Fastcat: An Open-Source Library for Composable EtherCAT Control Systems

Design of a digital adaptive algorithm for torque-controlled robotic joints

Trajectory control of a hydraulic system using intelligent control approach based on adaptive prediction model

Precise and stable trajectory tracking in mobile robotics is challenging due to dynamic disturbances and uncertain conditions. Traditional controllers like P-D and PID often underperform in non-linear, unpredictable environments. They also lack the adaptability needed for real-time, vision-based control systems. To address these issues, this paper explores and compares the effectiveness of three control approaches: P-D, PID, and a Fractional Order PID (FOPID) controller optimized using the World Cup Optimization Algorithm (WCOA). The control system is driven by inputs from a computer vision setup, and the controllers are evaluated on their ability to maintain accurate setpoint tracking under simulated dynamic disturbances. The FOPID controller’s parameters are tuned using WCOA, enhancing its adaptability and precision. The robustness of WCOA is also validated using standard benchmark functions including Sphere, Rastrigin, Ackley, Rosenbrock, and Griewank. Simulation results show that the WCOA-tuned FOPID controller significantly outperforms both P-D and PID controllers in minimizing error, maintaining control stability, and ensuring accurate trajectory tracking. Its superiority is also demonstrated through real-time tests on a mobile robot. Furthermore, feasibility evaluations reveal high levels of usability, operability, and learnability. These results highlight the strong potential of WCOA as a robust optimization method for advanced control systems and provide a foundation for future research in dynamic environments, hybrid optimization techniques, and broader engineering applications.

This paper presents a real-time implementation of a genetic-based hybrid fuzzy-PID controller for industrial motor drives. Both the design of fuzzy-PID controller and its integration with the conventional PID in global control system to produce a hybrid design is demonstrated. A genetic optimization technique is used to determine the optimal values of the scaling factors of the output variables of the fuzzy-PID controller. The objective is to utilize the best attributes of the PID and fuzzy-PID controllers to provide a controller, which will produce better response than either the PID or the fuzzy-PID controller. The principle of the hybrid controller is to use a PID controller, which performs satisfactorily in most cases, while keeping in the background, a fuzzy-PID controller, which, is ready to take over the PID controller when severe disturbs occur. The hybrid controller is formulated and implemented in real-time, using the speed control of a brushless drive system as a testbed. The design, analysis, and implementation stages are carried out entirely using a dSPACE DS1104 digital signal processor (DSP)-based real-time data acquisition control (DAC) system, and MATLAB/Simulink environment. Experimental results show that the proposed fuzzy- PID controller-based genetic optimization produces better control performance than the conventional PID controllers, particularly in handling nonlinearities and external disturbances.

This paper aimed on showing how efficient a Fuzzy-PID controller can control the speed and vibration of an Induction motor and how it can replace the conventional PID controllers. This testing is performed in MATLABSimulink software. The three phase Induction motor’s transfer function is framed and the PID controller values are auto-tuned. The output of PID and Fuzzy-PID Inference system controller show the Speed-Time waveforms. From these waveforms, the properties can be found leading to the conclusion which helps us decide which control system is efficient over the other. Wave properties such as rise-time, peak time, settling time and maximum overshoot values of the control systems are calculated and tabulated. The end comparative results show us that the Fuzzy-PID Inference system has better and safe wave characteristics compared to PID controller. This way Fuzzy-PID controller is much preferred and safe in the long run compared to PID controllers.

Although the traditional PID controller is widely used in many fields, the system parameters varying and external disturbances existing in the DC servo system will cause large overshoot or poor stability. To improve the performance of the PID controller, a compound servo control system combining the conventional PID control and the fuzzy control is presented to meet the demand of a vehicular antenna servo system in this paper. Incorporating the fuzzy control and the conventional PID control, this paper presents a design method of the fuzzy PID controller that is based on the fuzzy tuning rules and formed by integrating two above control ideas. Simulation results are presented to show the efficiency of the proposed controller. The practical control effect shows that the control system that adopts the fuzzy PID controller has better performance than that of the traditional PID control system, and meets the performance requirements of the servo system.

