Design of a multi-DSP system using TMS320C25 and optimal scheduling for digital controllers

This paper describes the medium voltage high power DVR (dynamic voltage restorer) with the new voltage disturbance detection method and the real-time digital voltage control. The new voltage disturbance detector was implemented by using the delta rule of the neural network control. Through the proposed method, we can instantaneously obtain the peak value of each phase voltage even under the single phase input voltage conditions. Compared to the conventional synchronous reference frame method, the proposed one shows the minimum time delay to determine the instance of the voltage sag or voltage swell event. Also real-time digital voltage control technique was adopted, where the inverter output filter capacitance voltage, the filter reactor current and the load current are sampled to calculate the inverter PWM command for the next sampling interval. By using digital control, the disturbance voltage can be compensated to the reference voltage level within two sampling intervals. The proposed disturbance detector and the voltage compensator were applied to the medium voltage high power DVR (22.9 kV/4 MVA) that was developed for the application of semiconductor manufacture plant. The performances of the proposed DVR control were verified through computer simulation and experimental results. Finally, conclusions are given.

Novel cyber-physical architecture for optimal operation of renewable-based smart city considering false data injection attacks: Digital twin technologies for smart city infrastructure management

An optimal scheduling algorithm for minimizing the computing period of cyclic synchronous tasks on multiprocessors

This thesis treats different aspects of the class of Mixed-Integer Optimal Control Problems (MIOCPs). These are optimization problems that combine the difficulties of underlying dynamic processes with combinatorial decisions. Typically, these combinatorial decisions are realized as switching decisions between the system’s different operations modes. During the last decades, direct methods emerged as the state-of-the-art solvers for MIOCPs. The formulation of a valid, tight and dependable integral relaxation, i.e., the formulation of a model for fractional values, plays an important role for these direct solution methods. We give detailed insight into several relaxation approaches for MIOCPs and compare them with regard to their respective structures. In particular, these are the typical solution’s structures and properties as convexity, problem size and numerical behavior. From these structural properties, we deduce some required specifications of a solver. Additionally, the modeling and subsequent limitation of the switching process directly tackle the class-specific typical issue of chattering solutions. One of the relaxation methods for MIOCPs is the outer convexification, where the binary variables only enter affinely. For the approximation of this relaxation’s solution, we took up on the control approximation problem in integral sense derived by Sager as part of a decomposition approach for MIOCPs with affine binary controls. This problem describes the optimal approximation of fractional controls with binary controls such that the corresponding dynamic process is changed as little as possible. For the multi-dimensional problem, we developed a new heuristic, which for the first time gives a bound that only depends on the control grid and not anymore on the number of the system’s controls. For the generalization of the control approximation problem with additional constraints, we derived a tailored branch-and-bound algorithm, which is based on the properties of the Lagrangian relaxation of the one-dimensional problem. This algorithm beats state-of-the-art commercial solvers for Mixed-Integer Linear Programs (MILPs) for this special approximation problem by several orders of magnitude. Overall, we present several, partially new modeling approaches for MIOCPs together with the accompanying structural properties. On this basis, we develop new theories for the approximation of certain relaxed solutions. We discuss the efficient implementation of the resulting structure exploiting algorithms. This leads to a deeper and better understanding of MIOCPs. We show the practicability of the theoretical observations with the help of four prototypical problems. The presented methods and algorithms allow on their basis the direct development of decision support and analysis tools in practice.

Digital controls have become the primary form of control in numerous applications due to the advancements in semiconductor industry and lower cost. Digital control algorithms implemented on digital signal processors (DSPs) or microcontrollers execute the algorithm at a specified clock frequency. Discrete time algorithms such as digital filters and digital PID controllers require the sampling period in the controller design, which is directly related to the microcontroller clock frequency. Due to aging, manufacturing process defects and environment conditions cause the clock frequency to drift from the specification. Such variation affects the discrete time algorithm performance deviate from expected performance.

