion optimality. This is made possible as the evolved rules can cover a delay to time constant ratio from zero to infinity based on first-order plus delay plant models. For second-order plus delay plant models, they can also cover all possible dynamics found in practice

PID controller design and tuning in networked control systems

Networked control systems (NCS) are distributed real-time computing and control systems with sensors, actuators and controllers that communicate over a shared medium. The distributed nature of NCS and issues related to the shared communication medium pose significant challenges for control design, as the control system no longer follows the rules of classical control theory. The main problems that are not well covered by the traditional control theory are varying time-delays due to communication and computation, and packet losses. During recent years, the control design of NCS and varying time-delay systems has been extensively researched. This investment has provided us with new results on stability. Often the proposed methods and solutions are far too complex for industrial use, especially if wireless automation applications are considered. The algorithms are computationally heavy, possibly requiring complete information from say, a network of hundreds or thousands of nodes. In the wireless case this is not feasible. The above justifies the use and research of simple controller structures and algorithms for NCS. Despite the growing interest towards more advanced control algorithms, the Proportional-Integral-Derivative (PID) controller still has a dominant status in the industry. Nevertheless, using PID for NCS has not been thoroughly investigated, especially with regard to controller tuning. This thesis proposes several PID tuning methods, which provide robustness against the challenges of NCS, namely varying time-delays (jitter) and packet loss. The doctoral thesis consists of a summary and eight publications that focus on the PID controller design, tuning and experimentation in NCS. The thesis includes a literature review of recent stability and control design results in NCS, a summary of publications and the original publications. The control design methods applied in the publications are also reviewed. In the thesis, several new methods for PID tuning in NCS are proposed. To make the methods usable, a PID tuning tool that implements one of the tuning methods is also developed. In order to verify the results of control design with real processes, the thesis suggests using the MoCoNet platform developed at the Helsinki University of Technology, Finland. The platform provides the tools for remote laboratory experiments in NCS settings. The results of the thesis indicate that the PID controller is well suited for NCS provided that the properties of the integrated communication and control system are taken into account in the tuning phase