We examined the patterns of joint kinematics and torques in two kinds of sagittal plane reaching movements. One consisted of movements from a fixed initial position with the arm partially outstretched, to different targets, equidistant from the initial position and located according to the hours of a clock. The other series added movements from different initial positions and directions and >40-80 cm distances. Dynamic muscle torque was calculated by inverse dynamic equations with the gravitational components removed. In making movements in almost every direction, the dynamic components of the muscle torques at both the elbow and shoulder were related almost linearly to each other. Both were similarly shaped, biphasic, almost synchronous and symmetrical pulses. These findings are consistent with our previously reported observations, which we termed a linear synergy. The relative scaling of the two joint torques changes continuously and regularly with movement direction. This was confirmed by calculating a vector defined by the dynamic components of the shoulder and elbow torques. The vector rotates smoothly about an ellipse in intrinsic, joint torque space as the direction of hand motion rotates about a circle in extrinsic Cartesian space. This confirms a second implication of linear synergy that the scaling constant between the linearly related joint torques is directionally dependent. Multiple linear regression showed that the torque at each joint scales as a simple linear function of the angular displacement at both joints, in spite of the complex nonlinear dynamics of multijoint movement. The coefficients of this function are independent of the initial arm position and movement distance and are the same for all subjects. This is an unanticipated finding. We discuss these observations in terms of the hypothesis that voluntary, multiple degrees of freedom, rapid reaching movements may use rule-based, feed-forward control of dynamic joint torque. Rule-based control of joint torque with separate dynamic and static controllers is an alternative to models such as those based on the equilibrium point hypotheses that rely on a positionally based controller to produce both dynamic and static torque components. It is also an alternative to feed-forward models that directly solve the problems of inverse dynamics. Our experimental findings are not necessarily incompatible with any of the alternative models, but they describe new, additional findings for which we need to account. The rules are chosen by the nervous system according to features of the kinematic task to couple muscle contraction at the shoulder and elbow in a linear synergy. Speed and load control preserves the relative magnitudes of the dynamic torques while directional control is accomplished by modulating them in a differential manner. This control system operates in parallel with a positional control system that solves the problems of postural stability.

Researching optimization problems of controller is need of industrial process control ,in which PID controller is widely used,which its parameters can be equivalent to optimization problems. In the industrial control the PID controller is widely used in excitation control system to improve its control performance.In order to find the optimal PID controller parameters effectively ,a kind of Adaptive Particle Swarm Optimization method (CAPSO) based on Cloud Theory is applied to fuzzy PID controller. Through the establishment of particle swarm algorithm of fuzzy PID controller parameters optimization model, which it can be used to optimize the membership function of fuzzy PID controller. Particle code adopts real coding. Particle dimension is related with the number of the input variables divided by fuzzy set and the number of control rules of whole fuzzy control system, thus the parameters of PID control are optimized on real time. The result from the simulation shows that compared with PID control and fuzzy control this system has several advantages which are small overshoots ,fast response ,and good stable performance to improve the control performance of excitation control system.

We propose a communication architecture for EtherCAT master motivated by the technological progress in IT systems and Industrial Ethernet in control systems. In the proposed method, a dedicated hardware named the EtherCAT accelerator offers virtualized real-time and IT communication channels by operating automatic control frame generation, time synchronization protocol, and transmission scheduling of frames based on synchronized time. Using the EtherCAT accelerator enables highly accurate cyclic communications under IT communications such as IP. We prototyped the proposed architecture on a field programmable gate array (FGPA) as hardware and Linux as software. The results show that the master can transmit 64-byte packets in a 30 µs cycle synchronized to an EtherCAT network with less than 1 µs accuracy.

