Analysis of pulse width modulation controlled systems based on a piecewise affine description

In this paper, a surge speed tracking problem for an unmanned surface vehicle (USV) driven by a direct current (DC) motor is investigated. The surge velocity tracking controller is developed based on a modular neural dynamic surface control (MNDSC) design method. Specifically, two neural-network-based identifiers are designed to identify the uncertainties existing in surge dynamics, propeller and DC motor. Then, a robust adaptive surge speed controller based on a dynamic surface control design method is designed by using the recovered unknown information from identifiers. The proposed surge velocity tracking controller is able to track any time-varying bounded velocity profiles. The stability of the closed-loop system is established based on cascade theory and input-to-state stability (ISS) theory. The effectiveness of the proposed surge speed controller for the USV is illustrated via simulations.

The speed control of direct current (DC) motor for various applications is very important. In particular requirement, setting a speed DC motor as the driving equipment must be performed remotely. Under that condition, conducted a research on a DC motor speed control with pulse width modulation (PWM) method of the infrared remote control. PWM is method that may be used as a efficient DC motor speed control. Controller used TV remote control to send data to ATmega16 microcontroller through the IR receiver. This command controls the L293D driver IC to control the direction and speed of a DC motor. To calculate the speed of a DC motor, perforated disk attached to the motor shaft is used and placed between the photodiode as a sensor and the LED. The results of the research are the direction and speed of a DC motor can be set from the infrared remote control with PWM method using ATmega16 microcontroller. Furthermore, the results of these settings can be displayed on the LCD every 7 seconds.

Although brushed direct current (DC) motors have given way to brushless DC motors for many high-performance applications, brushed DC motors still dominate cost-sensitive markets. For applications that require closed-loop speed control, a speed measurement method with a high frequency update rate is necessary. With cost being a significant constraint, complicated algorithms or large windowing operations are not feasible for these types of systems. This paper proposes two sensorless methods for detecting the speed of a brushed DC motor at up to 18,000 RPM.The first method utilizes a current ripple component detection method at low speeds to calibrate the motor constant. Once the motor constant is calibrated, it transitions to a back electromotive force (BEMF) measurement method for operation. The BEMF method is automatically calibrated by the current ripple method, such that no motor parameterization is required. This method is suitable for 8-bit microcontrollers running at clock frequencies of at least 8 MHz. The system was implemented and tested using a low cost ATMega328P eight-bit microcontroller. The average open-loop relative error of this speed measurement method was 3.11%.The second method utilizes the current ripple component detection exclusively. However, this method requires a 32-bit microcontroller running at 64 MHz. The average open-loop relative error of this method was 1.94%.

This paper proposes a photovoltaic (PV) string-level isolated DC–DC power optimizer with wide voltage range. A hybrid control scheme in which pulse frequency modulation (PFM) control and pulse width modulation (PWM) control are combined with a variable switching frequency is employed to regulate the wide PV voltage range. By adjusting the switching frequency in the above region during the PWM control process, the circulating current period can be eliminated and the turn-on period of the bidirectional switch of the dual-bridge LLC (DBLLC) resonant converter is reduced compared to that with a conventional PWM control scheme with a fixed switching frequency, resulting in better switching and conduction loss. Soft start-up control under a no-load condition is proposed to charge the DC-link electrolytic capacitor from 0 V. A laboratory prototype of a 6.25 kW DBLLC resonant converter with a transformer, including integrated resonant inductance, is built and tested in order to verify the performance and theoretical claims.

Direct current (DC) motors are widely used because of their easily controllable and reliable access. DC motors have many salient features that includes a wide range of torque speed control, reliable operation with greater efficiency and a greater starting torque and many more. A nonlinear model for a DC motor can be represented for considering all uncertainties and non-linearities. In this paper, DC motor is studied which is having a second order system. Many controllers are being used for controlling speed of DC motor. An analysis is carried out on mathematical model of DC motor whose field is excited by an external or separate supply. Tuning of FOPID parameters using Ant Colony Optimization Technique (ACO) is discussed here.

