Control of a DC motor using algebraic derivative estimation with real time experiments

This paper presents an experimental control scheme for DC motors which combines an overlapping implementation of the algebraic derivative estimation method and a disturbance estimator based on the aforementioned algebraic derivative method. The methodology only requires the measurement of the angular position of the motor and the voltage input to the motor. The main advantages of the proposed approach are: it is independent of the motor’s initial conditions, the methodology is robust to Coulomb friction effects, it does not require any statistical knowledge of the noises that corrupt the data, the derivative estimation process does not require initial conditions or dependence between the system input and output, and the algorithm is computed on-line and in real time. The effectiveness of the proposed controller has been verified by means of computer simulations and it has also been experimentally implemented on a laboratory prototype with excellent results in both, stabilization and trajectory tracking tasks

Adaptive PF (PDF) Speed Control for Servo Drives

This paper proposes two model reference adaptive PF (PDF) speed control methods for servo drives. Following from the structure (PF‐type) of model reference parameter adaptive control was developed to provide constant loop gain in speed control loop with changing gain (moment of inertia and/or torque factor) which makes it easier to reach nonovershooting step response as well as fast speed changing compensation caused by jump in load. The algorithm even keeps its stability at fast changing, jump‐like load torque. Model reference signal adaptive control is used to provide constant loop gain in speed control loop with changing parameters exposed to a significant load. The block diagram of the adaptive control can be seen as an extended version of the PF controller, so one of the adaptation factors (which is the free parameter of the adaptive control) is given. Both model reference adaptive controls drawn up can be easily implemented because the adaptation algorithms do not need acceleration measuring (thanks to the first‐order model). Simulation and experimental results demonstrate that the proposed methods are promising tools for speed control of electrical drives

Understanding and Design of an Arduino-based PID Controller

This thesis presents research and design of a Proportional, Integral, and Derivative (PID) controller that uses a microcontroller (Arduino) platform. The research part discusses the structure of a PID algorithm with some motivating work already performed with the Arduino-based PID controller from various fields. An inexpensive Arduino-based PID controller designed in the laboratory to control the temperature, consists of hardware parts: Arduino UNO, thermoelectric cooler, and electronic components while the software portion includes C/C++ programming. The PID parameters for a particular controller are found manually. The role of different PID parameters is discussed with the subsequent comparison between different modes of PID controllers. The designed system can effectively measure the temperature with an error of ± 0.6℃ while a stable temperature control with only slight deviation from the desired value (setpoint) is achieved. The designed system and concepts learned from the control system serve in pursuing inexpensive and precise ways to control physical parameters within a desired range in our laboratory

Learning and Reacting with Inaccurate Prediction: Applications to Autonomous Excavation

Motivated by autonomous excavation, this work investigates solutions to a class of problem where disturbance prediction is critical to overcoming poor performance of a feedback controller, but where the disturbance prediction is intrinsically inaccurate. Poor feedback controller performance is related to a fundamental control problem: there is only a limited amount of disturbance rejection that feedback compensation can provide. It is known, however, that predictive action can improve the disturbance rejection of a control system beyond the limitations of feedback. While prediction is desirable, the problem in excavation is that disturbance predictions are prone to error due to the variability and complexity of soil-tool interaction forces. This work proposes the use of iterative learning control to map the repetitive components of excavation forces into feedforward commands. Although feedforward action shows useful to improve excavation performance, the non-repetitive nature of soil-tool interaction forces is a source of inaccurate predictions. To explicitly address the use of imperfect predictive compensation, a disturbance observer is used to estimate the prediction error. To quantify inaccuracy in prediction, a feedforward model of excavation disturbances is interpreted as a communication channel that transmits corrupted disturbance previews, for which metrics based on the sensitivity function exist. During field trials the proposed method demonstrated the ability to iteratively achieve a desired dig geometry, independent of the initial feasibility of the excavation passes in relation to actuator saturation. Predictive commands adapted to different soil conditions and passes were repeated autonomously until a pre-specified finish quality of the trench was achieved. Evidence of improvement in disturbance rejection is presented as a comparison of sensitivity functions of systems with and without the use of predictive disturbance compensation

An improved equivalent force control algorithm for hybrid seismic testing of nonlinear systems

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Design of a Biaxial Test Device for Compliant Tissue

The objective of this project is to design and build a computer controlled testing system for planar biaxial stretching of soft connective tissues. The planar biaxial device designed in this paper has a four-axis control system as well as four components: a temperature-controlled testing chamber, a low friction sample attachment system, a stretching/force system, and a stress/strain measurement system. The device\u27s design is unique due to its low force capability (\u3c 0.5N), low cost (\u3c $15,000), and real-time computer control