Generally Quad-rotor type Unmanned Aerial Vehicles are unstable in nature, so to stabilize it, attitude controller is used. This paper presents a Fuzzy Logic based PID control system (FPID) for attitude stabilization of Quad-rotor Unmanned Aerial Vehicle (UAV). The Fuzzy logic controller updates the PID controller gains efficiently in such a way that it efficiently stabilizes the attitude of quad-rotor UAV. This method enhances the capabilities of conventional PID Controller to a dynamic PID Controller. The propose FPID control technique for attitude controlling of Quad-rotor UAV was tested on developed prototype of Quad rotor UAV for experimental purpose. Experimental results proved that proposed Fuzzy Logic based PID (FPID) controller quickly stabilized Quad-rotor UAV and its response time and settling time is reasonably good in attitude stabilization control application.

Spinal cord injuries severely change the life of affected people. Besides major brain reorganizations following the de-afferentiation of affected limbs, the resulting immobility is a major problem affecting life quality and self-efficacy. In tetraplegia, which is the paralysis of all four limbs, mobility is especially challenging. With traditional control interfaces, such as chin or head control and sip-and-puff controllers, 50% of individuals with tetraplegia find it hard or impossible to perform even simple wheelchair tasks. Drawbacks of these systems include complicated use in daily-life and severe interference with other important activities (e.g. communication or head orientation). Since these control systems depend on the integrity of dedicated functions (e.g. control over the diaphragm for sip-and-puff, over neck muscles for chin control) individuals with tetraplegia are often even left without options for control of assistive devices. Novel experimental control systems that are operated with the tongue or by sniffing are promising, but still interfere with other activities. In order to address this problem, we have developed an EMG-based novel control option, which is operated with the posterior auricular muscles (PAM). These small muscles behind the ear are especially suited for myoelectric control, because they comply with three prerequisites: first, because they are innervated by the facial nerve, they are still available in a number of sever neurological impairments, including spinal cord injuries. Second, unlike other facial muscles, the auricular muscles in humans are not involved in any relevant motor function, which secures minimal interference with other activities (e.g. facial movements, talking). Third, the isolated position of the posterior auricular muscle (PAM) ensures good accessibility and minimal crosstalk, rendering it particularly suitable for a myoelectric control interface. In this thesis, I will present first proof-of-principles of the suitability of the auricular muscles as a signal generator for rehabilitation devices. We then used the developed system to address neuronal plasticity from a new perspective. In the first study, ten healthy subjects and two subjects with tetraplegia were trained for five consecutive days. For the first time, it was shown with several parameters that subjects are able to learn to activate their auricular muscles. With appropriate training, they were able to produce fine graded activations and achieve bilateral distinction, i.e. only activate one side. This ability is important for wheelchair driving, and accordingly, all subjects were able to control an electric wheelchair with their auricular muscles on the fifth training day. In the second study, the control system was applied to another rehabilitation device, an arm prosthesis. The conventional myoelectric control scheme is robust and easy to use, but does not allow for simultaneous activation of e.g. opening and turning the prosthetic hand. The combination of the auricular system with a forearm EMG system solves this problem. It was tested with 10 healthy subjects and one subject with arm amputation. Without training, the hybrid auricular control system was significantly faster and more accurate than two other established myoelectric control modes in an established test. The third study aimed to exploit the potentials of the control system in a longer testing time. Nine tetraplegic subjects were trained in auricular control of an electric wheelchair for two weeks. Additionally, we aimed to investigate motor training effects on the brain reorganization that has been observed in SCI subjects. Subjects underwent fMRI and TMS measuring before and after training. We found significant improvements of the driving abilities with the electric wheelchair in complex tasks. Importantly, we found excessive motor task related brain activation, that has been suggested as maladaptive in the literature. Data indicates that it is on the contrary a phenomenon that enhances motor performance. Nevertheless, we show for the first time that it can be reduced through training, indicating a normalization of brain activity. These novel findings have important implications for physical rehabilitation of individuals with SCI. In conclusion, the results of this thesis provide several new insights about the auricular muscles, e.g. that voluntary activation can be learned and trained, and that they are appropriate for fine-tuned signal generation. The auricular control system has several advantages over other control systems, e.g. continuous and proportional signal generation. Results show that the application of this control system to different rehabilitation devices is easy and performance results are promising. Importantly, results provide new information about brain reorganization after SCI. Training of the auricular muscles can reduce over-activation of motor related cortex areas in tetraplegic subjects, which has been suggested to be maladaptive.