Direct Current (DC) motors are broadly used in various industrial applications such as robotics, automobiles, toys and for many other motoring purposes. This is attributable to their extraordinary flexibility, durability and low implementation cost. It is essential to control the speed, position, torque and other variables of the DC motor to achieve the needed performance depending on the area of application. Many classical techniques have been used in the past to control the DC motor, however, such methods typically take a long time, particularly when used for complex nonlinear systems. The application of metaheuristic algorithms as a means of implementing Artificial Intelligence (AI) in this area has proven to be highly effective in overcoming these shortcomings. In recent decades, metaheuristic algorithms have become increasingly prevalent due to their tremendous success in addressing a number real-world optimization challenges in various fields of human activities extending from economic, pharmaceutical and industrial applications to intellectual applications. This review, therefore, presents the optimization of the PID controller with metaheuristic algorithms for controlling the DC motor drives. A short description for each algorithm is presented along with papers published in various renowned journals. For a robust review, the application of various forms of PID controller, as well as different types of DC motors are examined. Finally, the paper presents some open issues and future directions for research.

In order to demonstrate the wind turbine in the laboratory, this paper first analyzed the operation principles, the power and torque characteristics of the wind turbine and direct current (DC) motor, then it investigated the operation characteristics of the wind turbine in contrast to those of the DC motor. The torque imitation scheme was provided, which imitates the torque characteristics of wind turbine by controlling the armature current of DC motor. The scheme has good performance and high feasibility. At last, the simulation of wind turbine operation characteristics was performed, the simulation was done under two typical conditions of variable wind speed and variable machine rotational velocity. The characteristics curves are presented in the paper. The simulation curves are highly consistent with theoretical datum. The torque imitation scheme of wind turbine characteristics can be conveniently used in the study of wind power generation in the laboratory.

Resource-aware MPC for constrained linear systems: Two rollout approaches

Solar trackers rely on a direct-current (DC) motor driver circuit to control the movement of the solar panel. However, conventional DC motor drivers used in solar tracking system do not provide any options for speed and torque control. Hence, the fixed speed of the DC motor leads to either too fast or too slow tracking movement. Usually, the output torque is set to the maximum. If the load (solar panels' weight) is small, the maximum torque is not fully utilized and therefore energy is wasted. So, a fully adjustable DC motor driver for solar tracking system shows great potential in commercialization because highly energy efficient DC motor driver circuit can improves the total efficiency of the solar tracker. Fewer solar panels are needed when they are attached to high efficiency solar tracking system, which will be reflected to lower system cost. Therefore, this enhanced motor driver will bring significant impact to the solar energy industry. The proposed DC motor driver is fully adjustable in term of speed and torque. The speed and torque of the motor is directly proportional to the output voltage and output current of the proposed DC motor driver, respectively. Adaptive controlling of the output voltage and current are possible by installing algorithm in the microcontroller of the DC motor driver and it can be reprogrammed according to the requirement. The speed control makes the solar tracking system to track the Sun more accurately and the torque control saves energy.

The most widely used drilling machinery, such as mud pumps, draw-works, and rotors, use direct-current (DC) motors with independent excitation as the electric drive. Drilling machinery drives operate in harsh ambient conditions, including those with the presence of moisture, dust and vibration, which increases the malfunction rate of both drilling equipment and their electric drives. One of the frequently encountered malfunctions are DC motor excitation coil faults, which disrupt the normal functioning of electric drives, often leading to shutdown of the drilling process. In a four-pole DC motor, the malfunction of one coil leads to lack of excitation current in just one coil pair, while the other pair remains functional. In this case, DC motors and drilling equipment can remain operational, which would allow for continuing the drilling process. This paper considers the possibility of operation of a DC motor on a drilling rig in those cases when one pair of excitation coils is non-functional, and describes the device for switching between the excitation coils and the auxiliary winding in a DC motor with independent excitation.

The Direct Current (DC) motor is widely applied in various implementations. The main problem in the DC motor is controlling the angular speed on the specific reference. This research then proposed an integral state feedback design for tracking control in DC motor, with Simulink Matlab simulation and the Arduino hardware implementation. The results will be compared with the implementation of the PID controller. The integral state feedback controller can handle the system to reach the setpoint with good performance in the simulations, even with changing different poles and setpoints. In the hardware implementation, the current sensor (INA219) and encoder sensor are used since all state variables need to be calculated. Based on the result, the controller can reach the setpoint stably with oscillation. Similar results are showed in simulations with different setpoints. Compared with the PID Controller, the integral state feedback controller has a better response with faster rise time and faster settling time.

