A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

Advanced and Innovative Optimization Techniques in Controllers: A Comprehensive Review

New commercial power electronic controllers come to the market almost every day to help improve electronic circuit and system performance and efficiency. In DC–DC switching-mode converters, a simple and elegant hysteretic controller is used to regulate the basic buck, boost and buck–boost converters under slightly different configurations. In AC–DC converters, the input current shaping for power factor correction posts a constraint. But, several brilliant commercial controllers are demonstrated for boost and fly back converters to achieve almost perfect power factor correction. In this paper a comprehensive review of the various advanced optimization techniques used in power electronic controllers is presented

Fractional Order Controller Designing with Firefly Algorithm and Parameter Optimization for Hydroturbine Governing System

A fractional order PID (FOPID) controller, which is suitable for control system designing for being insensitive to the variation in system parameter, is proposed for hydroturbine governing system in the paper. The simultaneous optimization for several parameters of controller, that is, Ki, Kd, Kp, λ, and μ, is done by a recently developed metaheuristic nature-inspired algorithm, namely, the firefly algorithm (FA), for the first time, where the selecting, moving, attractiveness behavior between fireflies and updating of brightness, and decision range are studied in detail to simulate the optimization process. Investigation clearly reveals the advantages of the FOPID controller over the integer controllers in terms of reduced oscillations and settling time. The present work also explores the superiority of FA based optimization technique in finding optimal parameters of the controller. Further, convergence characteristics of the FA are compared with optimum integer order PID (IOPID) controller to justify its efficiency. What is more, analysis confirms the robustness of FOPID controller under isolated load operation conditions

Fractional Order Fuzzy Control of Nuclear Reactor Power with Thermal-Hydraulic Effects in the Presence of Random Network Induced Delay and Sensor Noise having Long Range Dependence

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Nonlinear state space modeling of a nuclear reactor has been done for the purpose of controlling its global power in load following mode. The nonlinear state space model has been linearized at different percentage of reactor powers and a novel fractional order (FO) fuzzy proportional integral derivative (PID) controller is designed using real coded Genetic Algorithm (GA) to control the reactor power level at various operating conditions. The effectiveness of using the fuzzy FOPID controller over conventional fuzzy PID controllers has been shown with numerical simulations. The controllers tuned with the highest power models are shown to work well at other operating conditions as well; over the lowest power model based design and hence are robust with respect to the changes in nuclear reactor operating power levels. This paper also analyzes the degradation of nuclear reactor power signal due to network induced random delays in shared communication network and due to sensor noise while being fed-back to the Reactor Regulating System (RRS). The effect of long range dependence (LRD) which is a practical consideration for the stochastic processes like network induced delay and sensor noise has been tackled by optimum tuning of FO fuzzy PID controllers using GA, while also taking the operating point shift into consideration

Robust nonlinear control of vectored thrust aircraft

An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations