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D R . T A R E K A . T U T U N J I
M E C H A C T R O N I C S Y S T E M D E S I G N
P H I L A D E L P H I A U N I V E R S I T Y
2 0 1 4
Control Systems Overview REV II
Control Systems
The control system is at the heart of mechatronic systems and its selection is arguably the most critical decision in the design process.
The controller selection involves two inter-dependent parts:
The control method (i.e. software)
The physical controller (i.e. hardware)
O P E N V S . C L O S E D L O O P C O N T R O L
P R O C E S S V S . M O T I O N C O N T R O L
T R A N S I E N T A N D S T E A D Y S T A T E S P E C I F I C A T I O N S
Basic Control Concepts
Open-Loop Control
[Ref] Kilian
Closed-Loop Control
[Ref] Kilian
Control Systems Classification
Control systems are classified by application.
Process control usually refers to an industrial process being electronically controlled for the purpose of maintaining a uniform correct output.
Motion control refers to a system wherein things move. A servomechanism is a feedback control system that provides remote control motion of some object, such as a robot arm or a radar antenna.
Process Control
[Ref] Kilian
Process Control Example
[Ref] Kilian
Motion Control
Motion Control Examples
[Ref] Kilian
CNC Machine Robot Manipulator
General Control System
First Order Systems
First Order Systems
Second Order Systems
Performance Criteria
Transient Response
Transient response is the shape of a signal as it moves between two steady-state points.
It is quantified in terms of two parameters:
The damping ratio, z, pronounced zeta
The natural undamped frequency, wn.
Pole Locations
The poles location is the major factor for a systems’ transient response
Step Response Comparisons
Steady-State Error
Accuracy (or steady-state tracking error) is the error between input and output signals in the steady state for a system.
Three input signals can be used
Step
Ramp
Parabola
Steady-State Error
Steady-State Error
Stability
A stable system is one which produces a bounded, or finite, response when subjected to a bounded input
Stability conditions
A system is stable if the real part of all poles are < 0.
A system is marginally stable if real part of all poles are <= 0.
A system is unstable if the real part of any pole is positive.
T A R E K A . T U T U N J I
Control Methods
Dr. Tarek A. Tutunji
Control Techniques / Strategies
Classical Control
Advanced Control
Intelligent Control
Dr. Tarek A. Tutunji
Classical Control
Classical control design are used for SISO systems.
Most popular concepts are:
Bode plots
Nyquist Stability
Root locus.
PID is widely used in feedback systems.
Classical Control: On-Off Control
This is the simplest method of control. The control action has three possible outputs: on; off; no change. This method is usually used for slow-acting operations (such as a refrigeration unit).
The advantage is its ease of design and low cost. However, it cannot vary the controlled variable with precision.
On-Off Control Example
Classical Control: PID
Dr. Tarek A. Tutunji
Proportional-Integral-Derivative (PID) is the most commonly used controller for SISO systems
dt
)t(deKdt)t(eK)t(eK)t(u DIp
PD Design Example
Analog PID Implementation
[Ref] Kilian
Digital PID Control
Digital
Analog
Tarek A. Tutunji
Digital PID Realization
Required Operations: •Multiplication •Addition •Delay
Discrete PID Implementation
Digital Control Block Diagram
Classical Control: Root Locus
Discrete Systems: Pole Locations
Advanced Control
Adaptive control methods modify the control law used by a controller to cope with time-varying parameters. For example, as an aircraft flies, its mass will slowly decrease as
a result of fuel consumption; we need a control law that adapts itself to such changing conditions.
Robust control methods deal with uncertainty. They guarantee that if the changes are within given bounds the
control law need not be changed.
Optimal control uses math optimization methods to solve a set of differential equations. Two such methods are: Model Predictive Control (MPC) Linear-Quadratic-Gaussian control (LQG).
Intelligent Control
Dr. Tarek A. Tutunji
Intelligent controllers are used for high-level control
Intelligent controllers are also used when the system must make decisions (from several alternatives) based on input data from sensors.
Intelligent Control is usually used when the mathematical model for the plant is unavailable or highly complex.
The most two commonly used intelligent controllers are
Artificial Neural Networks
Fuzzy Logic
Intelligent Control: Fuzzy
Fuzzy set theory provides mathematical tools for carrying out approximate reasoning processes when available information is uncertain, incomplete, imprecise, or vague.
