Robust fractional-order control using a decoupled pitch and roll actuation strategy for the I-support soft robot

This article belongs to the Special Issue Applications of Mathematical Models in Engineering.Tip control is a current open issue in soft robotics; therefore, it has received a good amount of attention in recent years. The desirable soft characteristics of these robots turn a well-solved problem in classic robotics, like the end-effector kinematics and dynamics, into a challenging problem. The high redundancy condition of these robots hinders classical solutions, resulting in controllers with very high computational costs. In this paper, a simplification is proposed in the actuation setup of the I-Support soft robot, allowing the use of simple strategies for tip inclination control. In order to verify the proposed approach, inclination step input and trajectory-tracking experiments were performed on a single module of the I-Support robot, resulting in zero output error in all cases, including those where the system was exposed to disturbances. The comparative results of the proposed controllers, a proportional integral derivative (PID) and a fractional order robust (FOPI) controller, validate the feasibility of the proposed approach, showing a clear advantage in the use of the fractional robust controller for the tip inclination control of the I-Support robot compared to the integer order controller.The research leading to these results has received funding from the project Desarrollo de articulaciones blandas para aplicaciones robóticas, with reference IND2020/IND-1739, funded by the Comunidad Autónoma de Madrid (CAM) (Department of Education and Research), from HUMASOFT project, with reference DPI2016-75330-P, funded by the Spanish Ministry of Economy and Competitiveness, and from RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos, FaseIV; S2018/NMT-4331), funded by "Programas de Actividades I+D en la Comunidad de Madrid" and cofunded by Structural Funds of the EU. This work was also funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 863212 (PROBOSCIS) and No. 824074 (GROWBOT)

Iso-damping fractional-order control for robust automated car-following

This work deals with the control design and development of an automated car-following strategy that further increases robustness to vehicle dynamics uncertainties. The control algorithm is applied on a hierarchical architecture where high and low level control layers are designed for gap-control and desired acceleration tracking, respectively. A fractional-order controller is proposed due to its flexible frequency shape, fulfilling more demanding design requirements. The iso-damping loop property is sought, which yields a desired closed-loop stability that results invariant despite changes on the controlled plant gain. In addition, the graphical nature of the proposed design approach demonstrates its portability and applicability to any type of vehicle dynamics without complex reconfiguration. The algorithm benefits are validated in frequency and time domains, as well as through experiments on a real vehicle platform performing adaptive cruise control.This research is supported by the Vehicle Technology Office (VTO), U.S. Department of Energy, under the Energy Efficient Mobility Systems (EEMS) initiative of the SMART Mobility Program, through the Lawrence Berkeley National Laboratory. The contents of this paper reflect the views of the authors, who are responsible for the facts and accuracy of the data presented herein

3d model identification of a soft robotic neck

Soft robotics is becoming an emerging solution to many of the problems in robotics, such as weight, cost and human interaction. In order to overcome such problems, bio-inspired designs have introduced new actuators, links and architectures. However, the complexity of the required models for control has increased dramatically and geometrical model approaches, widely used to model rigid dynamics, are not enough to model these new hardware types. In this paper, different linear and non-linear models will be used to model a soft neck consisting of a central soft link actuated by three motor-driven tendons. By combining the force on the different tendons, the neck is able to perform a motion similar to that of a human neck. In order to simplify the modeling, first a system input¿output redefinition is proposed, considering the neck pitch and roll angles as outputs and the tendon lengths as inputs. Later, two identification strategies are selected and adapted to our case: set membership, a data-driven, nonlinear and non-parametric identification strategy which needs no input redefinition; and Recursive least-squares (RLS), a widely recognized identification technique. The first method offers the possibility of modeling complex dynamics without specific knowledge of its mathematical representation. The selection of this method was done considering its possible extension to more complex dynamics and the fact that its impact in soft robotics is yet to be studied according to the current literature. On the other hand, RLS shows the implication of using a parametric and linear identification in a nonlinear plant, and also helps to evaluate the degree of nonlinearity of the system by comparing the different performances. In addition to these methods, a neural network identification is used for comparison purposes. The obtained results validate the modeling approaches proposed.Funding: The research leading to these results has received funding from the project Desarrollo de articulaciones blandas para aplicaciones robóticas, with reference IND2020/IND-1739, funded by the Comunidad Autónoma de Madrid (CAM) (Department of Education and Research), and from RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos, FaseIV; S2018/NMT-4331), funded by “Programas de Actividades I+D en la Comunidad de Madrid” and cofunded by Structural Funds of the EU