In order to study the control theory, students need to learn about basic theories that are sometimes difficult to understand. Only in-class lecturing is not enough, and hand-on practices are very important, in which theory and practice can be integrated to create knowledge and skills simultaneously. Although there are many learning tools available for practicing with sample exercises, they are not enough for students to understand properly especially in the subject that are abstraction and requires imagination. This paper presents a didactic tool for a study of leveling control system which maintains the surface level using multiple sensors including IMUs and ultrasonic sensors, and multiple models including digital filters, coordination, digital automatic control, and kinematic model. The data obtained from the IMU are used to calculate the tilt angle using the complementary filter method, and from the ultrasonic sensors are used to find the distance between the platform and ground using low-pass filter. The difference tilt from both roll and pitch angles and the distance are used to control the tilt angle and the correct distance using the PID controller. This system can be used to study IMU sensor functions, digital signal processing and digital controller as well, and will enable students to understand and use the sensor system to easily create automatic control systems in the future.

A visual CAD platform for designing the positioning system of optical disk drives is described in this paper. The platform consists of the opto-mechanical assembly (OMA) and its simulator of an optical disk drive, a servo control board (SCB) with a high performance digital signal processor (DSP), and a personal computer (PC). The OMA and SCB form the complete digital positioning control system of an optical disk drive. The OMA simulator and SCB provide a real-time simulation environment under which a digital controller (i.e., the DSP program) is run. On a PC with the CAD software packages, the controller can be conveniently designed and loaded into SCB. Furthermore, the behavior of the disk drive and the status, parameters and structure of the controller are visualized on the PC's display without interrupting the controller. The visualization can be implemented on three levels: post-processing, tracking, and even steering.

Electromagnetic waves are transmitted by radars and reflected by different objects, and radar signal processing is highly significant as its analyses can lead to the acquisition of important information such as the situation and radial movement speed. Moreover, deep learning has gained much attention in several fields, and it can be utilized to implement radar signal processing. Compared with the traditional methods, deep learning can realize automatic feature extraction and yield highly accurate results; hence, in this paper, the application of deep learning algorithm in radar signal processing is studied. In addition, the study directions in radar signal processing are summarized into overfitting and interpretation. Thus, these two issues are being considered.

In this paper, an efficient power electronic circuit simulation approach is discussed for a digitally controlled three phase active PFC converter system. The control circuit simulation software used in this simulation technique is also applied to the digital signal processor (DSP) based control implementation of a a practical power factor correction (PFC) power conversion circuit with a digital control scheme. This circuit simulation technique is based on a circuit equation modeled by substituting control input dependent time-varying resistors in place of all the power switches incorporated in the bridge arms of the three phase active PFC converter circuit and system treated here, one state-vector equation described by state-variables for inductors and capacitors, together with an algebraic computation method to transform the matrix of the circuit equation into matrix of the state vector equation. In addition, this paper proves the effectiveness of a voltage-fed three phase PFC converter with a digital control PWM strategy and its performance evaluations on the basis of computer-aided simulation results together with experimental result.

Implementation of digital controllers in embedded environment suffers from the inherent problems associated with analog-digital signals interfacing in hard real-time, therefore, the control algorithms are invariantly subjected to approximations. This paper presents a novel technique for implementation of an efficient FPGA based digital Proportional-Integral-Derivative (PID) controller for the motion control of a permanent magnet DC motor. The implementation technique circumnavigates the problem of interfacing analog and digital systems in real-time. The controller is used in a speed control loop. The hardware implementation has been done on a Xilinx Spartan 3 FPGA chip. A novel technique has been adopted for the generation of the control input as a PWM signal for controlling the motor driver circuit and decoding the optical encoder data for using it for the speed feedback in the PID control loop. The VHDL algorithm for the proposed implementation has also been presented in this paper. A comparison of the experimental results with the Matlab <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> based simulation shows the effectiveness of the proposed method.

