Reinforcement Learning Adaptive PID Controller for an Under-actuated Robot Arm

Abstract: An adaptive PID controller is used to control of a two degrees of freedom under actuated manipulator. An actor-critic based reinforcement learning is employed for tuning of parameters of the adaptive PID controller. Reinforcement learning is an unsupervised scheme wherein no reference exists to which convergence of algorithm is anticipated. Thus, it is appropriate for real time applications. Controller structure and learning equations as well as update rules are provided. Simulations are performed in SIMULINK and performance of the controller is compared with NARMA-L2 controller. The results verified good performance of the controller in tracking and disturbance rejection tests

Novi mehanizam za pasivno-dinamičnu manipulaciju objektom duž zakrivljenog puta

Object manipulation is a basic task in robotics and automation. Active manipulation by grasp is conventional approach in object manipulation. However, in many cases, grasp-less manipulation can be beneficial in terms of cost, minimalism and extension of workspace. On the other hand passive mechanisms are advantageous from the energy saving viewpoint. In this paper we combine these ideas to develop a dynamic passive object manipulation mechanism to achieve manipulation in more than one dimension and simultaneously change position and orientation of the object. In developed mechanism the manipulation platform is a simple inclined surface. The object is composed of two wheels with different radiuses and an axle connecting the wheels to each other. The object moves passively along a circular path on the platform. Kinematic equations of the motion are devised, dynamic analyses are performed and no-slippage conditions are extracted. Modelling in CATIA and simulations in MSC.ADAMS are performed and experimental set up is built to verify the analysis.Manipulacija objektom je osnovni zadatak u robotici i automatici.Aktivna manipulacija hvatom predstavlja konvencionalan prostup manipulaciji objektom. Ipak, u mnogim slučajevima, manipulacija objektom bez hvata može biti korisna u smislu troškova, minimalizma i proširenja radnom prostora.S druge strane, pasivni mehanizmi posjeduju prednosti iz perspektive uštede energije. U ovom radu mi kombiniramo ove ideje kako bismo razvili dinamično-pasivni mehanizam za manipulaciju objektom u svrhu postizanja manipulacije u više od jedne dimenzije i simultano mijenjali poziciju i orijentaciju objekta. U razvijenom mehanizmu platforma za manipulaciju sastoji se od jednostavne nagnute plohe. Objekt se sastoji od dvaju kotača različitih radijusa i jedne osi koja spaja kotače. Objekt se kreće pasivno duž zakrivljenog puta na platformi.Postaljene su jednadžbe kinematike gibanja, te je analizirana dinamika, dok je klizanje zanemareno. U svrhu verifikacije analize izrađen je model eksperimentalnog postava u CATIA-i te su provedene simulacije korištenjem MSC.ADAMS alata

Multi-agent Optimal Control of Ball Balancing on a Mobile

Multi-agent systems have origin in computer engineering however, they have found applications in different field. One of the newly emerged problems in multi-agent systems is multi-agent control. In multi-agent control it is desired that the control is done in distributed manner. That is the controller of each agent should be implemented based on local feedback. In this a mechanism is introuded as a test bed for multi-agent control systems. The introduced mechanism is balancing of a ball on link located on a planar mobile robot. Dynamic equations of the mechanism is derived and the control task is distributed among two agents. For each agent a two loop controller designed wherein external loop is a LQR controller and inner loop is a simple proportional controller. Regulation and fault tolerance performance of controller scheme is evaluated by simulations

Inteligentno upravljanje paralelnim robotom sa šest stupnjeva slobode korištenim za rehabilitaciju donjih udova

The process of empowering muscles in order to make them to a normal and common value is an expensive and prolonged work, in common available methods. There are some commercial exercise machines used for this purpose called rehabilitation systems. However, due to their insufficient motion freedom and prospect of being expensive, these machines have limited usage. Hence, it is clearly necessary that Mechatronic technologies should be used in this area. In this paper, an algorithm and an improved rule are presented for controlling a rehabilitation system of lower limbs which is implemented on a 6-Degree Of Freedom (DOF) Stewart parallel robot. Impedance control and adaptive control are used for this purpose. Estimation and optimization of control parameters will be done by artificial neural networks and genetic algorithms, respectively (intelligent strategy). Safety is guaranteed since some of controller parameters can be adapted under the stability conditions given by using Routh stability theory. Thereafter, the results of simulations are presented by defining a physiotherapy standard mode on a desired trajectory. MATLAB/SIMULINK is used for simulations. Finally, a comparative discussion between this strategy and common methods is devised.Proces osposobljavanja mišića za normalne funkcije je skup i dugotrajan uz korištenje dostupnih metoda. Postoje komercijalni strojevi za tu svrhu koji se nazivaju sustavi za rehabilitaciju. Zbog njihove nedostatne slobode pokreta i visoke cijene takvi strojevi imaju ograničenu upotrebu. Stoga je jasno da je u području rehabilitiacije potrebno koristiti mehatroničke sustave. U ovom radu prikazan je algoritam i poboljšano pravilo za upravljanje rehabilitacijskog sustava za donje udove koji je implementiran na Stewart paralelnom robotu sa šest stupnjeva slobode. Pritom je korišteno upravljanje impedancijom i adaptivno upravljanje. Za estimaciju i optimiranje parametara upravljanja koriste se neuronske mreže i genetički algoritmi. Sigurnost je garantirana jer se neki parametri regulatora adaptiraju prema uvjetima stabilnosti koji su dobiveni korištenjem Ruthove teorije stabilnosti. Nakon toga, rezultati simulacija prikazani su definiranjem standardnog fizioterapijskog rada na željenoj trajektoriji. Za simulacije se koristi MATLAB/SIMULINK. Konačno, u radu je dana i usporedba predložene strategije s uobičajenim metodama

FORECASTING OF TECHNICAL CONDITION PARAMETERS FOR COMPLEX ELECTROMECHANICAL SYSTEMS

Estimation of technical condition parameters for complex electromechanical systems

General method for state-space modeling and nonlinear control of single-phase cascaded multilevel inverters with LCL coupling

Due to the nonlinear behavior of grid-connected cascaded multilevel inverters (GCCMI), the use of nonlinear controllers can guarantee system stability over a wide range of operation. Therefore, state-space modeling is required to design nonlinear controllers. In this manuscript, a comprehensive method is proposed for the general state-space modeling of an n-level GCCMI with LCL coupling. To validate the accuracy of obtained state-space model, an experimental setup of a cascaded multilevel inverter including two H-bridges has been implemented. The outputs of the state-space model are compared with the simulation and experimental results of the GCCMI. This shows that the proposed model is compatible with a real closed-loop system. The simulations were performed using EMTDC/PSCAD software. In the following, the designed general model is used to develop a nonlinear controller based on the Lyapunov stability criteria for a multilevel shunt active power filter (SAPF). Results show that the designed controller is stable and robust in a wide range of operating point changes

Optimal Trajectory Planning of a Box Transporter Mobile Robot

This paper aims to discuss the requirements of safe and smooth trajectory planning of transporter mobile robots to perform non-prehensile object manipulation task. In non-prehensile approach, the robot and the object must keep their grasp-less contact during manipulation task. To this end, dynamic grasp concept is employed for a box manipulation task and corresponding conditions are obtained and are represented as a bound on robot acceleration. A trajectory optimization problem is defined for general motion where dynamic grasp conditions are regarded as constraint on acceleration. The optimal trajectory planning for linear, circular and curve motions are discussed. Optimization problems for linear and circular trajectories were analytically solved by previous studies and here we focused with curve trajectory where Genetic Algorithm is employed as a solver tool. Motion simulations showed that the resulted trajectories satisfy the acceleration constraint as well as velocity boundary condition that is needed to accomplish non-prehensile box manipulation task

Autonomous energy management system with self-healing capabilities for green buildings (microgrids)

Nowadays, distributed energy resources are widely used to supply demand in micro grids specially in green buildings. These resources are usually connected by using power electronic converters, which act as actuators, to the system and make it possible to inject desired active and reactive power, as determined by smart controllers. The overall performance of a converter in such system depends on the stability and robustness of the control techniques. This paper presents a smart control and energy management of a DC microgrid that split the demand among several generators. In this research, an energy management system ( EMS) based on multi-agent system ( MAS) controllers is developed to manage energy, control the voltage and create balance between supply and demand in the system with the aim of supporting the reliability characteristic. In the proposed approach, a reconfigurated hierarchical algorithm is implemented to control interaction of agents, where a CAN bus is used to provide communication among them. This framework has ability to control system, even if a failure appears into decision unit. Theoretical analysis and simulation results for a practical model demonstrate that the proposed technique provides a robust and stable control of a microgrid

Autonomous energy management system with self-healing capabilities for green buildings (microgrids)

Nowadays, distributed energy resources are widely used to supply demand in micro grids specially in green buildings. These resources are usually connected by using power electronic converters, which act as actuators, to the system and make it possible to inject desired active and reactive power, as determined by smart controllers. The overall performance of a converter in such system depends on the stability and robustness of the control techniques. This paper presents a smart control and energy management of a DC microgrid that split the demand among several generators. In this research, an energy management system ( EMS) based on multi-agent system ( MAS) controllers is developed to manage energy, control the voltage and create balance between supply and demand in the system with the aim of supporting the reliability characteristic. In the proposed approach, a reconfigurated hierarchical algorithm is implemented to control interaction of agents, where a CAN bus is used to provide communication among them. This framework has ability to control system, even if a failure appears into decision unit. Theoretical analysis and simulation results for a practical model demonstrate that the proposed technique provides a robust and stable control of a microgrid

Robust Cooperative Controller for Output Regulation in Multi- Robot Systems

In this paper a robust cooperative multi-agent controller is designed for a linear uncertain multi-robot system with a nonlinear exosystem. Multi-robot system is divided into two subsystems; the first group of subsystems can be associated with the leader while the second group has no leader. Assuming that all agents are similar and have the same dynamics and decentralized control, state and output feedback control rules are proposed. Multi-robot system with nonlinear exosystem is simulated in MATLAB and tracking performances with state and output feedback controllers are investigated