Design and performance validation of a cable-driven soft robotic neck

This paper has been presented at Jornadas Nacionales de Robótica 2018The purpose of this paper is to design a soft robotic neck prototype with two Degrees of Freedom (DOF). It is mainly aimed to investigate, study and design a mechanism that allows to simulate the movements of a human neck, concretely the movements of flexion, extension and lateral bending. To archieve these movements, the design is made based on a cable-driven mechanism, validating the design of spring, through which it will be possible to obtain the sketch of the components that make up the soft neck and then its manufacture in a 3D printer. Another important aspect for the development of the project is the load weight that the soft neck can support, in order to size the motors that are needed for the operation of the parallel mechanism. In addition, the analysis of its mathematical model for the control system that will be implemented in future work is carried out.The research leading to these results has received funding from the HUMASOFT project, with reference DPI2016-75330-P, funded by the Spanish Ministry of Economy and Competitiveness

A graphical tuning method for fractional order controllers based on iso-slope phase curves

Fractional order controllers are widely used in the robust control field. As a generalization of the ubiquitous PID controllers, fractional order controllers are able to reach design specifications their integer counterparts cannot, and as a result they outperform them at particular situations. Their main drawback is that generalization of the design tools is not always evident, and therefore tuning this kind of controller is always a new and different challenge. Existing methods often use numerical computation to find the controller parameters that fit the specifications. This paper describes a graphical solution for fractional order controllers, which avoids the solution by nonlinear equations and helps designer to solve the control problem in a very intuitive way. This approach is tested in the servomotors of a real bio-inspired soft neck and results are compared with those obtained from other control strategies. The experiments show that the controller tuned by this method works as expected from a robust controller and that this approach is very competitive compared to other state of the art methods, while offering a more simplified and direct tuning process.Research leading to these results has received funding from HUMASOFT project, with reference DPI2016-75330-P, funded by the Spanish Ministry of Economy and Competitiveness, and from RoboCity2030-DIH-CM Madrid Robotics Digital Innovation Hub, S2018/NMT-4331, funded by "Programas de Actividades I+D en la Comunidad de Madrid" and cofunded by Structural Funds of the EU

Modular and self-scalable origami robot: A first approach

This paper presents a proposal of a modular robot with origami structure. The proposal is based on a self-scalable and modular link made of soft parts. The kinematics of a single link and several links interconnected is studied and validated. Besides, the link has been prototyped, identified, and controlled in position. The experimental data show that the system meets the scalability requirements and that its response is totally reliable and robust.The research leading to these results has received funding from the project Desarrollo de articulaciones blandas para aplicaciones robóticas, with reference IND2020/IND-1739, funded by the Comunidad Autónoma de Madrid (CAM) (Department of Education and Research), and from RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos, FaseIV; S2018/NMT-4331), funded by “Programas de Actividades I+D en la Comunidad de Madrid” and cofunded by Structural Funds of the EU