Modeling and control of a pneumatic muscle actuator

This thesis presents the theoretical and experimental study of pneumatic servo position control systems based on pneumatic muscle actuators (PMAs). Pneumatic muscle is a novel type of actuator which has been developed to address the control and compliance issues of conventional cylindrical actuators. Compared to industrial pneumatic cylinders, muscle actuators have many ideal properties for robotic applications providing an interesting alternative for many advanced applications. However, the disadvantage is that muscle actuators are highly nonlinear making accurate control a real challenge. Traditionally, servo-pneumatic systems use relatively expensive servo or proportional valve for controlling the mass flow rate of the actuator. This has inspired the research of using on/off valves instead of servo valves providing a low-cost option for servo-pneumatic systems. A pulse width modulation (PWM) technique, where the mass flow is provided in discrete packets of air, enables the use of similar control approaches as with servo valves. Although, the on/off valve based servo-pneumatics has shown its potential, it still lacks of analytical methods for control design and system analysis. In addition, the literature still lacks of studies where the performance characteristics of on/off valve controlled pneumatic systems are clearly compared with servo valve approaches. The focus of this thesis has been on modeling and control of the pneumatic muscle actuator with PWM on/off valves. First, the modeling of pneumatic muscle actuator system controlled by a single on/off valve is presented. The majority of the effort focused on the modeling of muscle actuator nonlinear force characteristics and valve mass flow rate modeling. A novel force model was developed and valve flow model for both simulation and control design were identified and presented. The derived system models (linear and nonlinear), were used for both control design and utilized also in simulation based system analysis. Due to highly nonlinear characteristics and uncertainties of the system, a sliding mode control (SMC) was chosen for a control law. SMC strategy has been proven to be an efficient and robust control strategy for highly nonlinear pneumatic actuator applications. Different variations of sliding mode control, SMC with linear model (SMCL) and nonlinear model (SMCNL) as well as SMC with integral sliding surface (SMCI) were compared with a traditional proportional plus velocity plus acceleration control with feed-forward (PVA+FF) compensation. Also, the effects of PWM frequency on the system performance were studied. Different valve configurations, single 3/2, dual 2/2, and servo valve, for controlling a single muscle actuator system were studied. System models for each case were formulated in a manner to have a direct comparison of the configuration and enabling the use of same sliding mode control design. The analysis of performance included the sinusoidal tracking precision and robustness to parameter variations and external disturbances. In a similar manner, a comparison of muscle actuators in an opposing pair configuration controlled by four 2/2 valves and servo valve was executed. Finally, a comparison of a position servo realized with pneumatic muscle actuators to the one realized with traditional cylinder was presented. In these cases, servo valve with SMC and SMCI were used to control the systems. The analysis of performance included steady-state error in point-to-point positioning, the RMSE of sinusoidal tracking precision, and robustness to parameter variations

Modeling and control of a pneumatic muscle actuator

This thesis presents the theoretical and experimental study of pneumatic servo position control systems based on pneumatic muscle actuators (PMAs). Pneumatic muscle is a novel type of actuator which has been developed to address the control and compliance issues of conventional cylindrical actuators. Compared to industrial pneumatic cylinders, muscle actuators have many ideal properties for robotic applications providing an interesting alternative for many advanced applications. However, the disadvantage is that muscle actuators are highly nonlinear making accurate control a real challenge. Traditionally, servo-pneumatic systems use relatively expensive servo or proportional valve for controlling the mass flow rate of the actuator. This has inspired the research of using on/off valves instead of servo valves providing a low-cost option for servo-pneumatic systems. A pulse width modulation (PWM) technique, where the mass flow is provided in discrete packets of air, enables the use of similar control approaches as with servo valves. Although, the on/off valve based servo-pneumatics has shown its potential, it still lacks of analytical methods for control design and system analysis. In addition, the literature still lacks of studies where the performance characteristics of on/off valve controlled pneumatic systems are clearly compared with servo valve approaches. The focus of this thesis has been on modeling and control of the pneumatic muscle actuator with PWM on/off valves. First, the modeling of pneumatic muscle actuator system controlled by a single on/off valve is presented. The majority of the effort focused on the modeling of muscle actuator nonlinear force characteristics and valve mass flow rate modeling. A novel force model was developed and valve flow model for both simulation and control design were identified and presented. The derived system models (linear and nonlinear), were used for both control design and utilized also in simulation based system analysis. Due to highly nonlinear characteristics and uncertainties of the system, a sliding mode control (SMC) was chosen for a control law. SMC strategy has been proven to be an efficient and robust control strategy for highly nonlinear pneumatic actuator applications. Different variations of sliding mode control, SMC with linear model (SMCL) and nonlinear model (SMCNL) as well as SMC with integral sliding surface (SMCI) were compared with a traditional proportional plus velocity plus acceleration control with feed-forward (PVA+FF) compensation. Also, the effects of PWM frequency on the system performance were studied. Different valve configurations, single 3/2, dual 2/2, and servo valve, for controlling a single muscle actuator system were studied. System models for each case were formulated in a manner to have a direct comparison of the configuration and enabling the use of same sliding mode control design. The analysis of performance included the sinusoidal tracking precision and robustness to parameter variations and external disturbances. In a similar manner, a comparison of muscle actuators in an opposing pair configuration controlled by four 2/2 valves and servo valve was executed. Finally, a comparison of a position servo realized with pneumatic muscle actuators to the one realized with traditional cylinder was presented. In these cases, servo valve with SMC and SMCI were used to control the systems. The analysis of performance included steady-state error in point-to-point positioning, the RMSE of sinusoidal tracking precision, and robustness to parameter variations

Robust Stabilization of Elastic Joint Robots by ESP and PID Control: Theory and Experiments

This work addresses the problem of global set-point control of elastic joint robots by combining elastic structure preserving (ESP) control with non-collocated integral action. Despite the popularity and extensive research on PID control for rigid joint robots, such schemes largely evaded adoption to elastic joint robots. This is mainly due to the underactuation inherent to these systems, which impedes the direct implementation of PID schemes with non-collocated (link position) feedback. We remedy this issue by using the recently developed concept of “quasi-full actuation,” to achieve a link-side PID control structure with “delayed” integral action. The design follows the structure preserving design philosophy of ESP control and ensures global asymptotic stability and local passivity of the closed loop. A key feature of the proposed controller is the switching logic for the integral action that enables the combination of excellent positioning accuracy in free motion with compliant manipulation in contact with the environment. Its performance is evaluated on an elastic joint testbed and a compliant robot arm. The results demonstrate that elastic robots may achieve positioning accuracy comparable to rigid joint robots