Present paper attempts to review the literature related to design of P-I-D control for time delayed complex industrial process for single as well as for multivariable process with interaction considerations, their decoupler design and time delay compensators. General instrumentation of the industrial feedback control systems along with control system analysis has been covered. Also it covers, control features of some paper mill sub-processes like headbox operation, basis weight and retention. The importance of eliminating the effects of interactions, among the process control loops inside a multi input multi output industrial control system, has been discussed with the help of literature study. The importance of the process dynamics knowledge for designing a control system has also been investigated. This paper also investigates the significance and effectiveness of PID controllers through various literature studies. The problems of the classical PID controllers such as constraints, presence of disturbances etc.) can be removed by designing in combination with soft computing techniques. Moreover, possibility of further enhancements in the PID controller with the utilization of various schemes available, has been presented. The present status of control systems in industrial processes in terms of various control parameters such as stability, dead time compensation etc. has been presented and the future improvements have been stated.

The Advanced Concepts Office (ACO) at Marshall Space Flight Center (MSFC) has conducted ongoing studies and trades into options for both hybrid and solid vehicle systems for potential Mars Ascent Vehicle (MAV) concepts for the Jet Propulsion Laboratory (JPL). Two MAV propulsion options are being studied for use in a potential Mars Sample Retrieval (MSR) campaign. The following paper describes the current concepts for hybrid and solid propulsion vehicles for MAV as part of a potential MSR campaign, and provides an overview of the ongoing studies and trades for both hybrid and solid vehicle system concepts. Concepts and options under consideration for vehicle subsystems include reaction control system (RCS), separation, and structures will be described in terms of technology readiness level (TRL), benefit to the vehicle design, and associated risk. A hybrid propulsion system, which uses a solid fuel core and liquid oxidizer, is currently being developed by JPL with support from MSFC. This type of hybrid propulsion vehicle would allow the MAV to be more flexible at the cost of higher complexity, in contrast to the solid propulsion vehicle that is simpler, but allows less flexibility. The solid propulsion vehicle study performed by MSFC in 2018 further refined the solid propulsion system sizing as well as added definition to vehicle subsystem concepts, including the RCS, structures and configuration, interstage and separation, aerodynamics, and power/avionics. The studies were performed using an iterative concept design methodology, engaging subject matter experts from across MSFC's propulsion and vehicle systems disciplines as well as seeking trajectory feedback from analysts at JPL.

It is difficult for greenhouse to control temperature since it is usually of such characteristics as big inertia and big lag.Therefore,Fuzzy PID control was introduced into the system.Fuzzy PID control algorithm was used to design temperature control system according to the season of a year and the section of a day.By simulation and comparison with Fuzzy PID and general control,this paper concludes that the use of the method in the system can greatly improve the robustness and self-adaptability of the system.It can save energy and improve economic benefit.

Fractional order PID, which involve integration and differentiation of non-integer order, is increasingly being used in the fields of control system, robotics, signal processing and circuit theory. Based on neural network, this paper introduce a new approach for design fractional order PID controller. A self-learning PID controller with five dimension parameters is realized by using parameter turning strategy of RBF neural network. Further apply the fractional order PID controller to a typical FOLPD process like pulp consistency control system. In particular, pulp consistency system is a typical FOLPD process. The simulation results show that this kind of controller has a better effect for pulp consistency system than traditional PID and PIDNN controller.