Fuzzy logic controllers manage complex control problems through heuristics (IF … THEN) and mathematical models provided by fuzzy logic, rather than via mathematical models provided by differential equations.
This is particularly useful for controlling systems whose mathematical models are nonlinear or for which standard mathematical models are simply not available
Fuzzy Control
Fuzzy Control
Dr. Tarek A. Tutunji
Intelligent Control: ANN
Artificial Neural networks (ANN) are nonlinear mathematical models that are used to mimic the biological neurons in the brain.
ANN are used as black box models to map unknown functions
ANN can be used for: Identification and Control
ANN: Single Neuron
y
w0
w1
wM
x1
x2
xM
f(net)
M
mmmwxfy
1
Neural Nets
TDL
TDL
Weights
Weights
Log
Function + Weights +
Log
Function
Plant
Output
Plant
Input
Net
Output
First Layer Second Layer
ANN: Identification and Control
Identification Control
ANN: Identification and Control
Intelligent Controllers Applications
Intelligent Controller Application
•Low Level PID Control for velocity control •High Level Intelligent Control:
•Fuzzy for Decision making •Neural nets for Image Analysis
D R . T A R E K T U T U N J I
Hardware Controllers
Analog vs. Digital Control Systems
Analog Digital
Time variable Continuous Discrete
Time equations Differential equations Difference equations
Frequency transforms Laplace Z-Transform
Stability Poles on LHS Poles inside unit circle
Controller Hardware: Op-Amps Software: None
Hardware: Microcontroller Software: Program
Dr. Tarek A. Tutunji
Criteria for Choosing Controller
Price Size and Weight Number of Digital Inputs and Outputs Number of Analog Inputs and Outputs Speed Required Interrupt Required hardware Communication Interface Reliability Memory Programming Capability Software Support
Dr. Tarek A. Tutunji
Hardware Controllers
Microcontroller
PLCs
DSPs
FPGA
PC with DAQ
Dr. Tarek A. Tutunji
Microcontrollers
Microcontroller is a special type of small computer that can perform a specific job
Microcontrollers
The microcontroller is a computer-on-chip. It is an integrated circuit that contains microprocessor, memory, I/O ports and sometimes A/D converters. It can be programmed using several languages (such as Assembly or C/C++). It can be used in manufacturing lines, but requires additional hardware. Microcontrollers are mainly used in engineering products such as washing machines and air-conditioners.
Dr. Tarek A. Tutunji
Microcontrollers Companies
Microcontroller Market Share
Arduino
Arduino is an open-source electronics prototyping platform based on flexible, easy-to-use hardware and software.
The hardware consists of a simple open source hardware board designed around an 8-bit Atmel AVR microcontroller, though a new model has been designed around a 32-bit Atmel ARM
ARM
The ARM architecture describes a family of RISC-based computer processors designed and licensed by British company ARM Holdings.
As an IP core business, ARM Holdings itself does not manufacture its own electronic chips, but licenses its designs to other semiconductor manufacturers
PLCs
A Programmable Logic Controller (or PLC) is a specialized digital controller that can control machines and processes. it monitors inputs, makes decisions, and controls outputs in order to automate machines and processes
Programmable Logic Controller
PLC’s are a user-friendly, microprocessor-based, specialized computer that is used for process control. It contains input/output (I/O) modules for appropriate sensors/actuator interfaces. It is mainly used in automated manufacturing lines. The PLC is usually used for simple logic operations. It is considered reliable and easy to program (using ladder diagrams, instructions, or function blocks).
Dr. Tarek A. Tutunji
PLC Manufacturers
PLC vs. Microcontroller
Usually PLCs are used in an industrial environment, where as the microcontrollers are smaller and well suited for embedded situations.
PLCs are programmed with ready made blocks or programming elements, whereas in Microcontrollers a programming language must be used to write a programming code
PLC Advantages
They are highly reliable, fast and flexible.
They can handle severe conditions such as dust, humidity etc.
They can communicate with other controllers.
They are easy to program and troubleshoot.
They include display units.
Digital Signal Processors
Digital Signal Processing (DSP) is the arithmetic processing of discrete-time signals. A/D is needed for analog signals
Digital signal processors (DSP) are specialized
microprocessors with advanced architectures (such as multiple buses, parallel processing, hardware multipliers and fast sampling rate) that are designed to reduce the number of instructions and operations necessary for efficient processing.
