Delivered across the US and Europe

Training Courses

35+

Years Delivering Training

10+

Companies Trained

Delivery Formats

Continents

An example introduction from one of ISC's on-demand, self-teaching courses — Control Fundamentals: Theory and Practice, presented by Mike Grimble and Paweł Majecki.

Delivery Formats

At Company Premises

Delivered on-site, tailored to your team, systems, and specific operational context.

Customised to your existing control systems
Hands-on sessions with your engineering team
Flexible scheduling around production needs

Web Presentations

Delivered remotely, suited to distributed teams across multiple sites or time zones.

Live sessions with Q&A
Suited to multi-site or international teams
Recorded for later reference

Self-Teaching Format

Materials structured for independent study, at your own pace and schedule.

Structured written materials
Self-paced progression
No scheduling constraints

Topics Covered

Predictive and Optimal Control

Robust and Nonlinear Control

Adaptive and Self-Tuning Control

Filtering and State Estimation

Multivariable System Design

Engine and Powertrain Calibration

Course Titles

Offered by ISC Consultants Limited and Grimble Consultancies Limited. Course length can be tailored to company needs, and courses can be presented at company premises, delivered virtually to international sites, or provided in a self-training, on-demand format.

Introductory / Fundamentals

12 courses

Introduction to Artificial Intelligence and Machine Learning in Control
Introduction to the Design of Model Predictive Controllers and Guidelines for Effective Implementation
Control Fundamentals I – Introduction to Basics of Control Systems
Control Fundamentals II – More Advanced Basic Concepts in Control Engineering
Control Engineering Practice – Basic Course with Applications Focus
Introduction to PID Control Design and Tuning
Control Systems Design for Servosystems
Power Systems Control – Generation, Nuclear and Renewable
Introduction to Process Control
Introduction to Wind Turbine Control
Control Fundamentals for Automotive Applications – A Self-Study Course
AI and Machine Learning for Control and Signal Processing Applications

Intermediate

16 courses

Role of Artificial Intelligence and Machine Learning in Advanced Control and Estimation
Modelling, Kalman Filtering, Optimal and Predictive Control
Overview of Modern Control and Optimization Methods
Optimal Control and Optimization Methods
Robust Multivariable Control for Aerospace Applications
Modelling, Identification and Parameter Estimation Methods
Estimation and Kalman Filtering Techniques
Multivariable and Optimal Control Systems Design Methods
Fundamentals of Nonlinear Systems Modelling and Control
Linear and Nonlinear Predictive Control and Applications
Digital Control and Processing (MV, GMV and Predictive Laws)
Introduction to Neural Networks, Fuzzy Control and Global Optimization
Wind Turbine Control (Part 1: Individual Turbines / Part 2: Wind Farms)
Modelling Rolling Mill Processes for Improved Control
Benchmarking Controllers and Automatic Tuning
AI and Machine Learning for Use with Model-Based Optimal and Predictive Controls

Advanced

15 courses

Model Predictive Control Methods and Applications
Estimation and Kalman Filtering Techniques
Robust Optimal and Predictive Control Systems Design Methods
Nonlinear Systems Modelling and Control Design
System Identification, Fault Detection and Adaptive Control
System Identification Methods for Linear and Nonlinear Systems
Filtering and Prediction for Linear and Nonlinear Systems
Advanced Robust Multivariable Control and Stochastic Systems
Wind Turbine Control – Robust Control and Stochastic Systems
Signal Processing for Control Applications and Condition Monitoring
Advanced Control for Hot and Cold Rolling Mills
Nonlinear Predictive Control for Automotive Applications
Control of Autonomous Vehicles and Use of AI and Machine Learning
Electric, Hydrogen and Hybrid Road Vehicle and Heavy-Duty Vehicle Modelling and Control
AI and Machine Learning for Automotive Applications – Battery Estimation, Energy Management

Download full course list (PDF)

Course Syllabi

Advanced Control Fundamentals Course

Multivariable, Optimal, Robust and Predictive Control Systems Design

Six morning web-based sessions

For control specialists, or those advancing beyond the Control Fundamentals course — covers modern modelling, optimal control, robustness, predictive control, and nonlinear design.

Designed for control specialists or to advance the learning of those who have attended the Control Fundamentals course. Covers a range of advanced control topics in overview and introductory form: modern modelling and simulation methods, optimal control and optimisation techniques, dealing with uncertainty, robust and safety-critical control methods, predictive control to handle constraints, nonlinearities and design issues, and application of advanced control problems and solutions.

Day 1: Introduction to Modelling and State Estimation

Modelling dynamic systems, Kalman filters and observers for state estimation, hands-on state estimation session.

Day 2: Introduction to Multivariable and Optimal Control

Multivariable control design and stability, LQ and LQG optimal control, hands-on LQ state feedback design.

Day 3: Uncertainty in Systems

Uncertainty and robustness, hands-on LQG stochastic control design, introduction to H∞ control.

Day 4: Robust Control and H∞ Design Methods

Kalman filtering/LQG/H∞ design example, hands-on H∞ robust design, quantitative feedback theory, introduction to linear MPC.

Day 5: Predictive Control Law Design

MPC with linear parameter-varying models, constrained MPC and quadratic programming solvers, hands-on MPC design.

Day 6: Nonlinear Control Systems

Overview of nonlinear control techniques, hands-on nonlinear control problems, servo system design study, model-based advanced control methods including AI & ML.

Course Deliverables

Copies of the presentations are provided to all delegates
Hands-on MATLAB/Simulink modelling and design examples, with step-by-step problem and solution notes
Presenter emails provided so follow-up questions can be answered
Training course certificates issued on completion, with course details/agenda for company training records

Open full syllabus (PDF)

Control Fundamentals Course

Theory and Practice, and Future Directions

Six afternoon sessions (UK time)

For engineers using control techniques day-to-day who need a refresher, or who only had an introduction to control at university.

Developed and refined over two decades and presented at companies worldwide. Aimed at engineers using control techniques in everyday work who need a refresher, or those with only an introductory background — including calibration and software engineers working alongside control specialists. Course material is motivational, emphasising the use of techniques over background mathematics, with hands-on MATLAB/Simulink exercises throughout.

Day 1: Modelling for Linear Systems

The need for improved control, fundamentals of modelling and simulation, hands-on modelling for controller design.

Day 2: Frequency and Time-Domain Analysis Methods

Linear dynamic systems and transfer functions, frequency response analysis (Bode, Nichols, Nyquist), hands-on linear system representations and controller design.

Day 3: Classical Control Methods for Design

Fundamentals of feedback control design, hands-on control design for linearized systems, frequency domain control design (lead-lag compensation).

Day 4: Classical Control and Control Structures

Hands-on frequency domain design procedure, control system structures (feedforward/feedback, cascade, multivariable), introduction to PID controllers.

Day 5: PID Controllers and Implementation

PID structures and tuning (Ziegler-Nichols, IMC, auto-tuning), hands-on PID tuning, implementation issues (windup, bumpless transfer), hands-on implementation.

Day 6: Practical Aspects and a Look to the Future

What makes control difficult, discrete-time systems and control, hands-on discrete-time design example, a look to the future.

Course Deliverables

Copies of the presentations are provided to all delegates
Hands-on MATLAB/Simulink modelling and design examples, with step-by-step problem and solution notes
Presenter emails provided so follow-up questions can be answered
Training course certificates issued on completion, with course details/agenda for company training records

Open full syllabus (PDF)