Modern High performance control applications demanded from mixed-signal and digital signal processors (DSPs) are ever increasing. As digital circuits and DSP operate at a higher rate, a considerable amount of noise and radiation degrades the system?s performance and creates EMI problems that make it difficult to pass tests required to obtain certification by the EMC regulations. In this paper, we introduce some effective methods for reduced EMI of the measurement and control systems, which are power supply design, clock and phase-locked loop (PLL) isolation, decoupling techniques, digital and analog partitioning, printed circuit board (PCB) layout, and so on for meeting many challenges of mixed-signal and DSP systems design. Design guidelines for improved EMC and signal integrity are derived from the results obtained, thus, the evaluation board of the measurement and control systems is especially suitable for performing function in high definition array induction log (HDAIL).

This paper presents a novel approach to combine trajectory optimization and gain scheduling for a nonlinear dynamic inversion controller, in order to optimize both guidance commands and control response. Therein, the guidance problem is formulated as an optimal control problem that also incorporates inner-loop dynamics based on a nonlinear dynamic inversion control block. At the same time, the gain profile for this control block is incorporated into the optimization problem as additional variables. As a result, the optimization process not only optimizes the required guidance commands based on knowledge of the control response, but also the control response itself. The optimal control problem is transcribed into a nonlinear optimization problem by direct multiple shooting, while the resulting nonlinear program is solved with an sequential quadratic programming method. The optimization procedure is augmented by an ordinary differential equation formulation to obtain the required sensitivity terms, as well as a condensing procedure to decrease the size of the auxiliary quadratic problem within the iterative optimization algorithm. Numerical results are presented that illustrate the feasibility of this approach and that indicate potential benefits.

Multi-cell inverter include an array of singlephase inverters capable of handling higher voltage ratings with lower rating power electronics devices. In this paper, a Real Time Digital Feedback Controller (RTDFBC) combined with a Repetitive Controller is proposed to control a Variable Frequency Drive (VFD) fed by a multi-cell inverter. This digital control is characterized by a very fast transient response, low switching losses, and a proper compensation for load disturbances and cyclical fluctuations.

Real-time systems for wireless communication, digital signal processing and control experience a wide gamut of operating conditions (signal/channel noise, workload demand, perturbed process conditions). As device bandwidths expand, it becomes increasingly expensive, from a power consumption and reliability perspective, to operate such real-time systems for worst-case (static) performance requirements. In contrast, it is attractive to design algorithms, architectures and circuits that are power-performance tunable and can adapt dynamically, via self-learning techniques, to the requirements of system-level applications for extended battery usage and device lifetime. Such future systems will feed application level demands to the underlying algorithm-architecture-circuit design fabric through built-in sense-and-control infrastructure (hardware, software). The sense functions assess instantaneous application level demands (e.g. throughput, signal integrity) as well as the performances of the individual hardware components as determined by manufacturing process conditions. The control functions actuate algorithm-through-circuit level tuning knobs that continuously trade off performance vs. power of the individual software and hardware modules in such a way as to deliver the end-to-end desired application level Quality of Service (QoS), while minimizing energy/power consumption. Application to wireless communications systems, digital signal processing and control algorithms is discussed.

Numerical linear algebra, digital signal processing, and parallel algorithms are three disciplines with a great deal of activity in the last few years. The interaction between them has been growing to a level that merits an Advanced Study Institute dedicated to the three areas together. This volume gives an account of the main results in this interdisciplinary field. The following topics emerged as major themes of the meeting: - Singular value and eigenvalue decompositions, including applications, - Toeplitz matrices, including special algorithms and architectures, - Recursive least squares in linear algebra, digital signal processing and control, - Updating and downdating techniques in linear algebra and signal processing, - Stability and sensitivity analysis of special recursive least squares problems, - Special architectures for linear algebra and signal processing. This book contains tutorials on these topics given by leading scientists in each of the three areas. A consider- able number of new research results are presented in contributed papers. The tutorials and papers will be of value to anyone interested in the three disciplines.