Smoothly speed range changing, easily speed controlling, and swiftly dynamic response for load torque changing are the main merits which are delivered by direct current (DC) motors. They are also distinguished by their versatility. All these characteristics make the DC motors suitable candidates for various applications. An accurate high-speed control with a good dynamic response, would be of demand for many applications of the DC motors. Controlling the speed of motors using conventional systems is one of the most important method that is adopted and it can be more efficient when used with electronic power devices to control the output voltage. Hence, this paper introduces an efficient proportional integral (PI) speed controller for DC motor fed by direct current-direct current (DC-DC) convertor, which is switched by pulse-width modulation technique. MATLAB/Simulink environment is used to build the whole system. Two operation scenarios have been conducted including constant load with variable speed and variable load with constant speed.

SummaryThe chapter deals with neural networks and learning machines for engine control applications, particularly in modeling for control. In the first section, basic features of engine control in a layered engine management architecture are reviewed. The use of neural networks for engine modeling, control and diagnosis is then briefly described. The need for descriptive models for model-based control and the link between physical models and black box models are emphasized by the grey box approach discussed in this chapter. The second section introduces the neural models frequently used in engine control, namely, MultiLayer Perceptrons (MLP) and Radial Basis Function (RBF) networks. A more recent approach, known as Support Vector Regression (SVR), to build models in kernel expansion form is also presented. The third section is devoted to examples of application of these models in the context of turbocharged Spark Ignition (SI) engines with Variable Camshaft Timing (VCT). This specific context is representative of modern engine control problems. In the first example, the airpath control is studied, where open loop neural estimators are combined with a dynamical polytopic observer. The second example considers modeling the in-cylinder residual gas fraction by Linear Programming SVR (LP-SVR) based on a limited amount of experimental data and a simulator built from prior knowledge. Each example demonstrates that models based on first principles and neural models must be joined together in a grey box approach to obtain effective and acceptable results.

The development of photovoltaic has shown the maturity of technology. The application can already be used as a source of electrical energy and is an environmentally friendly source of electrical energy. The use of PV technology in Indonesia has developed well for the generation of electricity for companies or household units as an alternative energy source. Currently, Indonesia has begun to develop electric car transportation by using batteries, so that it was need inverter equipment which change a direct current to the alternating current. This paper discusses the comparison of power consumption 125 watts pump by using alternating current (AC) and direct current (DC) based on solar energy using photovoltaic (PV). The type PV cell uses a 100-watt peak solar cell type silicon mounted on a portable basis and parallel connected. The PV is installed at Semarang region which connected by battery. The type battery is 100 AH, 12 V. The battery was connected to motor pump of 125 watts. There are two motors type which has specification as DC motor and AC motor. The DC motor should be connected by DC-DC converter before DC motor pump to increase the requirement voltage of motor pump while AC motor should be provided by inverter DC to AC. The pump was connected by piping system which suction pipe use a diameter of 32 mm and discharge pipe of 20 mm. The total head for both experiment is 4 m. The speed of motor was measured as in motor specification. The operating of PV was at 08.00 am – 16.00 pm. The result of the power consumption of the DC motor was more efficiency than by using AC motor. The operation of the battery using DC motor is about two times longer than AC motor.

This paper presents a novel interval observer design for uncertain locally Lipschitz continuous-time (CT) and discrete-time (DT) systems with noisy nonlinear observations that is input-to-state stable (ISS) and minimizes the L1-gain of the observer error system with respect to the uncertainties. Using mixed-monotone decompositions, the proposed observer is correct and positive by construction without the need for additional constraints/assumptions. This, in turn, allows us to directly leverage techniques for positive systems to design an ISS and L1-robust interval observer via mixed-integer (linear) programs instead of semi-definite programs with linear matrix inequalities. Further, our observer design offers additional degrees of freedom that may serve as a surrogate for coordinate transformations. Finally, we demonstrate the effectiveness of our proposed observer on some CT and DT systems.