DSP chips enable developers to implement complex
algorithms and perform computationally efficient and fast algorithms. DSP are preferred over microcontrollers when the need for complex and
iterative control algorithms is required.
Dr. Tarek A. Tutunji
DSP Operations: Convolution
Convolution requires:
Reflection
Shift
Multiplication
Addition
-k
k)x(k)h(nh(n)*x(n)y(n)
h(n)
x(n) y(n)
DSP Architecture Features
Parallel Processing (Modified Harvard)
Deep Instructions Pipeline
Very Fast A/D
Hardware Multiplier
Barrel Shifter
RISC
Dr. Tarek A. Tutunji
Modified Harvard Architecture
A Harvard architecture employs separate program and data buses to access separate data and program memories.
A modified Harvard architecture.
DSP use multiple data buses (and multiple associated address buses) so that the processing of two signals can be done in parallel.
The address buses are also separate. This multiple bus arrangement increases speed since instructions and data can move in parallel, and execute simultaneously rather than sequentially.
Modified Harvard Architecture
DAGEN A
DAGEN B Memory
A Memory
B
ALU Multiplier
Shifter
Accumulators
Shifter Memory
C
DAGEN C
Instruction Pipelining
Up to six levels of pipelining are implemented.
DSP can execute instructions in parallel
Overall execution times are accelerated so that high
Hardware Multiplier
A 16- by 16-bit hardware multiplier multiplies and stores results in a 40-bit accumulator (8 guard bits) in a single instruction cycle.
Thus, multiply and accumulate operations can be performed in a single clock cycle in a DSP; conventional processors may require tens of cycles for this operation.
Shifters and RISC
Hardware shifters allow scaling, prevent overflows, and maintain required precision.
An on-chip hardware stack reduces interrupt response time and minimizes stack pointer manipulations.
DSP use reduced instruction sets tailored to digital signal processing operations. For example, the MACD command implements four operations in one instruction: multiplies two values moves data adds the product to a previous result transfers the result to an adjacent register.
Digital Signal Controllers Manufacturers
Texas Instruments.
TMS320C2000™ DSP Platform
Microchip.
dsPIC30F3010
Motorola
Custom made DSP Engines
Field Programmable Gate Arrays
The field-programmable gate array (FPGA) is a semiconductor device that can be programmed after manufacturing.
Instead of being restricted to any predetermined hardware function,
an FPGA allows you to program product features and functions, adapt to new standards, and reconfigure hardware for specific applications even after the product has been installed in the field—hence the name "field-programmable".
FPGAs can be used to implement any logical function that an application-specific integrated circuit (ASIC) could perform. One advantage is its ability to update the functionality after shipping.
FPGAs vs. Microcontrollers
FPGAs can perform concurrent operations while the microcontrollers’ operations are sequential. This makes FPGAs better suited for real-time applications such as executing
DSP algorithms.
FPGA are flexible, you can add subtract the functionality as
required. This can not be done in microcontroller. FPGAs are hard-wired and the random attack of alpha rays can not
destroy/corrupt the memory areas hence collapse the device functionality.
FPGA based development is longer while microcontrollers change
too often and there is lots re-work required to do in order to keep pace with changing technology. This is necessary to save the design from being obsolete.
Dr. Tarek A. Tutunji
FPGAs vs. Microcontrollers
The development time for microcontroller is shorter and that of FPGA
The microcontroller peripherals are readily available and tested by
the vendor. As for the FPGA, open source soft-peripherals are available, but still need to be embedded and tested.
Microcontroller are power efficient. Microcontroller are low-cost, much lower than FPGAs. This is
specially true for small applications and large quantities. Microcontrollers are available in easy to solder SOIC and QFP
package while FPGAs offer limited sources.
Dr. Tarek A. Tutunji
Personal Computers
Personal computers are used when extensive signal processing and in-depth analysis is required.
This will require Data Acquisition Cards (DAQs) to interface
the I/O power and signals between the PC and the environment.
Advantages include superior graphical and software
flexibility. However, the cost is high and, therefore, they are not suitable
for a large number of products Another disadvantage is the speed
Dr. Tarek A. Tutunji
PCs and DAQs
Summary
The selection of the controller is arguably the most important issue of the mecahtronics system
This choice can be divided into two parts:
1. Software/Firmware algorithm On-Off, PID, Adaptive, Robust, Optimal, and Intelligent
2. Hardware system Microcontroller, PLC, DSP, FPGA, and PC-DAQ
Dr. Tarek A. Tutunji