SMA-driven soft robotic neck: design, control and validation

Replicating the behavior and movement of living organisms to develop robots which are better adapted to the human natural environment is a major area of interest today. Soft device development is one of the most promising and innovative technological fields to meet this challenge. However, soft technology lacks of suitable actuators, and therefore, development and integration of soft actuators is a priority. This article presents the development and control of a soft robotic neck which is actuated by a flexible Shape Memory Alloy (SMA)-based actuator. The proposed neck has two degrees of freedom that allow movements of inclination and orientation, thus approaching the actual movement of the human neck. The platform we have developed may be considered a real soft robotic device since, due to its flexible SMA-based actuator, it has much fewer rigid parts compared to similar platforms. Weight and motion noise have also been considerably reduced due to the lack of gear boxes, housing and bearings, which are commonly used in conventional actuators to reduce velocity and increase torque.This work was supported in part by the Spanish Ministry of Economy and Competitiveness through the Exoesqueleto para Diagnostico y Asistencia en Tareas de Manipulación Spanish Research Project under Grant DPI2016-75346-R and the HUMASOFT Project under Grant DPI2016-75330-P, in part by the Programas de Actividades I+D en la Comunidad de Madrid through the RoboCity2030-DIH-CM Madrid Robotics Digital Innovation Hub (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos, fase IV) under Grant S2018/NMT-4331, and in part by the Structural Funds of the EU

Iso-m based adaptive fractional order control with application to a soft robotic neck

This article proposes an adaptive fractional feedback control using recursive least squares algorithm for plant identification and a recent real-time method (iso-m) for fractional controller tuning. The combination of both methods allows keeping the same original performance specifications invariant, combining adaptability and robustness in a single scheme. Thanks to the robust controller, the system performance is maintained around a specified operating point, and due to the adaptive scheme, this operating point is adjusted depending on plant changes. Extensive experimentation of the proposal is carried out in a real platform with non-linear time varying properties, a soft robotic neck made of 3D printer soft materials. The experiments proposed consist in the neck inclination control using tilt sensors installed on the tip. According to expectations, an invariant performance despite plant parameter changes was observed throughout the experiments. The good results obtained in the proposed test platform suggest that the benefits of this control scheme are suitable for other nonlinear time varying applications.This work was supported in part by the Spanish Ministry of Economy and Competitiveness through the Exoesqueleto para Diagnostico y Asistencia en Tareas de Manipulación Spanish Research Project under Grant DPI2016-75346-R and the HUMASOFT Project under Grant DPI2016-75330-P, in part by the Programas de Actividades I+D en la Comunidad de Madrid, RoboCity2030-DIH-CM, through the Madrid Robotics Digital Innovation Hub (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos, Fase IV) under Grant S2018/NMT-4331, and in part by the Structural Funds of the EU

