Predictable multi-core implementation of multi-rate sensor fusion for high-precision positioning systems
- A predictable and composable multi-core system-on-chip (MPSoC) platform designed for developing embedded control applications with strict performance requirements.
- Predictable multi-core implementation of multi-sensor fusion imposing (nearly) constant delay.
- Reducing sensing delay using predictable parallel and pipelined implementation.
Improved Positioning Precision using a Multi-rate Multi-sensor in Industrial Motion Control Systems
- A multi-rate multi-sensor fusion algorithm fusing accurate but slow and delayed vision sensor data and fast but less accurate linear encoder data along with a bias correction solution to correct the effect of external disturbances.
- The proposed fusion algorithm offers a higher-accuracy positioning estimation at a high operating frequency.
- An evaluation framework to analyze and optimize the performance of multi-rate multi-sensor industrial motion control systems.
An Evaluation Framework for Vision-in-the-Loop Motion Control Systems
- The SIL simulation to evaluate the effects of vision sensor feedback and the operating environment on the motion control system.
- The PIL simulation of C code for discrete-time controller and image processing algorithm on an instance of the CompSOC platform. This feature further establishes interfacing with CoppeliaSim using application programming interfaces (APIs).
- Automatic code generation for the VIL system software targeting the CompSOC platform.
FPGA Implementation Framework for Accelerating Nonlinear MPC Through Machine Learning
- Proposed a framework for accelerating Nonlinear Model Predictive Control(MPC) through Machine Learning
- Approximated control law using Deep Neural Network(DNN) for a nonlinear system
- DNN-based NMPC implemented on a Xilinx’s ZYNQ-7000 SoC ZC706 FPGA board using low-level C/C++ code and demonstrated for a flying robot control application.
A Memory Efficient Implementation of Offset-Free Explicit Model Predictive Controllers on FPGA using Posits
- Proposed a novel approach for memory efficient embedded implementation of MPC using Posit numbers
- HIL co-simulation for Posit-based offset-free Explicit MPC on FPGA
- Detailed analysis of posit based offset-free EMPC such as FPGA resources utilization, power utilization, Posit operations per second
- Demonstrated on Citation Aircraft and Anesthesia control model
A Framework for High accuracy low precision embedded model predictive control using posits
- Proposed a high accuracy and low memory quadratic programming solver using posit numbers
- Proposed Posit-based QP solvers
- Embedded implementation framework for posit based MPC
- Demonstrated on Couple tank, Double integrator, Benchmark convex QP problem repository
A Memory efficient explicit model predictive control using posits
- Proposed a novel approach for memory reduction in Explicit MPC
- Posits based EMPC
- Memory utilization calculation and comparisons with classical IEEE-754 number based MPC.
- Couple Tank Control
Development of Posit Arithmetic and Logical Unit (ALU) in Verilog and its HIL Co-simulation on FPGA
- Developed Verilog functions for posit addition and multiplication
- Tested with Xilinx system generator in MATLAB Simulink
- HIL co-simulations of all posit arithmetic on FPGA
Stochastic MPC using Stochastic Gradient Descent (SGD), Stochastic Proximal Point (SPP)
- Development of SGD, SPP, proximal point algorithms in MATLAB
- Convergence rate analysis for large scale standard datasets
- Non-smooth optimization, composite optimzation
- Solving optimization problems such as l2 SVM, Hinge loss, logarithmic regression
Design and development of first order unconstrained and Constrained optimization methods
- Development of Steepest descent, Newton Method, Conjugate gradient and BFGS, Penalty barrier, SQP optimization methods
- Performance comparison for checking convergence rate and simulation time
- Embedded implementation for improving timing constraints
Linear and Explicit MPC on FPGA
- Implemented Interior Point Method, Active Set Method for Linear MPC.
- MPT toolbox, Hybrid toolbox
- Framework for embedded implementation using FPGA, STM Microcontrollers
- Couple tank, Anesthesia, Aircraft, 2DOF helicopter control
Framewok design in MATLAB for auto tuning of PID Controller
- Developed Ziegler-Nichols tuning method in MATLAB for Auto tuning of PID controller
- Verification of Kp, Ki and Kd parameters values using inbuilt MATLAB auto tune features to compare the performance.
- C code development for embedded implementation
- Designed GUI for PID auto-tuner for Type-I,II and III transfer functions
- GUI developed with features of closed loop response, PID tuning parameter, C code generation
Mathematical modeling and simulations
- Two tank, Quadruple Tank System
- Anesthesia control problem
- Citation Aircraft
- 2DOF helicopter
- Inverted Pendulum, Crane model
- Boiler, Heat exchanger
- DC motor