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

Online identification and nonlinear control of the electrically stimulated quadriceps muscle

A new approach for estimating nonlinear models of the electrically stimulated quadriceps muscle group under nonisometric conditions is investigated. The model can be used for designing controlled neuro-prostheses. In order to identify the muscle dynamics (stimulation pulsewidth-active knee moment relation) from discrete-time angle measurements only, a hybrid model structure is postulated for the shank-quadriceps dynamics. The model consists of a relatively well known time-invariant passive component and an uncertain time-variant active component. Rigid body dynamics, described by the Equation of Motion (EoM), and passive joint properties form the time-invariant part. The actuator, i.e. the electrically stimulated muscle group, represents the uncertain time-varying section. A recursive algorithm is outlined for identifying online the stimulated quadriceps muscle group. The algorithm requires EoM and passive joint characteristics to be known a priori. The muscle dynamics represent the product of a continuous-time nonlinear activation dynamics and a nonlinear static contraction function described by a Normalised Radial Basis Function (NRBF) network which has knee-joint angle and angular velocity as input arguments. An Extended Kalman Filter (EKF) approach is chosen to estimate muscle dynamics parameters and to obtain full state estimates of the shank-quadriceps dynamics simultaneously. The latter is important for implementing state feedback controllers. A nonlinear state feedback controller using the backstepping method is explicitly designed whereas the model was identified a priori using the developed identification procedure

Constrained Nonlinear Model Predictive Control of an MMA Polymerization Process via Evolutionary Optimization

In this work, a nonlinear model predictive controller is developed for a batch polymerization process. The physical model of the process is parameterized along a desired trajectory resulting in a trajectory linearized piecewise model (a multiple linear model bank) and the parameters are identified for an experimental polymerization reactor. Then, a multiple model adaptive predictive controller is designed for thermal trajectory tracking of the MMA polymerization. The input control signal to the process is constrained by the maximum thermal power provided by the heaters. The constrained optimization in the model predictive controller is solved via genetic algorithms to minimize a DMC cost function in each sampling interval.Comment: 12 pages, 9 figures, 28 reference

Process analytical technology in food biotechnology

Biotechnology is an area where precision and reproducibility are vital. This is due to the fact that products are often in form of food, pharmaceutical or cosmetic products and therefore very close to the human being. To avoid human error during the production or the evaluation of the quality of a product and to increase the optimal utilization of raw materials, a very high amount of automation is desired. Tools in the food and chemical industry that aim to reach this degree of higher automation are summarized in an initiative called Process Analytical Technology (PAT). Within the scope of the PAT, is to provide new measurement technologies for the purpose of closed loop control in biotechnological processes. These processes are the most demanding processes in regards of control issues due to their very often biological rate-determining component. Most important for an automation attempt is deep process knowledge, which can only be achieved via appropriate measurements. These measurements can either be carried out directly, measuring a crucial physical value, or if not accessible either due to the lack of technology or a complicated sample state, via a soft-sensor.Even after several years the ideal aim of the PAT initiative is not fully implemented in the industry and in many production processes. On the one hand a lot effort still needs to be put into the development of more general algorithms which are more easy to implement and especially more reliable. On the other hand, not all the available advances in this field are employed yet. The potential users seem to stick to approved methods and show certain reservations towards new technologies.Die Biotechnologie ist ein Wissenschaftsbereich, in dem hohe Genauigkeit und Wiederholbarkeit eine wichtige Rolle spielen. Dies ist der Tatsache geschuldet, dass die hergestellten Produkte sehr oft den Bereichen Nahrungsmitteln, Pharmazeutika oder Kosmetik angehöhren und daher besonders den Menschen beeinflussen. Um den menschlichen Fehler bei der Produktion zu vermeiden, die Qualität eines Produktes zu sichern und die optimale Verwertung der Rohmaterialen zu gewährleisten, wird ein besonders hohes Maß an Automation angestrebt. Die Werkzeuge, die in der Nahrungsmittel- und chemischen Industrie hierfür zum Einsatz kommen, werden in der Process Analytical Technology (PAT) Initiative zusammengefasst. Ziel der PAT ist die Entwicklung zuverlässiger neuer Methoden, um Prozesse zu beschreiben und eine automatische Regelungsstrategie zu realisieren. Biotechnologische Prozesse gehören hierbei zu den aufwändigsten Regelungsaufgaben, da in den meisten Fällen eine biologische Komponente der entscheidende Faktor ist. Entscheidend für eine erfolgreiche Regelungsstrategie ist ein hohes Maß an Prozessverständnis. Dieses kann entweder durch eine direkte Messung der entscheidenden physikalischen, chemischen oder biologischen Größen gewonnen werden oder durch einen SoftSensor. Zusammengefasst zeigt sich, dass das finale Ziel der PAT Initiative auch nach einigen Jahren des Propagierens weder komplett in der Industrie noch bei vielen Produktionsprozessen angekommen ist. Auf der einen Seite liegt dies mit Sicherheit an der Tatsache, dass noch viel Arbeit in die Generalisierung von Algorithmen gesteckt werden muss. Diese müsse einfacher zu implementieren und vor allem noch zuverlässiger in der Funktionsweise sein. Auf der anderen Seite wurden jedoch auch Algorithmen, Regelungsstrategien und eigne Ansätze für einen neuartigen Sensor sowie einen Soft-Sensors vorgestellt, die großes Potential zeigen. Nicht zuletzt müssen die möglichen Anwender neue Strategien einsetzen und Vorbehalte gegenüber unbekannten Technologien ablegen

MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory

In this work, a new pre-tuning multivariable PID (Proportional Integral Derivative) controllers method for quadrotors is put forward. A procedure based on LQR/LQG (Linear Quadratic Regulator/Gaussian) theory is proposed for attitude and altitude control, which suposes a considerable simplification of the design problem due to only one pretuning parameter being used. With the aim to analyze the performance and robustness of the proposed method, a non-linear mathematical model of the DJI-F450 quadrotor is employed, where rotors dynamics, together with sensors drift/bias properties and noise characteristics of low-cost commercial sensors typically used in this type of applications are considered. In order to estimate the state vector and compensate bias/drift effects in the measures, a combination of filtering and data fusion algorithms (Kalman filter and Madgwick algorithm for attitude estimation) are proposed and implemented. Performance and robustness analysis of the control system is carried out by employing numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show the proposed controller design method for multivariable PID controller is robust with respect to: (a) parametric uncertainty in the plant model, (b) disturbances acting at the plant input, (c) sensors measurement and estimation errors

Review of dynamic positioning control in maritime microgrid systems

For many offshore activities, including offshore oil and gas exploration and offshore wind farm construction, it is essential to keep the position and heading of the vessel stable. The dynamic positioning system is a progressive technology, which is extensively used in shipping and other maritime structures. To maintain the vessels or platforms from displacement, its thrusters are used automatically to control and stabilize the position and heading of vessels in sea state disturbances. The theory of dynamic positioning has been studied and developed in terms of control techniques to achieve greater accuracy and reduce ship movement caused by environmental disturbance for more than 30 years. This paper reviews the control strategies and architecture of the DPS in marine vessels. In addition, it suggests possible control principles and makes a comparison between the advantages and disadvantages of existing literature. Some details for future research on DP control challenges are discussed in this paper

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Automatic control of a multirotor

Objective of this thesis is to describe the design and realisation phases of a multirotor to be used for low risk and cost aerial observation. Starting point of this activity was a wide literature study related to the technological evolution of multirotors design and to the state of the art. Firstly the most common multirotor configurations were defined and, according to a size and performance based evaluation, the most suitable one was chosen. A detailed computer aided design model was drawn as basis for the realisation of two prototypes. The realised multirotors were “X-shaped” octorotors with eight coaxially coupled motors. The mathematical model of the multirotor dynamics was studied. “Proportional Integral Derivative” and “Linear Quadratic” algorithms were chosen as techniques to regulate the attitude dynamics of the multirotor. These methods were tested with a nonlinear model simulation developed in the Matlab Simulink environment. In the meanwhile the Arduino board was selected as the best compromise between costs and performance and the above mentioned algorithms were implemented using this platform thanks to its main characteristic of being completely “open source”. Indeed the multirotor was conceived to be a serviceable tool for the public utility and, at the same time, to be an accessible device for research and studies. The behaviour of the physical multirotor was evaluated with a test bench designed to isolate the rotation about one single body axis at a time. The data of the experimental tests were gathered in real time using a custom Matlab code and several indoor tests allowed the “fine tuning” of the controllers gains. Afterwards a portable “ground station” was conceived and realised in adherence with the real scenarios users needs. Several outdoor experimental flights were executed with successful results and the data gathered during the outdoor tests were used to evaluate some key performance indicators as the endurance and the maximum allowable payload mass. Then the fault tolerance of the control system was evaluated simulating and experimenting the loss of one motor; even in this critical condition the system exhibited an acceptable behaviour. The reached project readiness allowed to meet some potential users as the “Turin Fire Department” and to cooperate with them in a simulated emergency. During this event the multirotor was used to gather and transmit real time aerial images for an improved “situation awareness”. Finally the study was extended to more innovative control techniques like the neural networks based ones. Simulations results demonstrated their effectiveness; nevertheless the inherent complexity and the unreliability outside the training ranges could have a catastrophic impact on the airworthiness. This is a factor that cannot be neglected especially in the applications related to flying platforms. Summarising, this research work was addressed mainly to the operating procedures for implementing automatic control algorithms to real platforms. All the design aspects, from the preliminary multirotor configuration choice to the tests in possible real scenarios, were covered obtaining performances comparable with other commercial of-the-shelf platforms