Robust control strategies based on fractional calculus for robotic platforms

Mención Internacional en el título de doctorThe proportional integral derivative feedback control is currently the most widely used system at industrial level, not just for simple systems, but also for highly complex ones, or even for new research developments. The main reason behind their widespread use is their simple implementation and the large number of available design tools. Only when it is strictly required, more advanced techniques such as robust, adaptive, predictive, or intelligent control are applied. In one way or another, all these advanced control systems have a common task: to achieve satisfactory results in the control of a system where classical techniques fail. One difficult problem to solve from a classical control point of view is uncertainty. The classic methods approach is based on some specifications and a model of the system to be controlled. This model, although it is considered to have some modeling error, is assumed to be invariable and correct. In other words, it is assumed to be certain. However, the reality is very different. At best, we can say that the system is invariant to some degree, and that the error is small enough. This lack of information about the system is known in the literature as uncertainty. One of the existing solutions to this problem comes from robust control, whose strategy is to design systems that are unaffected by plant variations, meaning that even with an inaccurate model, or with changing parameters, usually gain, the system response remains almost constant. Some examples of robust control are H-infinity control, sliding mode control or quantitative feedback theory. All these methods are complicated in both implementation and design, and therefore, are usually applied only when classical control fails. Halfway between the complexity of these methods and the simplicity of classical control is the fractional order control, based on the application of non-integer calculus to classical control methods. The great advantage of fractional order control compared to the previous methods consists in its close similarity to the classic control techniques, allowing many tools to be adapted from the classic control. Another great advantage compared to classic control is their great versatility, providing robust designs for a wide range of different plants. Naturally, fractional control also has its drawbacks. Firstly, the implementation of fractional order operators is more difficult than the integer ones, leading to a significant research effort, still growing, to find straightforward and reliable implementations. Secondly, the tuning of fractional order controllers involves the solution of non-linear equations, which normally requires high computational effort and added complexity. The problem of fractional controller tuning is addressed in this thesis in a novel way, seeking always simplicity in the calculations. The approach derives from a basic concept, followed by a mathematical analysis that provides simple but meaningful operations to calculate the parameters of the controller. Thanks to this approach, the solution can be found avoiding the use of numerical methods, while providing extensive information on the tuning process. The result is the formulation of a new tuning method that is swift and straightforward and avoids the limitations of the currently available methods. The excellent results obtained are coincident with other more complex solutions, but avoiding the use of numerical methods at all times. The precision and simplicity of the tuning method also allows an adaptive approach when a system identification algorithm is provided. Available alternatives in the field of fractional adaptive control are currently based on implicit adaptive techniques. The low computational cost of the new tuning method also makes explicit adaptive control possible, resulting in a robust control with an optimal operating point at all times. This solution, novel in the field of adaptive fractional control, allows a more complete solution to the uncertainty problems, since it combines the robustness of fractional order control with the flexibility of adaptive control. On the one hand, the robust controller prevents fast plant parameter changes to affect the system’s performance, as long as they are close to the operating point. On the other hand, the adaptive algorithm changes the operating point in case of a major variation in plant parameters. The key to this combination is that the fractional controller provides the time needed for adaptation, which is usually on the order of seconds, while maintaining the robustness of the system’s behavior. In addition, since the computational cost of the proposed methods is very low, their implementation on low-cost embedded platforms offers an amazing opportunity for the development and standardization of advanced control techniques. This in turn would allow the improvement of many current systems without the need of large equipment investment and the application of robust adaptive control to a much larger number of systems than those covered in the current landscape. The excellent results offered by both robust and adaptive fractional control methods are widely evidenced in the experimental part of this thesis through their application to several plants, including robotic joints, soft robotic links and autonomous vehicles.El control proporcional integral derivativo con realimentación es en la actualidad el sistema más usado a nivel industrial, no solo en sistemas sencillos, sino también en sistemas de gran complejidad, incluso en nuevos desarrollos de investigación. Este tipo de control es muy usado debido sobre todo a su sencilla implementación y al gran número de herramientas de diseño disponibles. Solo en caso de ser estrictamente necesario, se aplican técnicas mas avanzadas como el control robusto, adaptativo, predictivo, o inteligente. De una u otra forma, todos estos sistemas de control avanzado tienen una tarea en común: conseguir resultados satisfactorios en el control de un sistema cuando fallan las técnicas clásicas. Uno de los problemas con difícil solución desde un punto de vista clásico de control es el de la incertidumbre. El enfoque de los métodos clásicos es el del diseño en base a una serie de especificaciones y un modelo del sistema a controlar. Este modelo, aunque se considera que puede tener cierto error de modelado, se supone invariable y perfecto. Dicho de otro modo, se supone como cierto. Sin embargo, la realidad es muy distinta. En el mejor de los casos, podemos afirmar que el sistema es invariable hasta cierto punto, y que el error es suficientemente pequeño. Toda esta falta de información sobre el sistema se conoce en la literatura como incertidumbre. Una de las soluciones existentes a dicho problema es el control robusto, cuya solución pasa por diseñar sistemas imperturbables por las variaciones de la planta, de forma que, a pesar de que el modelo sea impreciso, o que los parámetros, normalmente la ganancia, cambien, la respuesta del sistema permanezca lo más invariable posible. Algunos ejemplos de control robusto son H-infinity control, sliding mode control o quantitative feedback theory. Todos estos métodos son más complicados tanto en la implementación como en el diseño, y por lo tanto, se aplican por lo general exclusivamente cuando el control clásico falla. A medio camino entre la complejidad de estos métodos y la simplicidad del control clásico se encuentra el control de orden fraccionario, basado en la aplicación del cálculo no entero a las técnicas de control clásico. La gran ventaja del control de orden fraccionario frente a las técnicas anteriores radica en su gran parecido con las técnicas clásicas de control, lo que permite que muchas de las herramientas disponibles se puedan adaptar desde el control clásico. La otra gran ventaja en comparación con el control clásico es su gran versatilidad, lo que permite realizar diseños robustos para muy diversos tipos de planta. Por supuesto, el control fraccionario también tiene sus desventajas. En primer lugar, la implementación de los operadores de orden fraccionario es más complicada que los de orden entero, lo que ha originado un gran esfuerzo de investigación, aún en auge, para encontrar implementaciones sencillas y fiables. Por otro lado, el ajuste de los controladores de orden fraccionario implica la solución de ecuaciones no lineales, lo que requiere normalmente de técnicas con un esfuerzo computacional elevado y una complejidad añadida. En esta tesis se trata el problema del ajuste del controlador fraccionario desde una forma novedosa, buscando en todo momento la simplicidad en los cálculos. La propuesta parte de un concepto sencillo, seguido de un desarrollo matemático que resuelve el cálculo de los parámetros del controlador mediante operaciones simples pero significativas. Gracias a este enfoque, la solución se plantea evitando el uso de métodos numéricos, a la vez que se ofrece abundante información sobre el proceso de ajuste. Esto permite el desarrollo de un nuevo método de ajuste rápido y sencillo que evita las desventajas de los métodos actualmente disponibles. Los resultados obtenidos son excelentes, coincidiendo en su solución con otros más complejos, pero evitando en todo momento el uso de métodos numéricos. La precisión y sencillez del método de ajuste permite además su aplicación en sistemas adaptativos en caso de disponer de un algoritmo de identificación de sistemas. Actualmente, las propuestas disponibles en el campo del control adaptativo fraccionario se basan en técnicas adaptativas implícitas. Dado el coste computacional mínimo del nuevo método de ajuste, el control adaptativo explícito también es posible, permitiendo el control robusto en un punto óptimo de operación en todo momento. Esta solución, de novedosa aplicación en el campo del control fraccionario adaptativo, permite una solución más completa a los problemas de incertidumbre, ya que une la robustez del control de orden fraccionario con la flexibilidad del control adaptativo. Por un lado, el controlador robusto permite que las variaciones rápidas en los parámetros de la planta no afecten al comportamiento del sistema, siempre que estén cerca del punto de operación. Por otra parte, el algoritmo de adaptación cambia el punto de operación en caso de una variación mayor en los parámetros de la planta. La clave de esta combinación está en que el controlador fraccionario proporciona el tiempo necesario para la adaptación, que suele ser del orden de segundos, mientras que mantiene la robustez en el comportamiento del sistema. Además, dado que el coste computacional de los métodos propuestos es muy reducido, su implementación en plataformas embebidas y de bajo coste ofrece una increíble oportunidad de desarrollo y estandarización de las técnicas avanzadas de control. Esto permitiría la mejora de muchos sistemas actuales sin la necesidad de una gran inversión en equipos y la aplicación del control adaptativo robusto a un número de sistemas mucho más amplio de los que se abordan en el panorama actual. Los excelentes resultados que ofrecen ambos métodos de control fraccionario robusto y adaptativo están ampliamente demostrados en la parte experimental de esta tesis mediante su aplicación en varias plantas, entre las que se encuentran articulaciones robóticas, eslabones robóticos blandos y vehículos autónomos.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Eduardo Rocon de Lima.- Secretario: Luis Santiago Garrido Bullón.- Vocal: Martin F. Stoele

A novel robust method for the elbow of the humanoid robot TEO based on a fractional order PD controller

Proceeding of: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 1-5, 2018, Madrid, SpainThis paper presents a novel method for the control of the elbow joint of the humanoid robot TEO, based on a fractional order PD controller. Due to the graphical nature of the proposed method, a few basic operations are enough to tune the controller, offering very competitive results compared to classic methods. The experiments show a robust performance of the system to mass changes at the tip of the humanoid right arm.The research leading to these results has received funding from the HUMASOFT project, with reference DPI2016-75330-P, funded by the Spanish Ministry of Economy and Competitiveness